diff --git a/Dockerfile b/Dockerfile
index b7d15c68..a49eb92d 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -3,15 +3,13 @@
 # A container for the core semantic-search capability.
 #
 ######################################################
-FROM python:3.12.1-alpine3.19
+FROM python:alpine3.20
 
 
 # Install required packages
 RUN apk update && \
-    apk add g++ make
+    apk add g++ make 
 
-#upgrade openssl \
-#RUN apk  add openssl=3.1.4-r4
 
 RUN pip install --upgrade pip
 # Create a non-root user.
diff --git a/bin/get_bdc_studies_from_gen3.py b/bin/get_bdc_studies_from_gen3.py
index 1a7de3c1..5c5e2c2b 100644
--- a/bin/get_bdc_studies_from_gen3.py
+++ b/bin/get_bdc_studies_from_gen3.py
@@ -105,11 +105,12 @@ def get_bdc_studies_from_gen3(output, bdc_gen3_base_url):
     sorted_study_ids = sorted(discovery_list)
 
     # Step 2. For every study ID, write out an entry into the CSV output file.
-    csv_writer = csv.DictWriter(output, fieldnames=['Accession', 'Consent', 'Study Name', 'Last modified', 'Notes', 'Description'])
+    csv_writer = csv.DictWriter(output, fieldnames=['Accession', 'Consent', 'Study Name', 'Program', 'Last modified', 'Notes', 'Description'])
     csv_writer.writeheader()
     for study_id in sorted_study_ids:
         # Reset the variables we need.
         study_name = ''
+        program_names = []
         description = ''
         notes = ''
 
@@ -139,6 +140,24 @@ def get_bdc_studies_from_gen3(output, bdc_gen3_base_url):
             else:
                 study_name = '(no name)'
 
+            # Program name.
+            if 'authz' in gen3_discovery:
+                # authz is in the format /programs/topmed/projects/ECLIPSE_DS-COPD-MDS-RD
+                match = re.fullmatch(r'^/programs/(.*)/projects/(.*)$', gen3_discovery['authz'])
+                if match:
+                    program_names.append(match.group(1))
+                    # study_short_name = match.group(2)
+
+            # Tags don't seem as fine-grained as authz and are often slightly different from the authz values
+            # (e.g. `COVID 19` instead of `COVID-19`, `Parent` instead of `parent`), so for now we only use the authz
+            # values.
+            #
+            # if 'tags' in gen3_discovery:
+            #     for tag in gen3_discovery['tags']:
+            #         category = tag.get('category', '')
+            #         if category.lower() == 'program':
+            #             program_names.append(tag.get('name', '').strip())
+
             # Description.
             description = gen3_discovery.get('study_description', '')
 
@@ -156,11 +175,15 @@ def get_bdc_studies_from_gen3(output, bdc_gen3_base_url):
             accession = study_id
             consent = ''
 
+        # Remove any blank program names.
+        program_names = filter(lambda n: n != '', program_names)
+
         csv_writer.writerow({
             'Accession': accession,
             'Consent': consent,
             'Study Name': study_name,
             'Description': description,
+            'Program': '|'.join(sorted(set(program_names))),
             'Last modified': last_modified,
             'Notes': notes.strip()
         })
diff --git a/bin/get_dbgap_data_dicts.py b/bin/get_dbgap_data_dicts.py
index a67e08b2..25e1fbdd 100644
--- a/bin/get_dbgap_data_dicts.py
+++ b/bin/get_dbgap_data_dicts.py
@@ -16,6 +16,10 @@
 # Default to logging at the INFO level.
 logging.basicConfig(level=logging.INFO)
 
+# FTP timeout in seconds
+FTP_TIMEOUT = 100
+
+
 # Helper function
 def download_dbgap_study(dbgap_accession_id, dbgap_output_dir):
     """
@@ -28,7 +32,7 @@ def download_dbgap_study(dbgap_accession_id, dbgap_output_dir):
 
     count_downloaded_vars = 0
 
-    ftp = FTP('ftp.ncbi.nlm.nih.gov')
+    ftp = FTP('ftp.ncbi.nlm.nih.gov', timeout=FTP_TIMEOUT)
     ftp.login()
     ftp.sendcmd('PASV')
     study_variable = dbgap_accession_id.split('.')[0]
@@ -56,6 +60,8 @@ def download_dbgap_study(dbgap_accession_id, dbgap_output_dir):
         return 0
 
     ftp_filelist = ftp.nlst(".")
+    ftp.quit()
+
     for ftp_filename in ftp_filelist:
         if 'data_dict' in ftp_filename:
             with open(f"{local_path}/{ftp_filename}", "wb") as data_dict_file:
@@ -73,13 +79,20 @@ def download_dbgap_study(dbgap_accession_id, dbgap_output_dir):
                 logging.info(f"Downloaded {ftp_filename} to {local_path}/{ftp_filename} in {response.elapsed.microseconds} microseconds.")
             count_downloaded_vars += 1
 
+    # Sometimes we've timed out on the FTP server by this point. So let's disconnect and reconnect.
+    ftp = FTP('ftp.ncbi.nlm.nih.gov', timeout=FTP_TIMEOUT)
+    ftp.login()
+    ftp.sendcmd('PASV')
+
     # Step 2: Check to see if there's a GapExchange file in the parent folder
     #         and if there is, get it.
     try:
         ftp.cwd(study_id_path)
     except error_temp as e:
-        logging.error("Ftp session timed out... Reconnecting")
+        logging.error("FTP session timed out. Reconnecting.")
+        ftp = FTP('ftp.ncbi.nlm.nih.gov', timeout=FTP_TIMEOUT)
         ftp.login()
+        ftp.sendcmd('PASV')
         resp = ftp.cwd(study_id_path)
         if resp[:1] == '2':
             logging.info("command success")
@@ -160,7 +173,12 @@ def get_dbgap_data_dicts(input_file, format, field, outdir, group_by, skip):
         # If multiple group-by fields are specified, we use them in order.
         output_dir_for_row = output_dir
         for group_name in list(group_by):
-            if group_name in row:
+            if group_name in row and row[group_name].strip() != '':
+                if '|' in row[group_name]:
+                    raise RuntimeError(
+                        f"Pipe-separated multiple values in group-by field {group_name} not supported:" +
+                        f"{row[group_name]} (line {line_num})"
+                    )
                 output_dir_for_row = os.path.join(output_dir_for_row, row[group_name])
             else:
                 output_dir_for_row = os.path.join(output_dir_for_row, '__missing__')
@@ -179,9 +197,15 @@ def get_dbgap_data_dicts(input_file, format, field, outdir, group_by, skip):
             # Try to download to output folder if the study hasn't already been downloaded
             if not os.path.exists(dbgap_dir):
                 logging.info(f"Downloading {dbgap_id} to {dbgap_dir}")
-                count_downloaded += download_dbgap_study(dbgap_id, dbgap_dir)
-
-    logging.info(f"Downloaded {count_downloaded} studies from {count_rows} in input files.")
+                try:
+                    count_downloaded += download_dbgap_study(dbgap_id, dbgap_dir)
+                except Exception as ex:
+                    logging.error(f"Exception occurred while downloading {dbgap_id} to {dbgap_dir}: {ex}")
+                    shutil.rmtree(dbgap_dir, ignore_errors=True)
+                    logging.error(f"Deleted {dbgap_dir} as it is probably incomplete.")
+                    logging.error("Re-run this script to ensure that all variables are downloaded.")
+
+    logging.info(f"Downloaded {count_downloaded} data dictionaries from {count_rows} rows in input files.")
 
 
 if __name__ == "__main__":
diff --git a/data/bdc_dbgap_ids.csv b/data/bdc_dbgap_ids.csv
index 6231c7d2..beed29ad 100644
--- a/data/bdc_dbgap_ids.csv
+++ b/data/bdc_dbgap_ids.csv
@@ -1,158 +1,176 @@
-Accession,Consent,Study Name,Last modified,Notes,Description
-phs000007.v31.p12,c1,Framingham Cohort,2023-09-28,"Name: FHS_HMB-IRB-MDS_, short name: FHS.","See Grouping of Framingham Phenotype Datasets Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the ""Variables"" tab above.  The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000007 Framingham Cohort.  phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES   The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.   Study Weblinks:   The Framingham Heart Study    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000007.v31.p12 on 2021-03-25 and may not include exact formatting or images."
-phs000007.v31.p12,c2,Framingham Cohort,2023-09-28,"Name: FHS_HMB-IRB-NPU-MDS_, short name: FHS.","See Grouping of Framingham Phenotype Datasets Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the ""Variables"" tab above.  The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000007 Framingham Cohort.  phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES   The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.   Study Weblinks:   The Framingham Heart Study    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000007.v31.p12 on 2021-03-25 and may not include exact formatting or images."
-phs000166.v2.p1,c1,"National Heart, Lung, and Blood Institute SNP Health Association Asthma Resource Project (SHARP)",2023-09-28,"Name: SHARP_ARR_, short name: SHARP.","SNP Health Association Resource (SHARe) Asthma Resource project (SHARP) is conducting a genome-wide analysis in adults and children who have participated in National Heart, Lung, and Blood Institute's clinical research trials on asthma. This includes 1041 children with asthma who participated in the Childhood Asthma Management Program (CAMP), 994 children who participated in one or five clinical trials conducted by the Childhood Asthma Research and Education (CARE) network, and 701 adults who participated in one of six clinical trials conducted by the Asthma Clinical Research Network (ACRN). There are three study types. The longitudinal clinical trials can be subsetted for population-based and/or case-control analyses. Each of the childhood asthma studies has a majority of children participating as part of a parent-child trio. The ACRN (adult) studies are probands alone. Control genotypes will be provided for case-control analyses.   Study Weblinks:   CAMP CARE ACRN    Study Design:       Cross-Sectional    Study Type:  Longitudinal Parent-Offspring Trios Case-Control   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000166.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000179.v6.p2,c1,"Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute",2023-09-28,"Name: COPDGene_HMB_, short name: COPDGene.","Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this top-level study page phs000179 COPDGene_v6 Cohort.  phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno     Study Weblinks:   COPDGene    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000179.v6.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000179.v6.p2,c2,"Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute",2023-09-28,"Name: COPDGene_DS-CS_, short name: COPDGene.","Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this top-level study page phs000179 COPDGene_v6 Cohort.  phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno     Study Weblinks:   COPDGene    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000179.v6.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000200.v12.p3,c1,Women's Health Initiative Clinical Trial and Observational Study,2023-09-28,"Name: WHI_HMB-IRB_, short name: WHI.","The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are:  Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo.   The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to 'WHI dbGaP Cohort Data Release Data Preparation Guide May 2018' for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000200 WHI Cohort.  phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS     Study Weblinks:   Scientific Resources Website: Women's Health Initiative NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Partial Factorial Randomized Double-Blind Placebo-Controlled Cohort Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000200.v12.p3 on 2021-03-25 and may not include exact formatting or images."
-phs000200.v12.p3,c2,Women's Health Initiative Clinical Trial and Observational Study,2023-09-28,"Name: WHI_HMB-IRB-NPU_, short name: WHI.","The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are:  Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo.   The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to 'WHI dbGaP Cohort Data Release Data Preparation Guide May 2018' for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000200 WHI Cohort.  phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS     Study Weblinks:   Scientific Resources Website: Women's Health Initiative NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Partial Factorial Randomized Double-Blind Placebo-Controlled Cohort Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000200.v12.p3 on 2021-03-25 and may not include exact formatting or images."
-phs000209.v13.p3,c1,Multi-Ethnic Study of Atherosclerosis (MESA) Cohort,2023-09-28,"Name: MESA_HMB_, short name: MESA.","MESA The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by four examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. MESA Air The general goal of the Multi-Ethnic Study of Atherosclerosis and Air Pollution ('MESA Air') is to prospectively examine the relation between an individual level assessment of long-term ambient air pollution exposures (including PM2.5 and the progression of subclinical cardiovascular disease in a multi-city, multi-ethnic cohort. MESA Air will also prospectively examine the relationship between an individual level assessment of long-term ambient air pollution exposures and the incidence of cardiovascular disease, including myocardial infarction and cardiovascular death. MESA AIR is funded by a grant from the United States Environmental Protection Agency to the University of Washington and subcontracts from the UW to other participating institutions. MESA Air will assess if ambient air pollution is associated with changes over time in subclinical measures of atherosclerosis and plasma markers of inflammation, oxidative damage, and endothelial activation in a longitudinal data model, adjusting for age, race/ethnicity, socioeconomic status, and specific cardiovascular risk factors (such as diabetes, hypertension, smoking, and diet). The study will similarly assess if the incidence of cardiovascular events is associated with long-term exposure to ambient air pollution, using a proportional hazards model. The study includes refinement of statistical tools, and explores joint/independent effects of acute and long-term pollutant exposure in the occurrence of cardiovascular disease. The MESA Air study is built on the foundation of the ongoing MESA study. The parent MESA Study cohort is located in six geographic areas ('Field Centers') that capture tremendous exposure heterogeneity, comparable to or greater than the variability in locations of prior U.S. cohort studies. In addition to the six Field Centers, the study involves a Coordinating Center, a Central Laboratory, and Reading Centers for Computed Tomography (CT), ultrasound and air pollution data. The cohort for the MESA Air study currently includes 6226 subjects: 5479 enrolled in the parent MESA study; 257 recruited specifically for this study, and 490 recruited from the MESA Family study. The entire MESA Air cohort will be followed over a 10-year project period for the occurrence of cardiovascular disease events. On two occasions over the ten-year study period, 3600 subjects from the MESA Air cohort, residing in nine locales, will undergo computed tomography scanning to assess presence and extent of coronary artery calcification (CAC), and ultrasound of the carotid artery to determine intima-media thickness (IMT). We will also repeatedly assess plasma markers of inflammation, oxidative damage, and endothelial function in 720 subjects. MESA Air adds state-of-the-art air pollution exposure assessment information to the MESA cohort study, and introduces new subjects and outcome measures to achieve our aims. The study will assess long-term individual-level exposure to ambient air pollutants for each subject using community-scale monitoring, outdoor spatial variation, subject proximity to pollution sources, pollutants' infiltration efficiency, and personal time-activity information. The exposure models will be validated using detailed monitoring in a subset of subjects. The MESA Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000209 MESA Cohort.  phs000420 MESA SHARe phs000283 MESA CARe phs000403 MESA ESP Heart-GO     Study Weblinks:   MESA MESA Air    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Family   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000209.v13.p3 on 2021-03-25 and may not include exact formatting or images."
-phs000209.v13.p3,c2,Multi-Ethnic Study of Atherosclerosis (MESA) Cohort,2023-09-28,"Name: MESA_HMB-NPU_, short name: MESA.","MESA The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by four examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. MESA Air The general goal of the Multi-Ethnic Study of Atherosclerosis and Air Pollution ('MESA Air') is to prospectively examine the relation between an individual level assessment of long-term ambient air pollution exposures (including PM2.5 and the progression of subclinical cardiovascular disease in a multi-city, multi-ethnic cohort. MESA Air will also prospectively examine the relationship between an individual level assessment of long-term ambient air pollution exposures and the incidence of cardiovascular disease, including myocardial infarction and cardiovascular death. MESA AIR is funded by a grant from the United States Environmental Protection Agency to the University of Washington and subcontracts from the UW to other participating institutions. MESA Air will assess if ambient air pollution is associated with changes over time in subclinical measures of atherosclerosis and plasma markers of inflammation, oxidative damage, and endothelial activation in a longitudinal data model, adjusting for age, race/ethnicity, socioeconomic status, and specific cardiovascular risk factors (such as diabetes, hypertension, smoking, and diet). The study will similarly assess if the incidence of cardiovascular events is associated with long-term exposure to ambient air pollution, using a proportional hazards model. The study includes refinement of statistical tools, and explores joint/independent effects of acute and long-term pollutant exposure in the occurrence of cardiovascular disease. The MESA Air study is built on the foundation of the ongoing MESA study. The parent MESA Study cohort is located in six geographic areas ('Field Centers') that capture tremendous exposure heterogeneity, comparable to or greater than the variability in locations of prior U.S. cohort studies. In addition to the six Field Centers, the study involves a Coordinating Center, a Central Laboratory, and Reading Centers for Computed Tomography (CT), ultrasound and air pollution data. The cohort for the MESA Air study currently includes 6226 subjects: 5479 enrolled in the parent MESA study; 257 recruited specifically for this study, and 490 recruited from the MESA Family study. The entire MESA Air cohort will be followed over a 10-year project period for the occurrence of cardiovascular disease events. On two occasions over the ten-year study period, 3600 subjects from the MESA Air cohort, residing in nine locales, will undergo computed tomography scanning to assess presence and extent of coronary artery calcification (CAC), and ultrasound of the carotid artery to determine intima-media thickness (IMT). We will also repeatedly assess plasma markers of inflammation, oxidative damage, and endothelial function in 720 subjects. MESA Air adds state-of-the-art air pollution exposure assessment information to the MESA cohort study, and introduces new subjects and outcome measures to achieve our aims. The study will assess long-term individual-level exposure to ambient air pollutants for each subject using community-scale monitoring, outdoor spatial variation, subject proximity to pollution sources, pollutants' infiltration efficiency, and personal time-activity information. The exposure models will be validated using detailed monitoring in a subset of subjects. The MESA Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000209 MESA Cohort.  phs000420 MESA SHARe phs000283 MESA CARe phs000403 MESA ESP Heart-GO     Study Weblinks:   MESA MESA Air    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Family   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000209.v13.p3 on 2021-03-25 and may not include exact formatting or images."
-phs000284.v2.p1,c1,NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe),2023-09-28,"Name: CFS_DS-HLBS-IRB-NPU_, short name: CFS.","The Cleveland Family Study is the largest family-based study of sleep apnea world-wide, consisting of 2284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study was begun in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. NIH renewals provided expansion of the original cohort (including increased minority recruitment) and longitudinal follow-up, with the last exam occurring in February 2006. Index probands (n=275) were recruited from 3 area hospital sleep labs if they had a confirmed diagnosis of sleep apnea and at least 2 first-degree relatives available to be studied. In the first 5 years of the study, neighborhood control probands (n=87) with at least 2 living relatives available for study were selected at random from a list provided by the index family and also studied. All available first degree relatives and spouses of the case and control probands also were recruited. Second-degree relatives, including half-sibs, aunts, uncles and grandparents, were also included if they lived near the first degree relatives (cases or controls), or if the family had been found to have two or more relatives with sleep apnea. Blood was sampled and DNA isolated for participants seen in the last two exam cycles (n=1447). The sample, which is enriched with individuals with sleep apnea, also contains a high prevalence of individuals with sleep apnea-related traits, including: obesity, impaired glucose tolerance, and HTN. Phenotyping data have been collected over 4 exam cycles, each occurring ~every 4 years. The last three exams targeted all subjects who had been studied at earlier exams, as well as new minority families and family members of previously studied probands who had been unavailable at prior exams. Data from one, two, three and four visits are available for 412, 630, 329 and 67, participants, respectively. In the first 3 exams, participants underwent overnight in-home sleep studies, allowing determination of the number and duration of hypopneas and apneas, sleep period, heart rate, and oxygen saturation levels; anthropometry (weight, height, and waist, hip, and neck circumferences); resting blood pressure; spirometry; standardized questionnaire evaluation of symptoms, medications, sleep patterns, quality of life, daytime sleepiness measures and health history; venipuncture and measurement of total and HDL cholesterol. The 4th exam (2001-2006) was designed to collect more detailed measurements of sleep, metabolic and CVD phenotypes and included measurement of state-of-the-art polysomnography, with both collection of blood and measurement of blood pressure before and after sleep, and anthropometry, upper airway assessments, spirometry, exhaled nitric oxide, and ECG performed the morning after the sleep study. Data have been collected by trained research assistants or GCRC nurses following written Manuals of Procedures who were certified following standard approaches for each study procedure. Ongoing data quality, with assessment of within or between individual drift, has been monitored on an ongoing basis, using statistical techniques as well as regular re-certification procedures. Between and within scorer reliabilities for key sleep apnea indices have been excellent, with intra-class correlation coefficients (ICCs) exceeding 0.92 for the apnea-hypopnea index (AHI). Sleep staging, assessed with epoch specific comparisons, also demonstrate excellent reliability for stage identification (kappas>0.82). There has been no evidence of significant time trends-between or within scorers- for the AHI variables. We also have evaluated the night-to-night variability of the AHI and other sleep variables in 91 subjects, with each measurement made 1-3 months apart. There is high night to night consistency for the AHI (ICC: 0.80), the arousal index (0.76), and the % sleep time in slow-wave sleep (0.73). We have demonstrated the comparability of the apnea estimates (AHI) determined from limited channel studies obtained at in-home settings with in full in-laboratory polysomnography. In addition to our published validation study, we more recently compared the AHI in 169 Cleveland Family Study participants undergoing both assessments (in-home and in-laboratory) within one week apart. These showed excellent levels of agreement (ICC=0.83), demonstrating the feasibility of examining data from either in-home or in-laboratory studies for apnea phenotyping. Data collected in the GCRC were obtained, when possible, with comparable, if not identical techniques, as were the same measures collected at prior exams performed in the participants' homes. To address the comparability of data collected over different exams, we calculated the crude age-adjusted correlations ~3 year within individual correlations between measures made in the most recent GCRC exam with measures made in a prior exam and demonstrated excellent levels of agreement for BMI (r=.91); waist circumference (0.91); FVC (0.88); and FEV1 (0.86). As expected due to higher biological and measurement variability, 149 somewhat lower 3-year correlations were demonstrated for SBP (0.56); Diastolic BP (0.48); AHI (0.62); and nocturnal oxygen desaturation (0.60). NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Cooperative Study of Sickle Cell Disease (CSSCD), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data will be created that includes records for approximately 50,000 study participants with approximately 50,000 SNPs from more than 1,200 selected candidate genes. In addition, a genome wide association study using a 1,000K SNP Chip will be conducted on approximately 9,500 African American participants drawn from the 50,000 participants in the nine cohorts. Some relevant CARe publications CARe Study: PMID 20400780 CVD Chip Design: PMID 18974833    Study Weblinks:   Cleveland Family Study    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000284.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000285.v3.p2,c1,Coronary Artery Risk Development in Young Adults (CARDIA) Study - Cohort,2023-09-28,"Name: CARDIA_HMB-IRB_, short name: CARDIA.","CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women aged 18-30 years were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), and 2010-2011 (Year 25); the proportions of the surviving cohort that have returned for the seven follow-up examinations were 90%, 86%, 81%, 79%, 74%, 72%, and 72%, respectively. In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination has differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements such as weight and skinfold fat as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20. The CARDIA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" box located on the right hand side of this top-level study page phs000285 CARDIA Cohort.  phs000236 PAGE_CALiCo_CARDIA phs000309 GENEVA_CARDIA phs000399 GO-ESP HeartGO_CARDIA phs000613 CARDIA_CARe     Study Weblinks:   CARDIA    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000285.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000285.v3.p2,c2,Coronary Artery Risk Development in Young Adults (CARDIA) Study - Cohort,2023-09-28,"Name: CARDIA_HMB-IRB-NPU_, short name: CARDIA.","CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women aged 18-30 years were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), and 2010-2011 (Year 25); the proportions of the surviving cohort that have returned for the seven follow-up examinations were 90%, 86%, 81%, 79%, 74%, 72%, and 72%, respectively. In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination has differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements such as weight and skinfold fat as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20. The CARDIA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" box located on the right hand side of this top-level study page phs000285 CARDIA Cohort.  phs000236 PAGE_CALiCo_CARDIA phs000309 GENEVA_CARDIA phs000399 GO-ESP HeartGO_CARDIA phs000613 CARDIA_CARe     Study Weblinks:   CARDIA    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000285.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000286.v6.p2,c1,Jackson Heart Study (JHS) Cohort,2023-09-28,"Name: JHS_HMB-IRB-NPU_, short name: JHS.","The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31% and secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents aged 35-84 during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (Exam 1 - 2000-2004; Exam 2 - 2005-2008; Exam 3 - 2009-2013) include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurement, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. A note regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP: The coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this of this top-level study page phs000286 JHS Cohort.  phs000402 HeartGO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARe phs001098 T2D GENES Exome Seq phs001069 MIGen JHS phs001356 Exome Chip     Study Weblinks:   Jackson Heart Study JHS Publications    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000286.v6.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000286.v6.p2,c2,Jackson Heart Study (JHS) Cohort,2023-09-28,"Name: JHS_DS-FDO-IRB-NPU_, short name: JHS.","The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31% and secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents aged 35-84 during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (Exam 1 - 2000-2004; Exam 2 - 2005-2008; Exam 3 - 2009-2013) include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurement, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. A note regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP: The coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this of this top-level study page phs000286 JHS Cohort.  phs000402 HeartGO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARe phs001098 T2D GENES Exome Seq phs001069 MIGen JHS phs001356 Exome Chip     Study Weblinks:   Jackson Heart Study JHS Publications    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000286.v6.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000286.v6.p2,c3,Jackson Heart Study (JHS) Cohort,2023-09-28,"Name: JHS_HMB-IRB_, short name: JHS.","The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31% and secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents aged 35-84 during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (Exam 1 - 2000-2004; Exam 2 - 2005-2008; Exam 3 - 2009-2013) include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurement, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. A note regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP: The coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this of this top-level study page phs000286 JHS Cohort.  phs000402 HeartGO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARe phs001098 T2D GENES Exome Seq phs001069 MIGen JHS phs001356 Exome Chip     Study Weblinks:   Jackson Heart Study JHS Publications    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000286.v6.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000286.v6.p2,c4,Jackson Heart Study (JHS) Cohort,2023-09-28,"Name: JHS_DS-FDO-IRB_, short name: JHS.","The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31% and secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents aged 35-84 during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (Exam 1 - 2000-2004; Exam 2 - 2005-2008; Exam 3 - 2009-2013) include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurement, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. A note regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP: The coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this of this top-level study page phs000286 JHS Cohort.  phs000402 HeartGO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARe phs001098 T2D GENES Exome Seq phs001069 MIGen JHS phs001356 Exome Chip     Study Weblinks:   Jackson Heart Study JHS Publications    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000286.v6.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000287.v7.p1,c1,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,2023-09-28,"Name: CHS_HMB-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000287.v7.p1,c2,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,2023-09-28,"Name: CHS_HMB-NPU-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000287.v7.p1,c3,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,2023-09-28,"Name: CHS_DS-CVD-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000287.v7.p1,c4,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,2023-09-28,"Name: CHS_DS-CVD-NPU-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000289.v2.p1,c1,National Human Genome Research Institute (NHGRI) GENEVA Genome-Wide Association Study of Venous Thrombosis (GWAS of VTE),2023-09-28,"Name: Mayo_VTE_GRU_, short name: Mayo_VTE.","Overview: Our overall long-term goal is to determine risk factors for the complex (multifactorial) disease, venous thromboembolism (VTE), that will allow physicians to stratify individual patient risk and target VTE prophylaxis to those who would benefit most. In this genome-wide association case-control study (1300 cases and 1300 controls) we hope to identify susceptibility variants for VTE. Mutations within genes encoding for important components of the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways are risk factors for VTE. We hypothesize that other genes within these four pathways or within other pathways also are VTE disease-susceptibility genes. Therefore, we performed a genome wide association (GWA) screen and analysis using the Illumina 660W platform to identify SNPs within 1,300 clinic-based, non-cancer VTE cases primarily from Minnesota and the upper Midwest USA, and 1300 clinic-based, unrelated controls frequency-matched on patient age, gender, myocardial infarction/stroke status and state of residence. This is a subset of a slightly larger candidate gene study using 1500 case-control pairs to identify haplotype-tagging SNPs (ht-SNPs) in a large set of candidate genes (n~750) within the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways. Study Populations. Cases. VTE cases were consecutive Mayo Clinic outpatients with objectively-diagnosed deep vein thrombosis (DVT) and/or pulmonary embolism (PE) residing in the upper Midwest and referred by Mayo Clinic physician to the Mayo Clinic Special Coagulation Laboratory for clinical diagnostic testing to evaluate for an acquired or inherited thrombophilia, or to the Mayo Clinic Thrombophilia Center. Any person contacted to be a control but discovered to have had a VTE was evaluated for inclusion as a case. Cases were primarily residents from Minnesota, Wisconsin, Iowa, Michigan, Illinois, North or South Dakota, Nebraska, Kansas, Missouri and Indiana. A DVT or PE was categorized as objectively diagnosed when (a) confirmed by venography or pulmonary angiography, or pathology examination of thrombus removed at surgery, or (b) if at least one non-invasive test (compression duplex ultrasonography, lung scan, computed tomography scan, magnetic resonance imaging) was positive. A VTE was defined as:  Proximal leg deep vein thrombosis (DVT), which includes the common iliac, internal iliac, external iliac, common femoral, superficial [now termed ""femoral""] femoral, deep femoral [sometimes referred to as ""profunda"" femoral] and/or popliteal veins. (Note: greater and lesser saphenous veins, or other superficial or perforator veins, were not included as proximal or distal leg DVT). Distal leg DVT (or ""isolated calf DVT""), which includes the anterior tibial, posterior tibial and/or peroneal veins. (Note: gastrocnemius, soleal and/or sural [e.g., ""deep muscular veins"" of the calf] vein thrombosis was not included as distal leg DVT). Arm DVT, which includes the axillary, subclavian and/or innominate (brachiocephalic) veins. (Note: jugular [internal or external], cephalic and brachial vein thrombosis was not included in ""arm DVT""). Hepatic, portal, splenic, superior or inferior mesenteric, and/or renal vein thrombosis. (Note: ovarian, testicular, peri-prostatic and/or pelvic vein thrombosis was not included). Cerebral vein thrombosis (includes cerebral or dural sinus or vein, saggital sinus or vein, and/or transverse sinus or vein thrombosis). Inferior vena cava (IVC) thrombosis Superior vena cava (SVC) thrombosis Pulmonary embolism   Patients with VTE related to active cancer, antiphospholipid syndrome, inflammatory bowel disease, vasculitis, a rheumatoid or other autoimmune disorder, a vascular anomaly (e.g., Klippel-Trénaunay syndrome, etc.), heparin-induced thrombocytopenia, or a mechanical cause for DVT (e.g., arm DVT or SVC thrombosis related to a central venous catheter or transvenous pacemaker, portal and/or splenic vein thrombosis related to liver cirrhosis, IVC thrombosis related to retroperitoneal fibrosis, etc.), with hemodialysis arteriovenous fistula thrombosis, or with prior liver or bone marrow transplantation were excluded.  Controls. A Mayo Clinic outpatient control group was prospectively recruited for this study. Controls were frequency-matched on the age group (18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+ years), sex, myocardial infarction/stroke status, and state of residence distribution of the cases. We selected clinic-based controls using a controls' database of persons undergoing general medical examinations in the Mayo Clinic Departments of General Internal Medicine or Primary Care Internal Medicine. Additionally persons undergoing evaluation at the Mayo Clinic Sports Medicine Center, and the Department of Family Medicine were screened for inclusion as controls. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to venous thrombosis through large-scale genome-wide association studies of 1,300 clinic-based, VTE cases and 1300 clinic-based, unrelated controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000289.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000422.v1.p1,c1,NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Asthma): Genetic variants affecting susceptibility and severity,2023-09-28,"Name: Asthma_GRU_, short name: Asthma.","The NHLBI ""Grand Opportunity"" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the ""exome"") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: 19892860). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (phs000355, Illumina platform).   Study Design:       Case Set    Study Type:  Case Set   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000422.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000571.v6.p2,c1,Congenital Heart Disease Genetic Network Study,2023-09-28,"Name: CHD-GENES_HMB, short name: CHD-GENES_HMB.","This substudy phs000571 PCGC contains whole exome sequences, targeted sequences, and SNP array data. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194.  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Study Weblinks:Bench to Bassinet Program Study Design:     Prospective Longitudinal Cohort Study Type:Parent-Offspring TriosCohortdbGaP estimated ancestry usingGRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-10-11 and may not include exact formatting or images."
-phs000703.v1.p1,c1,CATHeterization GENetics (CATHGEN),2023-09-28,"Name: CATHGEN_DS-CVD-IRB_, short name: CATHGEN.","The CATHGEN biorepository consists of biological samples collected on 9334 sequential consenting individuals undergoing cardiac catheterization at Duke University Medical Center between 2001 and 2010 inclusive. The Institutional Review Board informed consent allowed for 50 mL of blood to be collected from fasting patients through the femoral arterial sheath during the catheterization procedure. Three 7.5 mL EDTA tubes for DNA extraction are stored at -80°C. The Duke Database for Cardiovascular Disease (DDCD) provides the bulk of the clinical data used for analysis. Follow-up includes mortality information gleaned from the National Death Index and Social Security Death Index plus follow-up phone calls and written questionnaires regarding MI, stroke, re-hospitalization, coronary re-vascularization procedures, smoking, exercise, and medication use.   Study Weblinks:   CATHGEN    Study Design:       Cross-Sectional    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000703.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000784.v3.p1,c1,Genetic Epidemiology Network of Salt Sensitivity (GenSalt),2023-09-28,"Name: GenSalt_DS-HCR-IRB_, short name: GenSal.",The GenSalt study is aimed at identifying novel genes which interact with the effect of dietary sodium and potassium intake or cold pressor on blood pressure.   Study Design:       Interventional    Study Type:  Family Interventional     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000784.v3.p1 on 2021-03-25 and may not include exact formatting or images.
-phs000810.v1.p1,c1,Hispanic Community Health Study /Study of Latinos (HCHS/SOL),2023-09-28,"Name: HCHS-SOL_HMB-NPU_, short name: HCHS-SOL.","The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" box located on the right hand side of this top-level study page phs000810 HCHS SOL Cohort.  phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)     Study Weblinks:   Hispanic Community Health Study / Study of Latinos    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000810.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000810.v1.p1,c2,Hispanic Community Health Study /Study of Latinos (HCHS/SOL),2023-09-28,"Name: HCHS-SOL_HMB_, short name: HCHS-SOL.","The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" box located on the right hand side of this top-level study page phs000810 HCHS SOL Cohort.  phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)     Study Weblinks:   Hispanic Community Health Study / Study of Latinos    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000810.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000820.v1.p1,c1,The Cleveland Clinic Foundation's Lone Atrial Fibrillation GWAS Study,2023-09-28,"Name: CCAF_GRU_, short name: CCAF.",Blood samples were taken from patients who have lone atrial fibrillation. DNA samples were processed with Illumina Hap550 and Hap 610 chips.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000820.v1.p1 on 2021-03-25 and may not include exact formatting or images.
-phs000914.v1.p1,c1,Genome-Wide Association Study of Adiposity in Samoans,2023-09-28,"Name: SAS_GRU-IRB-PUB-COL-NPU-GSO_, short name: SAS.","The research goal of this study is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Population     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000914.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000920.v4.p2,c2,NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II),2023-09-28,"Name: GALAII_DS-LD-IRB-COL, short name: GALAII.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180.   Study Weblinks:   Study Populations and Research Staff    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000920.v4.p2 on 2021-03-25 and may not include exact formatting or images."
-phs000921.v4.p1,c2,"NHLBI TOPMed: Study of African Americans, Asthma, Genes and Environment (SAGE)",2023-09-28,"Name: SAGE_DS-LD-IRB-COL, short name: SAGE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a parallel case-control pharmacogenetic study of bronchodilator drug response among African American children with and without asthma. Each participant had spirometry measured using the KoKo PFT System. Asthmatic participants were administered with 4 puffs of HFA Albuterol. Healthy participants were given a baseline spirometry test. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants were 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications.   Study Weblinks:   Study Populations and Research Staff    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000921.v4.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000946.v5.p1,c1,NHLBI TOPMed: Boston Early-Onset COPD Study (EOCOPD),2023-09-28,"Name: NHLBI TOPMed: Boston Early-Onset COPD Study (EOCOPD), short name: EOCOPD_DS-CS-RD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project collected a set of extended pedigrees ascertained through subjects with severe, early-onset COPD. This study has enrolled subjects with severe COPD (forced expiratory volume in one second (FEV1) < 40% predicted) at an early age (< 53 years) without alpha-1 antitrypsin deficiency (a known Mendelian risk factor for COPD). Extended pedigrees are enrolled, primarily in New England, although some more geographically distant subjects have been included. This study has been used for epidemiological studies, familial aggregation analysis, linkage analysis, and candidate gene association analysis. Approximately 80 of the severe, early-onset COPD probands will undergo whole genome sequencing in this project with sequencing data available through dbGaP. Study Weblinks: Boston COPD Study Design:     Family/Twin/Trios Study Type:Pedigree Whole Genome Sequencing dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000951.v4.p4,c1,NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene),2023-09-28,"Name: COPDGene_HMB, short name: COPDGene.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are:  Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed.  Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179.   Study Weblinks:   COPDGene phs000179    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000951.v4.p4 on 2021-03-25 and may not include exact formatting or images."
-phs000951.v4.p4,c2,NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene),2023-09-28,"Name: COPDGene_DS-CS-RD, short name: COPDGene.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are:  Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed.  Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179.   Study Weblinks:   COPDGene phs000179    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000951.v4.p4 on 2021-03-25 and may not include exact formatting or images."
-phs000954.v4.p2,c1,NHLBI TOPMed: The Cleveland Family Study (CFS),2023-09-28,"Name: NHLBI TOPMed: The Cleveland Family Study (CFS), short name: CFS_DS-HLBS-IRB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Cleveland Family Study (CFS) is one cohort involved in the WGS project. The CFS was designed to provide fundamental epidemiological data on genetic and non-genetic risk factors for sleep disordered breathing (SDB). In brief, the CFS is a family-based study that enrolled a total of 2284 individuals from 361 families between 1990 and 2006. The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first degree relatives, spouses and available second degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first degree relatives. Each exam, occurring at approximately 4 year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in the participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. The GCRC exam (n=735 selected individuals) included more comprehensive phenotype data on a focused subsample of the larger cohort, to permit linking SDB phenotypes with cardio-metabolic phenotypes, with an interest in identifying genetic loci that are associated with these related phenotypes. In this last round of data collection, a subset of 735 individuals was selected based on expected genetic informativity by choosing pedigrees where siblings had extremes of the apnea hypopnea index (AHI). Participants underwent detailed phenotyping including laboratory polysomnography (PSG), ECG, spirometry, nasal and oral acoustic reflectometry, vigilance testing, and blood and urine collection before and after sleep and after an oral glucose tolerance test. A wide range of biochemical measures of inflammation and metabolism were assayed by a Core Laboratory at the University of Vermont. 994 individuals were sequenced as part of TOPMed Phase 1, including 507 African-Americans and 487 European-Americans. Among the sequenced individuals, 156 were probands with diagnosed sleep apnea, an additional 706 were members of families with probands, and 132 were from neighborhood control families.  298 individuals were sequenced as part of TOPMed Phase 3.5, including 169 African-Americans and 129 European-Americans. Among the newly sequenced individuals, 33 were probands with diagnosed sleep apnea, an additional 214 were members of families with probands, and 51 were from neighborhood control families. Please note: Phenotype and pedigree data are available through ""NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)"", phs000284.  Study Weblinks: Cleveland Family Study (CFS) Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000956.v4.p1,c2,NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish,2023-09-28,"Name: Amish_HMB-IRB-MDS, short name: Amish.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Amish Complex Disease Research Program includes a set of large community-based studies focused largely on cardiometabolic health carried out in the Old Order Amish (OOA) community of Lancaster, Pennsylvania (http://medschool.umaryland.edu/endocrinology/amish/research-program.asp). The OOA population of Lancaster County, PA immigrated to the Colonies from Western Europe in the early 1700's. There are now over 30,000 OOA individuals in the Lancaster area, nearly all of whom can trace their ancestry back 12-14 generations to approximately 700 founders. Investigators at the University of Maryland School of Medicine have been studying the genetic determinants of cardiometabolic health in this population since 1993. To date, over 7,000 Amish adults have participated in one or more of our studies. Due to their ancestral history, the OOA may be enriched for rare variants that arose in the population from a single founder (or small number of founders) and propagated through genetic drift. Many of these variants have large effect sizes and identifying them can lead to new biological insights about health and disease. The parent study for this WGS project provides one (of multiple) examples. In our parent study, we identified through a genome-wide association analysis a haplotype that was highly enriched in the OOA that is associated with very high LDL-cholesterol levels. At the present time, the identity of the causative SNP - and even the implicated gene - is not known because the associated haplotype contains numerous genes, none of which are obvious lipid candidate genes. A major goal of the WGS that will be obtained through the NHLBI TOPMed Consortium will be to identify functional variants that underlie some of the large effect associations observed in this unique population.   Study Weblinks:   University of Maryland School of Medicine - Amish Studies    Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000956.v4.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000964.v5.p1,c1,NHLBI TOPMed: The Jackson Heart Study (JHS),2023-09-28,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_HMB-IRB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000964.v5.p1,c2,NHLBI TOPMed: The Jackson Heart Study (JHS),2023-09-28,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_DS-FDO-IRB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000964.v5.p1,c3,NHLBI TOPMed: The Jackson Heart Study (JHS),2023-09-28,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_HMB-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000964.v5.p1,c4,NHLBI TOPMed: The Jackson Heart Study (JHS),2023-09-28,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_DS-FDO-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000972.v4.p1,c1,NHLBI TOPMed: Genome-Wide Association Study of Adiposity in Samoans,2023-09-28,"Name: SAS_GRU-IRB-PUB-COL-NPU-GSO, short name: SAS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The individuals sequenced here represent a small subset of the parent study (described below) and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing. The research goal of the parent study (dbGaP ID phs000914) is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Population     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000972.v4.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000974.v5.p3,c1,NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS),2023-09-28,"Name: NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS), short name: FHS_HMB-IRB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"" and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 subjects and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007. Study Weblinks:Framingham Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:CohortdbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000974 on 2021-03-17 and may not include exact formatting or images."
-phs000974.v5.p3,c2,NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS),2023-09-28,"Name: NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS), short name: FHS_HMB-IRB-NPU-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"" and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 subjects and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007. Study Weblinks:Framingham Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:CohortdbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000974 on 2021-03-17 and may not include exact formatting or images."
-phs000988.v4.p1,c1,NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica,2023-09-28,"Name: CRA_DS-ASTHMA-IRB-MDS-RD, short name: CRA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This administrative supplement to the project, ""The Genetic Epidemiology of Asthma in Costa Rica"" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.   Study Design:       Family/Twin/Trios    Study Type:  Parent-Offspring Trios     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000988.v4.p1 on 2021-03-25 and may not include exact formatting or images."
-phs000993.v5.p2,c1,NHLBI TOPMed: Heart and Vascular Health Study (HVH),2023-09-28,"Name: NHLBI TOPMed: Heart and Vascular Health Study (HVH), short name: HVH_HMB-IRB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000993.v5.p2,c2,NHLBI TOPMed: Heart and Vascular Health Study (HVH)),2023-09-28,"Name: NHLBI TOPMed: Heart and Vascular Health Study (HVH)), short name: HVH_DS-CVD-IRB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs000997.v5.p2,c1,NHLBI TOPMed - NHGRI CCDG: The Vanderbilt AF Ablation Registry,2023-09-28,"Name: NHLBI TOPMed - NHGRI CCDG: The Vanderbilt AF Ablation Registry, short name: VAFAR_HMB-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Vanderbilt Atrial Fibrillation Ablation Registry (VAFAR) was founded in 2011. Patients with AF referred for AF ablation are prospectively enrolled. A detailed clinical history is recorded, along with imaging data (cardiac MRI or CT). Blood samples are obtained for DNA extraction at the time of ablation. Details of the ablation procedure are recorded. Patients are longitudinally followed to monitor for AF recurrence. VAFAR contributed 171 samples submitted to dbGaP for WGS: 115 were from male subjects, of which 113 were white/non-Hispanic and 2 were Hispanic; 56 were from females, of which all 56 were white/non-Hispanic. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001001.v1.p1,c1,Massachusetts General Hospital (MGH) Atrial Fibrillation Study,2023-09-28,"Name: MGH_AF_HMB-IRB_, short name: MGH_AF.","The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study.  phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing     Study Design:       Case Set    Study Type:  Case Set   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001001.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001001.v1.p1,c2,Massachusetts General Hospital (MGH) Atrial Fibrillation Study,2023-09-28,"Name: MGH_AF_DS-AF-IRB-RD_, short name: MGH_AF.","The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study.  phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing     Study Design:       Case Set    Study Type:  Case Set   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001001.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001012.v1.p1,c1,The Diabetes Heart Study (DHS),2023-09-28,"Name: DHS_DS-DRC-IRB_, short name: DHS.","The Diabetes Heart Study is a family based study enriched for type 2 diabetes (T2D). The cohort included 1220 self-reported European Americans from 475 families (Bowden et al 2010 Review of Diabetic Studies 7:188-201: PMID: 21409311; Bowden et al 2008 Annals of Human Genetics 72:598-601 PMID: 18460048) and included siblings concordant for T2D; where possible unaffected siblings were also recruited. The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery and abdominal aorta all determined from non-contrast computed tomography scans.    Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001012.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001013.v3.p2,c1,Heart and Vascular Health Study (HVH),2023-09-28,"Name: HVH_HMB-IRB-MDS_, short name: HVH.","Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001013.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001013.v3.p2,c2,Heart and Vascular Health Study (HVH),2023-09-28,"Name: HVH_DS-CVD-IRB-MDS_, short name: HVH.","Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001013.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001024.v4.p1,c1,NHLBI TOPMed: Partners HealthCare Biobank,2023-09-28,"Name: PARTNERS_HMB, short name: PARTNERS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Atrial Fibrillation Genetics Consortium (AFGen) was organized to identify common and rare genetic variation associated with atrial fibrillation risk. In the current study, we have performed whole genome sequencing in cases with early-onset atrial fibrillation. Samples in this study were enrolled as a part of the Partners HealthCare Biobank. Cases with early-onset atrial fibrillation were identified from the Biobank (defined as atrial fibrillation onset prior to 61 years and in the absence of structural heart disease).    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs001024 on 2021-03-17 and may not include exact formatting or images."
-phs001032.v6.p2,c1,NHLBI TOPMed: Heart and Vascular Health Study (HVH),2023-09-28,"Name: NHLBI TOPMed: Heart and Vascular Health Study (HVH), short name: VU_AF_GRU-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Vanderbilt Atrial Fibrillation (AF) Registry was founded in 2001. Patients with AF and family members are prospectively enrolled. At enrollment a detailed past medical history is obtained along with an AF symptom severity assessment. Blood samples are obtained for DNA extraction. Patients are followed longitudinally along with serial collection of AF symptom severity assessments. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001040.v4.p1,c1,NHLBI TOPMed: Novel Risk Factors for the Development of Atrial Fibrillation in Women,2023-09-28,"Name: WGHS_HMB, short name: WGHS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Women's Genome Health Study (WGHS) is a prospective cohort comprised of over 25,000 initially healthy female health professionals enrolled in the Women's Health Study, which began in 1992-1994. All participants in WGHS provided baseline blood samples and extensive survey data. Women who reported atrial fibrillation during the course of the study were asked to report diagnoses of AF at baseline, 48 months, and then annually thereafter. Participants enrolled in the continued observational follow-up who reported an incident AF event on at least one yearly questionnaire were sent an additional questionnaire to confirm the episode and to collect additional information. They were also asked for permission to review their medical records, particularly available ECGs, rhythm strips, 24-hour ECGs, and information on cardiac structure and function. For all deceased participants who reported AF during the trial and extended follow-up period, family members were contacted to obtain consent and additional relevant information. An end-point committee of physicians reviewed medical records for reported events according to predefined criteria. An incident AF event was confirmed if there was ECG evidence of AF or if a medical report clearly indicated a personal history of AF. The earliest date in the medical records when documentation was believed to have occurred was set as the date of onset of AF.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001040.v4.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001062.v4.p2,c1,NHLBI TOPMed - NHGRI CCDG: Massachusetts General Hospital (MGH) Atrial Fibrillation Study,2023-09-28,"Name: MGH_AF_HMB-IRB, short name: MGH_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. For the TOPMed WGS project only early-onset atrial fibrillation cases were sequenced. Early-onset atrial fibrillation was defined as an age of onset prior to 66 years of age. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs001001.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001062.v4.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001062.v4.p2,c2,NHLBI TOPMed - NHGRI CCDG: Massachusetts General Hospital (MGH) Atrial Fibrillation Study,2023-09-28,"Name: MGH_AF_DS-AF-IRB-RD, short name: MGH_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. For the TOPMed WGS project only early-onset atrial fibrillation cases were sequenced. Early-onset atrial fibrillation was defined as an age of onset prior to 66 years of age. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs001001.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs001062 on 2021-03-17 and may not include exact formatting or images."
-phs001074.v1.p1,c2,GeneSTAR (Genetic Study of Atherosclerosis Risk) NextGen Consortium: Functional Genomics of Platelet Aggregation Using iPS and Derived Megakaryocytes,2023-09-28,"Name: GeneSTAR_DS-CVD-IRB-NPU-RD_, short name: GeneSTAR.","The causal mechanisms of common diseases and their therapies have been only marginally illuminated by genetic variants identified in genome wide association studies (GWAS) utilizing single nucleotide polymorphism (SNPs). Platelet activation pathways reflecting hemostasis and thrombosis are the underlying substrate for many cardiovascular diseases and related acute events. To overcome GWAS limitations, genomic studies are needed that integrate molecular surrogates for platelet-related phenotypes assayed in cell-based models derived from individuals of known genotypes and phenotypes. In our GWAS study of native platelet aggregation phenotypes and aggregation in response to low dose aspirin in 2200 subjects (GeneSTAR, Genetic Study of Aspirin Responsiveness), important genome wide ""signals"" (p<5x10-8) associated with native platelet aggregation and important ""signals"" associated with platelet responsiveness to aspirin were identified and replicated. Although we are currently performing functional genomics studies to elucidate our most promising findings in known genes (PEAR1, MET, PIKC3G), most ""signals"" occurred in intergenic regions or in introns. Mechanistic interpretation is limited by uncertainty as to which gene(s) are up- or down-regulated in the presence of most SNP modifications. In this 3 phase proposal, we will (1) create pluripotent stem cells (iPS) from peripheral blood mononuclear cells, and then differentiate these stem cells into megakaryocytes (2) develop an efficient strategy to produce iPS and megakaryocytes using a novel pooling method, and (3) produce iPS and megakaryocytes from 250 subjects in GeneSTAR (European Americans and African Americans), selected based on specific hypotheses derived from GWAS signals in native and post aspirin platelet function; characterize genetic mRNA transcripts using a comprehensive Affymetrix array; measure protein expression for transcripts of interest using mass spectrometry; examine mRNA and protein expression patterns for each GWAS signal to determine the functional pathway(s) involved in native platelet phenotypes; and examine the functional genomics of variations in responsiveness to aspirin using our prior genotyped and phenotyped population. Precise information about the exact functional processes in megakaryocytes and platelets may lead to innovative and tailored approaches to risk assessment and novel therapeutic targets to prevent first and recurrent cardiovascular and related thrombotic events.   Study Weblinks:   GeneSTAR Research Center, Genetic Studies of Atherosclerosis Risk    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Cohort Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001074.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001143.v4.p1,c1,NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados,2023-09-28,"Name: NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados, short name: BAGS_GRU-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Asthma is a complex disease where the interplay between genetic factors and environmental exposures influences susceptibility and disease prognosis. Asthmatics of African descent tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry. The baseline prevalence of asthma in Barbados is high (~20%), and from admixture analyses, we have determined that the proportion of African ancestry among Barbadian founders is similar to U.S. African Americans, rendering this a unique population to disentangle the genetic basis for asthma disparities among African ancestry populations in general. We therefore performed whole genome sequencing on 1,100 individuals from the Barbados Genetics of Asthma Study (BAGS), in order to generate additional discovery of rare and structural variants that may control risk to asthma. Study Design:     Family/Twin/Trios Study Type:Family dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001180.v2.p1,c2,Genes-Environments and Admixture in Latino Asthmatics (GALA II) Study,2023-09-28,"Name: GALAII_DS-LD-IRB-COL_, short name: GALAII.","A case-control pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. The GALAII Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" box located on the right hand side of this top-level study page phs001180 GALAII Study.  phs001274phs001274 GALAII GWAS     Study Weblinks:   Asthma Collaboratory    Study Design:       Case-Control    Study Type:  Case-Control   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001180.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001189.v4.p1,c1,NHLBI TOPMed: Cleveland Clinic Atrial Fibrillation (CCAF) Study,2023-09-28,"Name: NHLBI TOPMed: Cleveland Clinic Atrial Fibrillation (CCAF) Study, short name: CCAF_AF_GRU-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Cleveland Clinic Atrial Fibrillation Study consists of clinical and genetic data of patients with atrial fibrillation and control cohorts from the Cleveland Clinic CV/Arrhythmia Biobank, including the Cleveland Clinic Lone Atrial Fibrillation GeneBank. The Cleveland Clinic Lone AF GeneBank Study has enrolled patients with lone AF, defined as AF in the absence of significant structural heart disease. The CV/Arrhythmia Biobank has also enrolled participants with non-lone atrial fibrillation. All patients provided written informed consent. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001194.v2.p2,c1,"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study",2023-09-28,"Name: PCGC_HMB_, short name: PCGC.","Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. The PCGC Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001194 PCGC Cohort.  phs000571 The Pediatric Cardiac Genetics Consortium (PCGC)   The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.   Study Weblinks:   From Bench to Bassinet: CHD Genes    Study Design:       Prospective Longitudinal Cohort    Study Type:  Parent-Offspring Trios Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001194.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001194.v2.p2,c2,"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study",2023-09-28,"Name: PCGC_DS-CHD_, short name: PCGC.","Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. The PCGC Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001194 PCGC Cohort.  phs000571 The Pediatric Cardiac Genetics Consortium (PCGC)   The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.   Study Weblinks:   From Bench to Bassinet: CHD Genes    Study Design:       Prospective Longitudinal Cohort    Study Type:  Parent-Offspring Trios Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001194.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001207.v2.p1,c1,NHLBI TOPMed: African American Sarcoidosis Genetics Resource,2023-09-28,"Name: Sarcoidosis_DS-SAR-IRB, short name: Sarcoidosis.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study aims to comprehensively interrogate the genomes of African American sarcoidosis families. Sarcoidosis is characterized by a hyperimmune response resulting in granuloma formation in multiple organs. It affects African Americans (AAs) more frequently and more severely than whites. While previous linkage, admixture, candidate gene and genome-wide association (GWA) studies show statistically compelling effects, causal variants are still unknown and much of sarcoidosis heritability is yet to be explained. This ""missing"" heritability likely includes effects of both common (minor allele frequency (MAF)>5%) and rare variants (MAF<5%), since, in AAs, the former are inadequately represented and the latter are completely unexplored by commercial genotyping arrays. These facts, coupled with the availability of next-generation sequencing compel us to perform an exhaustive search for genetic variants that form the basis of sarcoidosis. The data generated are certain to identify candidate causal variants, provide fundamental insight for functional studies and lead to important new hypotheses of inflammation resulting in new treatments in not only sarcoidosis but other inflammatory diseases as well.   Study Design:       Family/Twin/Trios    Study Type:  Family Affected Sib Pairs     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001207.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001211.v3.p2,c1,NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC),2023-09-28,"Name: ARIC_HMB-IRB, short name: ARIC.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession.  Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001211.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001211.v3.p2,c2,NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC),2023-09-28,"Name: ARIC_DS-CVD-IRB, short name: ARIC.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession.  Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001211.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001215.v3.p2,c1,NHLBI TOPMed: San Antonio Family Heart Study (SAFHS),2023-09-28,"Name: SAFHS_DS-DHD-IRB-PUB-MDS-RD, short name: SAFHS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The San Antonio Family Heart Study (SAFHS) is a complex pedigree-based mixed longitudinal study designed to identify low frequency or rare variants influencing susceptibility to cardiovascular disease, using whole genome sequence (WGS) information from 2,590 individuals in large Mexican American pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for CVD, as well as to find novel low frequency or rare variants influencing susceptibility to CVD. WGS of the SAFHS cohort has been obtained through three efforts. Approximately 540 WGS were performed commercially at 50X by Complete Genomics, Inc (CGI) as part of the large T2D-GENES Project. The phenotype and genotype data for this group is available at dbGaP under accession number phs000462. An additional ~900 WGS at 30X were obtained through Illumina as part of the R01HL113322 ""Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk"" project. Finally, ~1,150 WGS at 30X WGS were obtained through Illumina funded by a supplement as part of the NHLBI's TOPMed program. Extensive phenotype data are provided for sequenced individuals primarily obtained from the P01HL45522 ""Genetics of Atherosclerosis in Mexican Americans"" for adults and R01HD049051 for children in these same families. Phenotype information was collected between 1991 and 2016. For this dataset, the SAFHS appellation represents an amalgamation of the original SAFHS participants and an expansion that reexamined families previously recruited for the San Antonio Family Diabetes Study (R01DK042273) and the San Antonio Family Gall Bladder Study (R01DK053889). Due to this substantial examination history, participants may have information from up to five visits. The clinical variables reported are coordinated with TOPMed and include major adverse cardiac events (MACE), T2D status and age at diagnosis, glycemic traits (fasting glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides). Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. PBMC derived gene expression assays for a subset of ~1,060 individuals obtained using the Illumina Sentrix-6 chip is also available from the baseline examination. The WGS data have been jointly called and are available in the current TOPMed accession (phs001215).   Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001215.v3.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001217.v2.p1,c1,NHLBI TOPMed: Genetic Epidemiology Network of Salt Sensitivity (GenSalt),2023-09-28,"Name: GenSalt_DS-HCR-IRB, short name: GenSalt.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The GenSalt study aims to identify genes which interact with dietary sodium and potassium intake to influence blood pressure in Han Chinese participants from rural north China. Whole genome sequencing will be conducted among 1,860 participants of the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) Study. We will work in collaboration with participating TOPMed studies to identify novel common, low-frequency and rare variants associated with an array of cardiometabolic phenotypes. In addition, we will explore the relation of low-frequency and rare variants with salt-sensitivity among GenSalt study participants.   Study Design:       Family/Twin/Trios    Study Type:  Parent-Offspring Trios Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001217.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001218.v2.p1,c2,NHLBI TOPMed: Genetic Study of Atherosclerosis Risk (GeneSTAR),2023-09-28,"Name: GeneSTAR_DS-CVD-IRB-NPU-MDS, short name: GeneSTAR.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. GeneSTAR began in 1982 as the Johns Hopkins Sibling and Family Heart Study, a prospective longitudinal family-based study conducted originally in healthy adult siblings of people with documented early onset coronary disease under 60 years of age. Commencing in 2003, the siblings, their offspring, and the coparent of the offspring participated in a 2 week trial of aspirin 81 mg/day with pre and post ex vivo platelet function assessed using multiple agonists in whole blood and platelet rich plasma. Extensive additional cardiovascular testing and risk assessment was done at baseline and serially. Follow-up was carried out to determine incident cardiovascular disease, stroke, peripheral arterial disease, diabetes, cancer, and related comorbidities, from 5 to 30 years after study entry. The goal of several additional phenotyping and interventional substudies has been to discover and amplify understanding of the mechanisms of atherogenic vascular diseases and attendant comorbidities.   Study Weblinks:   GeneSTAR    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Cohort Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001218.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001237.v2.p1,c1,NHLBI TOPMed: Women's Health Initiative (WHI),2023-09-28,"Name: WHI_HMB-IRB, short name: WHI.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200.   Study Weblinks:   WHI NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001237.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001237.v2.p1,c2,NHLBI TOPMed: Women's Health Initiative (WHI),2023-09-28,"Name: WHI_HMB-IRB-NPU, short name: WHI.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200.   Study Weblinks:   WHI NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001237.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001238.v2.p1,c1,Genetic Epidemiology Network of Arteriopathy (GENOA),2023-09-28,"Name: GENOA_DS-ASC-RF-NPU_, short name: GENOA.","The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals.   Study Weblinks:   FBPP STAMPEED    Study Design:       Prospective Longitudinal Cohort    Study Type:  Sibling Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001238.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001252.v1.p1,c1,Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE),2023-09-28,"Name: ECLIPSE_DS-COPD-RD_, short name: ECLIPSE.","ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo, European Respiratory Journal 2008; 31: 869). Inclusion criteria included age 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% predicted and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, NEJM 2010; 363: 1128) and lung function decline in COPD (Vestbo, NEJM 2011; 365: 1184). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers(Faner, Thorax 2014; 69: 666). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects.   Study Weblinks:   ECLIPSE    Study Design:       Case-Control    Study Type:  Case-Control Longitudinal Cohort Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001252.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001293.v2.p1,c1,NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy,2023-09-28,"Name: HyperGEN_GRU-IRB, short name: HyperGEN.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study.   Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001293.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001293.v2.p1,c2,NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy,2023-09-28,"Name: HyperGEN_DS-CVD-IRB-RD, short name: HyperGEN.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study.   Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001293.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001345.v2.p1,c1,NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA),2023-09-28,"Name: GENOA_DS-ASC-RF-NPU, short name: GENOA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238.   Study Weblinks:   FBPP STAMPEED    Study Design:       Family/Twin/Trios    Study Type:  Cohort Sibling Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001345.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001359.v2.p1,c1,NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate,2023-09-28,"Name: GOLDN_DS-CVD-IRB, short name: GOLDN.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.   Study Weblinks:   GOLDN    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001359.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001368.v3.p2,c1,NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study,2023-09-28,"Name: NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study, short name: CHS_HMB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE). Study Weblinks: CHS-NHLBI Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001368.v3.p2,c2,NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study,2023-09-28,"Name: NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study, short name: CHS_HMB-NPU-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE). Study Weblinks: CHS-NHLBI Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001368.v3.p2,c4,NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study,2023-09-28,"Name: NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study, short name: CHS_DS-CVD-NPU-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE). Study Weblinks: CHS-NHLBI Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001387.v2.p1,c3,NHLBI TOPMed: Rare Variants for Hypertension in Taiwan Chinese (THRV),2023-09-28,"Name: THRV_DS-CVD-IRB-COL-NPU-RD, short name: THRV.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The THRV-TOPMed study consists of three cohorts: The SAPPHIRe Family cohort (N=1,271), TSGH (Tri-Service General Hospital, a hospital-based cohort, N=160), and TCVGH (Taichung Veterans General Hospital, another hospital-based cohort, N=922), all based in Taiwan. 1,271 subjects were previously recruited as part of the NHLBI-sponsored SAPPHIRe Network (which is part of the Family Blood Pressure Program, FBPP). The SAPPHIRe families were recruited to have two or more hypertensive sibs, some families also with one normotensive/hypotensive sib. The two Hospital-based cohorts (TSGH and TCVGH) both recruited unrelated subjects with different recruitment criteria (matched with SAPPHIRe subjects for age, sex, and BMI category).   Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001387.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001395.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Hispanic Community Health Study/Study of Latinos (HCHS/SOL),2023-09-28,"Name: HCHS-SOL_HMB-NPU, short name: HCHS-SOL.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study contains whole genome sequence data. A case-control sample of individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multicenter prospective cohort study of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American background (phs000810), was selected for whole genome sequencing, including participants with a history of physician-diagnosed asthma and asthma-free participants.   Study Weblinks:   Hispanic Community Health Study / Study of Latinos NHLBI Trans-Omics for Precision Medicine Whole Genome Sequencing Program    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001395.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001395.v1.p1,c2,NHLBI TOPMed - NHGRI CCDG: Hispanic Community Health Study/Study of Latinos (HCHS/SOL),2023-09-28,"Name: HCHS-SOL_HMB, short name: HCHS-SOL.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study contains whole genome sequence data. A case-control sample of individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multicenter prospective cohort study of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American background (phs000810), was selected for whole genome sequencing, including participants with a history of physician-diagnosed asthma and asthma-free participants.   Study Weblinks:   Hispanic Community Health Study / Study of Latinos NHLBI Trans-Omics for Precision Medicine Whole Genome Sequencing Program    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001395.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001402.v2.p1,c1,NHLBI TOPMed: Whole Genome Sequencing of Venous Thromboembolism (WGS of VTE),2023-09-28,"Name: Mayo_VTE_GRU, short name: Mayo_VTE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study consists of 338 VTE cases from an inception cohort of Olmsted County, MN residents (OC) with a first lifetime objectively-diagnosed idiopathic VTE during the 40-year study period, 1966-2005. All living study subjects were invited to provide a whole blood sample at the Mayo Clinical Research Unit for leukocyte genomic DNA and plasma collection. For living study subjects who did not provide a blood sample, we retrieved any leftover blood (""waste"" blood) from samples collected as part of routine clinical diagnostic testing and used this to extract DNA after obtaining patient consent. For deceased cases, with IRB approval, we extracted DNA from any available stored tissue within the Mayo Tissue Archive. This ""tissue"" DNA has been successfully genotyped in prior studies. Three trained and experienced study nurse abstractors reviewed the complete medical records in the community of all potential cases. Note: WGS sample IDs for the previous GENEVA study cases (phs000289) are included in this dataset. The phenotypes for the GENEVA study are located under the above phs number.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001402.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001412.v3.p1,c1,NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC),2023-09-28,"Name: NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC), short name: AACAC_HMB-IRB-COL-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans. Study Design:     Cross-Sectional Study Type:CohortCross-Sectional dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001412.v3.p1,c2,NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC),2023-09-28,"Name: NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC), short name: AACAC_DS-DHD-IRB-COL-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans. Study Design:     Cross-Sectional Study Type:CohortCross-Sectional dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001416.v3.p1,c1,NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC),2023-09-28,"Name: NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC), short name: MESA_HMB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. Study Weblinks: MESA Study Design:     Prospective Longitudinal Cohort Study Type:FamilyLongitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001416.v3.p1,c2,NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC),2023-09-28,"Name: NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC), short name: MESA_HMB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. Study Weblinks: MESA Study Design:     Prospective Longitudinal Cohort Study Type:FamilyLongitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
-phs001434.v1.p1,c1,NHLBI TOPMed: Defining the time-dependent genetic and transcriptomic responses to cardiac injury among patients with arrhythmias,2023-09-28,"Name: miRhythm_GRU, short name: miRhythm.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The UMMS miRhythm Study is an ongoing study of adult patients undergoing an elective electrophysiology study or arrhythmia ablation procedure for a supraventricular or ventricular arrhythmia, including atrial fibrillation (AF). Atrial fibrillation is a major clinical and public health problem that is related to atrial pathologic remodeling. Few tools are available to quantify the activity or extent of this remodeling, rendering it difficult to identify individuals at risk for AF. Previous studies have suggested an important role for miRNA in cardiovascular disease through gene expression regulation, making this a promising avenue for studying AF mechanisms. The aim of the study is to determine the time-dependent changes to key circulating miRNAs in a model of planned atrial injury and remodeling via ablation. Such knowledge might provide additional insight into the biology and activity of the acute atrial injury response, and furthermore, inform new targets for development of preventative interventions or allow for better AF risk stratification. To assess pathways regulating atrial pathological remodeling, patient blood samples are collected prior to their ablation procedures and also at a regularly scheduled 1-month follow-up appointment. Plasma expression of miRNA is measured using high-throughput quantitative reverse transcriptase polymerase chain reaction (RT-qPCR), providing novel insights into the regulatory processes underlying AF, as well as acute atrial injury in vivo. Additionally, data collected from whole-genome sequencing (WGS) is used to supplement miRNA analyses and further explore new relations between genes and abnormal heart rhythm.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001434.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001435.v1.p1,c1,NHLBI TOPMed: Australian Familial Atrial Fibrillation Study,2023-09-28,"Name: AustralianFamilialAF_HMB-NPU-MDS, short name: AustralianFamilialAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. In the Australian Familial AF Study, a cohort of probands with familial AF was recruited for genetics studies at the Victor Chang Cardiac Research Institute. Familial AF cases were identified from in-patient and out-patient populations at St. Vincent's Hospital and by referral from collaborating physicians throughout Australia. Study subjects underwent clinical evaluation with history, ECG and echocardiogram, and informed consent was obtained from all participants. 151 probands aged <66 years at the time of diagnosis were included in this analysis. The control cohort was comprised of age- and sex-matched individuals (n=151) who had no history of cardiovascular disease. In the current TOPMed study, we have performed whole genome sequencing in European Ancestry cases with early-onset atrial fibrillation (defined as atrial fibrillation onset prior to 61 years).   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001435.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001466.v1.p1,c1,NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU),2023-09-28,"Name: pharmHU_HMB, short name: pharmHU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001466.v1.p1,c2,NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU),2023-09-28,"Name: pharmHU_DS-SCD-RD, short name: pharmHU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001466.v1.p1,c3,NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU),2023-09-28,"Name: pharmHU_DS-SCD, short name: pharmHU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001467.v1.p1,c1,NHLBI TOPMed: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE),2023-09-28,"Name: SAPPHIRE_asthma_DS-ASTHMA-IRB-COL, short name: SAPPHIRE_asthma.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Started in 2007, the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) is one of the largest asthma cohort studies in the United States. Its overarching goal is to elucidate the genetic underpinnings of asthma and asthma medication treatment response. The cohort was recruited from a large health care system serving southeast Michigan and the Detroit metropolitan area, and the participants broadly represent the demographic and socioeconomic diversity of the region. Control participants (i.e., patients without a diagnosis with asthma) were recruited from the same health system and geographic region. By virtue of their health system enrollment, both asthma case and control patients have longitudinal clinical information which was routinely collected as part of their care. Both case and control patients underwent at detailed evaluation at the time of enrollment which included lung function testing and bronchodilator response. The SAPPHIRE cohort is a member of the Asthma Translational Genomics Collaborative (ATGC). The latter was selected for whole genome sequencing in Phase 3 of the National Heart Lung and Blood Institute's TOPMed Program. The SAPPHIRE sample selected for sequencing includes African American and/or Latino individuals with and without asthma.   Study Weblinks:   Williams Lab - SAPPHIRE    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001467.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001468.v2.p1,c1,NHLBI TOPMed: REDS-III Brazil Sickle Cell Disease Cohort (REDS-BSCDC),2023-09-28,"Name: REDS-III_Brazil_SCD_GRU-IRB-PUB-NPU, short name: REDS-III_Brazil_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Establishing a Brazilian Sickle Cell Disease Cohort and Identifying Molecular Determinants of Response to Transfusions, Genetic Determinants of Alloimmunization, and Risk Factors Associated with HIV Infection. The REDS-III Brazil SCD Cohort study focused on transfusion practices and predictors of health outcomes in patients with Sickle Cell Disease (SCD) and began in the Fall of 2013. The four primary aims of this study are: 1) Aim A - Establish a cohort of SCD patients with a comprehensive centralized electronic database of detailed clinical, laboratory and transfusion information, as well as establish a repository of blood samples to support biological studies relevant to SCD pathogenesis and transfusion complications; 2) Aim B - Characterize changes in markers of inflammation in response to transfusion by analyzing chemokine/cytokine panels in serial post transfusion specimens; 3) Aim C - Identify single nucleotide polymorphisms (SNPs) that contribute to the risk of red blood cell alloimmunization in SCD by performing a genome-wide association (GWA) study in transfused SCD patients; and, 4) Aim D - Characterize risk of HIV and HIV outcomes in the Brazilian SCD population and compare SCD outcomes among HIV sero-positive and sero-negative SCD patients. Patients are enrolled from six hospitals affiliated with the participating four REDS-III Brazil hemocenters.   Study Weblinks:   REDS-III    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001468.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001472.v1.p1,c1,NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE),2023-09-28,"Name: ECLIPSE_DS-COPD-MDS-RD, short name: ECLIPSE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID:  18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID:  20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID:  21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID:  24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.   Study Weblinks:   What is ECLIPSE    Study Design:       Case-Control    Study Type:  Case-Control Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001472.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001514.v1.p1,c1,NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD),2023-09-28,"Name: Walk_PHaSST_SCD_HMB-IRB-PUB-COL-NPU-MDS-GSO, short name: Walk_PHaSST_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Clinical Trial     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001514.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001514.v1.p1,c2,NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD),2023-09-28,"Name: Walk_PHaSST_SCD_DS-SCD-IRB-PUB-COL-NPU-MDS-RD, short name: Walk_PHaSST_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Clinical Trial     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001514.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001515.v1.p1,c1,NHLBI TOPMed: MyLifeOurFuture (MLOF) Research Repository of patients with hemophilia A (factor VIII deficiency) or hemophilia B (factor IX deficiency),2023-09-28,"Name: MLOF_HMB-PUB, short name: MLOF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Hemophilia A and B are X-linked bleeding disorders resulting from a deficiency in coagulation factor VIII (FVIII) or factor IX (FIX), respectively. Hemophilia affects approximately 1/5000 male births worldwide, and results in premature death and disability due to bleeding if coagulation factor replacement therapy is not used effectively. Hemophilia is clinically categorized by coagulation factor activity levels and ranges in severity from mild (6% to 30%) to moderate (1-5%) to severe (<1%). Many female ""carriers"" of hemophilia also have decreased factor activity and morbidity from bleeding. Hemophilia A and B are almost always caused by identifiable mutations in the F8 and F9 genes, respectively, and these mutations are found throughout the structural genes. Although the hemophilias are monogenic disorders, there are wide variations in disease severity and therapeutic outcomes which are not readily explained by the disease causing mutations alone. The My Life Our Future (MLOF) project (www.mylifeourfuture.org) is a national resource developed by a partnership of BloodworksNW (BWNW, formerly the Puget Sound Blood Center), the American Thrombosis and Hemostasis Network (ATHN), the National Hemophilia Foundation (NHF) and Bioverativ, to provide free F8 and F9 gene variant analysis to patients with hemophilia A or B, and to establish a research repository of DNA sequence, DNA, RNA, buffy coat, serum and plasma. The sequence analysis and serum samples are linked to a phenotypic database hosted by ATHN, with samples submitted and clinical data entered at ~100 hemophilia treatment centers (HTCs) nationwide. (See ATHN Research Report Brief in the resource center at www.athn.org). MLOF has become the largest hemophilia genetic project worldwide. The roles of the MLOF partners are: BWNW, to serve as the central laboratory for the project and house the research repository; ATHN, to support and provide the administrative link with HTCs, to facilitate the collection of accurate phenotypic data, to conduct research review and approval for use of the repository and with BWNW to provide samples and data for research projects; NHF, to provide consumer education and facilitate consumer input into the project; and Bioverativ, to provide financial support and scientific input. The project is governed by a Steering Committee consisting of one representative from each organization. Subject samples chosen from the MLOF parent study for TOPMed and WGS were drawn from those who gave (or parents gave) informed consent for the Research Repository and included patients of all severities and type, but with an emphasis on those with severe hemophilia and others at increased risk of neutralizing antibody (inhibitor) formation and who had samples in the Research Repository (plasma, serum, RNA) for potential additional -omic studies. Also included were samples from subjects where a likely causative variant for hemophilia was not found in the F8 or F9 coding region, intron-exon boundaries or immediate upstream and downstream regions. Since hemophilia is an X-linked disorder, the majority of subjects are male. Racial distribution is similar to the overall population distribution.   Study Weblinks:   mylifeourfuture    Study Design:       Cross-Sectional    Study Type:  Cross-Sectional     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001515.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001542.v1.p1,c2,NHLBI TOPMed: Genetics of Asthma in Latino Americans (GALA),2023-09-28,"Name: GALA_DS-LD-IRB-COL, short name: GALA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. A Case pharmacogenetic study of bronchodilator drug response (Albuterol) among racially admixed Latino children with asthma between the ages of 8-40. Lung function testing was performed using the KoKo PFT system and each participant was administered albuterol dependent on age. Participants under 16 years of age, were administered 2 puffs of albuterol from a standard metered dose inhaler and 4 puffs for participants over 16 years old. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants with asthma have physician-diagnosed asthma, symptoms and medications.   Study Weblinks:   Asthma Collaboratory    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001542.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001543.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: AF Biobank LMU in the context of the MED Biobank LMU,2023-09-28,"Name: AFLMU_HMB-IRB-PUB-COL-NPU-MDS, short name: AFLMU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Atrial Fibrillation Biobank Ludwig Maximilian University (AFLMU) Study contributes to the spectrum of disease by adding carefully characterized patients with atrial fibrillation. Atrial fibrillation, one of the most common human arrhythmias confers major morbidity, mortality and health care cost, and has been demonstrated to be caused and influenced by genetic and -omics factors. Particularly, AFLMU enrolled patients with an early onset of atrial fibrillation to increase the genetic burden on disease pathophysiology. All patients were recruited applying standardized protocols to maintain homogeneity in data and DNA quality.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001543.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001544.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Malmo Preventive Project (MPP),2023-09-28,"Name: MPP_HMB-NPU-MDS, short name: MPP.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Malmö Preventive Project (MPP) was a community-based disease prevention program including 33,346 inhabitants from the city of Malmö in Southern Sweden. Complete birth cohorts between 1921-1949 were invited, and the participation rate was 71%. Participants underwent screening between 1974 to 1992 for cardiovascular risk factors, alcohol abuse, and breast cancer. Between 2002-2006, surviving participants were invited to a reexamination which included blood sampling from which DNA has been extracted. Subjects with prevalent or incident AF were identified from national registers as previously described, and cases with DNA were then matched in a 1:1 fashion to controls with DNA from the same cohort by sex, age (±1 year), and date of baseline exam (±1 year). Also, controls required a follow-up exceeding that of the corresponding AF case.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001544.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001545.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Intermountain INSPIRE Registry,2023-09-28,"Name: INSPIRE_AF_DS-MULTIPLE_DISEASES-MDS, short name: INSPIRE_AF_DS-MULTIPLE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The INtermountain Healthcare Biological Samples Collection Project and Investigational REgistry for the On-going Study of Disease Origin, Progression and Treatment (Intermountain INSPIRE Registry) purpose is to collect biological samples, clinical information and laboratory data from Intermountain Healthcare patients. The registry originally collected samples in patients undergoing a coronary angiography as part of the Intermountain Heart Collaborative Study. It has been expanded to collect samples in patients diagnosed with all types of medical conditions, and patients from the general population including those who have not been diagnosed with health related issues. Just over 25,000 individuals have provided samples as part of this registry. The registry enables researchers to develop a comprehensive collection of information that may help in disease management, including determining best medical practices for predicting, preventing and treating medical conditions.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001545.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001546.v1.p1,c1,NHLBI TOPMed: Determining the association of chromosomal variants with non-PV triggers and ablation-outcome in AF (DECAF),2023-09-28,"Name: DECAF_GRU, short name: DECAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The DECAF trial was conducted at the Texas Cardiac Arrhythmia Institute (TCAI) in 2013 in collaboration with the University of Texas at Austin. Four hundred consecutive AF patients undergoing catheter ablation were enrolled. All participants provided voluntary informed consents. Blood samples were collected before the ablation procedure and labeled with anonymous patient identifier. The researchers at UT Austin responsible for DNA extraction and genetic analysis were blinded about the clinical characteristics and identification of the study participants. AF cases included adults >18 years of age from both sex and all AF types.   Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001546.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001547.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The GENetics in Atrial Fibrillation (GENAF) Study,2023-09-28,"Name: GENAF_HMB-NPU, short name: GENAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Genetics in AF (GENAF) study enrolled individuals with early-onset lone AF before age 50 in Norway between 2009 and 2016. Early-onset was defined as diagnosis of AF before age 50. Lone AF was defined as AF in the absence of clinical or echocardiographic findings of cardiovascular disease, hypertension, metabolic or pulmonary disease. AF was documented in ECG. All participants underwent clinical examination, including ECG, echocardiography, and blood draw, from which DNA has been extracted. The study conforms to the principles of the Declaration of Helsinki and was approved by the Regional Ethics Committee (REK) in Norway (Protocol reference number: 2009/2224-5). All included patients gave written informed consent.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001547.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001598.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study,2023-09-28,"Name: JHU_AF_HMB-NPU-MDS, short name: JHU_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001598.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001599.v1.p1,c1,NHLBI TOPMed: Boston-Brazil Sickle Cell Disease (SCD) Cohort,2023-09-28,"Name: BostonBrazil_SCD_HMB-IRB-COL, short name: BostonBrazil_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.This study involves sequencing of patients with a diagnosis of sickle cell disease from Brazil. No exclusionary criteria were employed and any eligible patients that consented to this study were recruited. Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-07-13 and may not include exact formatting or images."
-phs001600.v2.p2,c1,NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort,2023-09-28,"Name: CATHGEN_DS-CVD-IRB, short name: CATHGEN.","'This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ''TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4'' and ''TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4''. Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-pop NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images.'"
-phs001601.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Penn Medicine BioBank Early Onset Atrial Fibrillation Study,2023-09-28,"Name: CCDG_PMBB_AF_HMB-IRB-PUB, short name: CCDG_PMBB_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   'TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2'  and 'TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4'.  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Cases with early-onset atrial fibrillation were selected from the Penn Biobank based on an age of atrial fibrillation onset prior to 61 years of age, and in the absence of a myocardial infarction, heart failure or severe valvular disease.   Study Design:       Case Set    Study Type:  Case Set        dbGaP estimated ancestry using     GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
-phs001602.v1.p1,c1,NHLBI TOPMed: Children's Health Study (CHS) Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP),2023-09-28,"Name: ChildrensHS_GAP_GRU, short name: ChildrensHS_GAP.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP) study was proposed to use an innovative genetics approach in mice and humans to identify novel variants that interact with traffic-related pollutant exposures to affect lung function phenotypes and the risk of childhood asthma. The study participants were enrolled from the original southern California Children's Health Study (CHS). In the TOPMed project, seven Hispanic White participants who did not have asthma history were included in the WGS analysis.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001602.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001603.v1.p1,c1,NHLBI TOPMed: Children's Health Study (CHS) Integrative Genomics and Environmental Research of Asthma (IGERA),2023-09-28,"Name: ChildrensHS_IGERA_GRU, short name: ChildrensHS_IGERA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Integrative Genomics and Environmental Research of Asthma (IGERA) Study was proposed to collect immortalized cell lines, RNA, cDNA and DNA from 400 well-characterized subjects who participated in the southern California Children's Health Study (CHS) and to develop an accompanying database for these samples consisting of extensive phenotype, exposure, genome-wide genotype, gene expression, and methylation data. A subset of Hispanic-White participants (n=160) were included in the TOPMed project, including 77 asthma cases and 83 controls.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001603.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001604.v1.p1,c1,NHLBI TOPMed: Children's Health Study (CHS) Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR),2023-09-28,"Name: ChildrensHS_MetaAir_GRU, short name: ChildrensHS_MetaAir.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR) study was proposed to study a subset of the Children's Health Study (CHS) participants representing the extremes of long-term traffic-related air pollution exposure occurring in Southern California CHS communities. The primary aim of the Meta-AIR study was to investigate whether lifetime exposure to air pollution increases risk for obesity and metabolic dysfunction at 17-18 years of age. A total of 56 Hispanic White participants (16 asthma cases and 40 controls) were included in the TOPMed project.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001604.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001605.v1.p1,c2,NHLBI TOPMed: Chicago Initiative to Raise Asthma Health Equity (CHIRAH),2023-09-28,"Name: CHIRAH_DS-ASTHMA-IRB-COL, short name: CHIRAH.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The CHIRAH project was a community based study of the factors associated with asthma morbidity in the African American population. CHIRAH evaluated the role of various variables (biologic / environmental, psychologic / behavioral, and socioeconomic) on asthma morbidity and the function of changes in these variables on asthma morbidity in a longitudinal fashion. This involved collection of a cohort based on school screening which was sampled to include similar numbers of underprivileged and non-underprivileged subjects which roughly equally represented self-classified African Americans and self-classified non-African Americans. Subjects were followed-up every 3 months of this cohort over the course of 2 years.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001605.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001606.v1.p1,c1,NHLBI TOPMed: Early-onset Atrial Fibrillation in the Estonian Biobank,2023-09-28,"Name: EGCUT_GRU, short name: EGCUT.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up.   Study Weblinks:   EGCUT Estonian BioBank    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001606.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001607.v2.p2,c1,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,2023-09-28,"Name: IPF_DS-ILD-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001607.v2.p2,c2,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,2023-09-28,"Name: IPF_DS-LD-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001607.v2.p2,c3,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,2023-09-28,"Name: IPF_DS-PFIB-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001607.v2.p2,c4,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,2023-09-28,"Name: IPF_DS-PUL-ILD-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001607.v2.p2,c5,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,2023-09-28,"Name: IPF_HMB-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
-phs001608.v1.p1,c1,NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG),2023-09-28,"Name: OMG_SCD_DS-SCD-IRB-PUB-COL-MDS-RD, short name: OMG_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, ""Outcome Modifying Genes in Sickle Cell Disease"" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001608.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001612.v1.p1,c1,NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA),2023-09-28,"Name: CARDIA_HMB-IRB, short name: CARDIA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.   Study Weblinks:   CARDIA: Coronary Artery Risk Development in Young Adults    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001612.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001612.v1.p1,c2,NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA),2023-09-28,"Name: CARDIA_HMB-IRB-NPU, short name: CARDIA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.   Study Weblinks:   CARDIA: Coronary Artery Risk Development in Young Adults    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001612.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001624.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The Vanderbilt University BioVU Atrial Fibrillation Genetics Study,2023-09-28,"Name: BioVU_AF_HMB-GSO, short name: BioVU_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. At least 2.7 million Americans are living with AFib. Individuals with early onset atrial fibrillation (AF) are included in this study of cases from the BioVU sample repository. BioVU is Vanderbilt's biobank of DNA extracted from leftover and otherwise discarded clinical blood specimens. BioVU operates as a consented biorepository; all individuals must sign the BioVU consent form in order to donate future specimens. BioVU subjects are de-identified and linked to the Synthetic Derivative enabling researchers to access genetic data/DNA material as well as dense, longitudinal electronic medical record (EMR) information.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001624.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001644.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai,2023-09-28,"Name: BioMe_HMB-NPU, short name: BioMe.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants enroll through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a ""data-broker"" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry (Table 1, Figure 1). BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%) (Table 1, Figure 1). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has available a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden.  ** Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. ** Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individual with COPD (62% women) and 1800 as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.   Study Weblinks:   The Charles Bronfman Institute for Personalized Medicine    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001644.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001661.v2.p1,c1,NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A),2023-09-28,"Name: GCPD-A_DS-ASTHMA-GSO, short name: GCPD-A.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001661.v2.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001662.v1.p1,c2,NHLBI TOPMed: Lung Tissue Research Consortium (LTRC),2023-09-28,"Name: LTRC_HMB-MDS, short name: LTRC.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburg, and Temple University.   Study Weblinks:   LTRC    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001662.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001682.v1.p1,c1,NHLBI TOPMed: Pulmonary Hypertension and the Hypoxic Response in SCD (PUSH),2023-09-28,"Name: PUSH_SCD_DS-SCD-IRB-PUB-COL, short name: PUSH_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. During Visit One, the PUSH Study will perform echocardiography on 600 children and adolescent with patients with SCD and 100 control children and adolescents at three Field Centers, namely Howard University, Children's National Medical Center and University of Michigan. Patients or their parents will be approached and asked to give informed consent. If they appear to have difficulty reading, reading of the consent will be offered. Patients or their parents not appearing to comprehend the consent will not be eligible. As a part of this visit, each participant or parent will sign informed consent, complete a Participant Contact Information Form, complete a Medical History Form, undergo physical examination with completion of a Physical Examination Form and have blood drawn. Each participant must have echocardiography performed with measurement of Tricuspid Regurgitant Jet Velocity (TRV). In addition attempts will be made 1) to perform a six-minute walk test, 2) to collect information from a recent (within six months) Transcranial Doppler Study (TCD) or to perform TCD, and 3) to perform pulmonary function tests. Study personnel will review all forms for completeness and conduct phlebotomy. Blood will be shipped to the Central Lab. Results of all procedures and tests will be transmitted to the Data Manager at Howard University. Sequencing was only done on sickle cell participants.    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001682.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001725.v1.p1,c1,NHLBI TOPMed CCDG: Groningen Genetics of Atrial Fibrillation (GGAF) Study,2023-09-28,"Name: GGAF_GRU, short name: GGAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. The Groningen Genetics of Atrial Fibrillation (GGAF) cohort is a cohort composed from 5 different sources of individuals with atrial fibrillation (AF) and age and sex-matched controls. Written informed consent was provided from all participating individuals, and all 5 studies were approved by the ethical committee at the University Medical Center (www.atrialfibrillationresearch.nl) and Maastricht University. All samples selected for TOPMed WGS are from individuals with atrial fibrillation.   Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001725.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001726.v1.p1,c1,NHLBI TOPMed: Childhood Asthma Management Program (CAMP),2023-09-28,"Name: CAMP_DS-AST-COPD, short name: CAMP.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Childhood Asthma Management Program (CAMP) was designed to evaluate whether continuous, long-term treatment (over a period of four to six years) with either an inhaled corticosteroid (budesonide) or an inhaled noncorticosteroid drug (nedocromil) safely produces an improvement in lung growth as compared with treatment for symptoms only (with albuterol and, if necessary, prednisone, administered as needed). The primary outcome in the study was lung growth, as assessed by the change in forced expiratory volume in one second (FEV1, expressed as a percentage of the predicted value) after the administration of a bronchodilator. Secondary outcomes included the degree of airway responsiveness, morbidity, physical growth, and psychological development.   Study Design:       Family/Twin/Trios    Study Type:  Parent-Offspring Trios     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001726.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001727.v1.p1,c2,NHLBI TOPMed: Pathways to Immunologically Mediated Asthma (PIMA),2023-09-28,"Name: PIMA_DS-ASTHMA-IRB-COL, short name: PIMA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Study designed to further our understanding of the pathogenesis of asthma exacerbations in children. Children enrolled in the study (n=217) were all asthmatic and primarily Hispanic white. The children were followed for 18 months until they experienced an asthma exacerbation or completed the follow-up without an exacerbation. The time to the first asthma exacerbation was considered the outcome. The acute and convalescent immune phenotype of each asthma exacerbation was documented.   Study Weblinks:   PIMA    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001727.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001728.v1.p1,c2,NHLBI TOPMed: Best ADd-on Therapy Giving Effective Response (BADGER),2023-09-28,"Name: CARE_BADGER_DS-ASTHMA-IRB-COL, short name: CARE_BADGER.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. BADGER is a 56-week randomized, double-blind, three-treatment, three-period cross-over trial that will evaluate the differential improvement in control that is achieved following three separate treatment interventions in children whose asthma is not acceptably controlled on a low dose of ICS (per NAEPP guidelines). All participants will enter an 8-week run-in period during which time they will receive a dose of 1x ICS (fluticasone 200 μg/day). During this 8-week time period, running 2-week averages to establish the lack of acceptable asthma control will be calculated. Thus, a child could qualify for randomization at any time during this 8-week run-in period. This approach should maximize both patient safety and successful enrollment. Children will continue to receive 1x ICS during the entire treatment phase. During each period of the treatment phase, they also will receive one add-on therapy in the form of LABA, LTRA or additional 1x ICS. The order of the add-on therapy assignment will be determined by randomization into one of six treatment sequences (order determined randomly). Each treatment period will be 16 weeks in length; the initial 4 weeks of each period will be considered to be the washout period for the previous treatment. The primary outcome measures will be frequency of asthma exacerbations, asthma control days, and FEV1.   Study Weblinks:   BADGER    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001728.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001729.v1.p1,c2,NHLBI TOPMed: Characterizing the Response to a Leukotriene Receptor Antagonist and an Inhaled Corticosteroid (CLIC),2023-09-28,"Name: CARE_CLIC_DS-ASTHMA-IRB-COL, short name: CARE_CLIC.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Within-subject clinical responses to either inhaled corticosteroids or Montelukast were compared in 126 children with mild to moderate asthma.   Study Weblinks:   CLIC    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001729.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001730.v1.p1,c2,NHLBI TOPMed: Pediatric Asthma Controller Trial (PACT),2023-09-28,"Name: CARE_PACT_DS-ASTHMA-IRB-COL, short name: CARE_PACT.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. After a 2-4 week assessment/characterization run-in period, 6-14 year-old children who met NAEPP criteria for mild-moderate persistent asthma specifically based on symptom criteria and methacholine PC20 ≤ 12.5 mg/ml and FEV1 ≥ 80% were randomized to one of the three active treatment arms for 12 months. Randomization was stratified according to clinical center, bronchodilator response (< 12% or ≥ 12%), race (Caucasian or non-Caucasian), and methacholine PC20 (< 2 or ≥ 2 mg/ml). The primary outcome variable was the proportion of asthma-free days during the 12-month treatment period. Secondary outcomes included other measures of asthma control (percentage of rescue-free days, albuterol-free days, and episode-free days; the number of asthma exacerbations requiring prednisone therapy and the time to the first asthma exacerbation), forced oscillation and spirometry, reversibility (FEV1 pre- and post 2 puffs of albuterol MDI), methacholine PC20, exhaled nitric oxide, and asthma-related quality of life.   Study Weblinks:   PACT    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001730.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001732.v1.p1,c2,NHLBI TOPMed: TReating Children to Prevent EXacerbations of Asthma (TREXA),2023-09-28,"Name: CARE_TREXA_DS-ASTHMA-IRB-COL, short name: CARE_TREXA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. TREXA is a 44-week randomized, double-blind, double-masked, four-treatment, parallel trial that will evaluate the weaning strategy that provides the best protection against the development of exacerbations in children whose asthma is acceptably controlled on a low dose of ICS (per NAEPP guidelines). Following the 4 weeks of the run-in period on a 1x dose of ICS (100 µg fluticasone b.i.d. or its equivalent), children who do not meet the definition of acceptable asthma control will be randomized to the parallel BADGER protocol; those who meet the definition of acceptable asthma control will be enrolled into the 44-week treatment phase of the study. The primary outcome measure will be time to first exacerbation requiring a prednisone course.   Study Weblinks:   TREXA    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001732.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs001735.v2.p1,c1,NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank,2023-09-28,"Name: PCGC_CHD_HMB, short name: PCGC_CHD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design:     Prospective Longitudinal Cohort Study Type:Case SetParent-Offspring Trios dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-07-13 and may not include exact formatting or images."
-phs001735.v2.p1,c2,NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank,2023-09-28,"Name: PCGC_CHD_DS-CHD, short name: PCGC_CHD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design:     Prospective Longitudinal Cohort Study Type:Case SetParent-Offspring Trios dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-07-13 and may not include exact formatting or images."
-phs001843.v1.p2,c1,Pediatric Cardiac Genomics Consortium (PCGC) Study - Centers for Mendelian Genomics Collaboration,2023-09-28,"Name: CMG_WGS_HMB, short name: CMG_WGS_HMB.","This substudy phs001843 PCGC Study - CMG Collaboration contains whole genome sequences. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194. Mendelian cardiovascular disorders provide crucial insights into the genetic susceptibility to more common forms of cardiovascular disease. While Mendelian cardiovascular disorders are individually rare, collectively they impose a significant public health burden. This proposal focuses on 2 specific categories of cardiovascular disease for which we have extensive research expertise and existing cohorts, congenital heart disease (CHD) and inherited arrhythmia syndromes. The tremendous burden on the health care system and on families with these Mendelian cardiovascular disorders underscore the urgency to understand their genomic bases, in order to design improved strategies for risk stratification, surveillance and medical intervention. Emerging evidence supports the use of whole-genome sequencing (WGS) over whole-exome sequencing (WES) for detecting coding variants in discovery projects, in addition to the obvious advantages of detecting features invisible to WES: structural variants (SV) and non-coding variants. We believe the way forward lies in widening the scope for discovery to include the patient's entire genome - and all types of variants. While family-based studies are crucial for genomic discovery, obtaining a sufficient number of high-risk pedigrees to achieve meaningful conclusions remains a challenge for most research institutions. For this proposal, we will leverage 2 powerful resources for the identification, ascertainment and recruitment of high-risk cardiovascular disease pedigrees: (1) the NHLBI-sponsored Pediatric Cardiac Genomics Consortium (PCGC) and (2) the Utah Population Database (UPDB). We propose to perform WGS on PCGC and UPDB cohorts with autosomal dominant disease to achieve the following Specific Aims: Aim 1) Identify the genomic basis for CHD in high-risk pedigrees derived from the PCGC and UPDB; and Aim 2) Identify the genomic basis for inherited arrhythmia disorders, using extended pedigrees derived from the UPDB. Aim 2 focuses on familial forms of AF, undiagnosed Long QT Syndrome, Wolff-Parkinson White syndrome and progressive conduction disorders. A WGS approach in high-risk pedigrees coupled with our validated bioinformatics pipeline, will allow the identification and prioritization of disease-causing SVs and sequence variants in coding and non-coding regulatory elements. These variants will be functionally characterized and validated in downstream experiments (heterologous expression systems, zebrafish cardiac assays, induced pluripotent stem cell-derived cardiomyocytes) that are beyond the scope of this X01. For this proposal, we have assembled the right combination of clinical expertise, resources for patient recruitment and computational know-how to enable these game-changing methodologies and to apply them to the challenge of cardiovascular Mendelian disease-gene discovery. Study Weblinks: Bench to Bassinet Program Study Design:     Family/Twin/Trios Study Type:FamilyCohortNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images."
-phs001927.v1.p1,c1,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),2023-09-28,"Name: SPIROMICS_DS-COPD-NPU, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
-phs001927.v1.p1,c2,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),2023-09-28,"Name: SPIROMICS_DS-COPD, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
-phs001927.v1.p1,c3,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),2023-09-28,"Name: SPIROMICS_GRU-NPU, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
-phs001927.v1.p1,c4,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),2023-09-28,"Name: SPIROMICS_GRU, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
-phs001961.v2.p1,c1,LungMAP: Molecular Atlas of Lung Development – Human Lung Tissue,2023-09-28,"Name: MALD_GRU, short name: MALD_GRU.","Mammalian fetal lung development is a complex biological process. Despite considerable progress, a comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. The purpose of this study as part of the LungMAP consortium (www.lungmap.net) is to understand the transcriptional changes in the process of mammalian lung development. Study Weblinks: NCBI GEO GSE161383 Study Design:     Control Set Study Type:LongitudinalSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-01 and may not include exact formatting or images."
-phs002299.v1.p1,c1,PETAL Network: Outcomes Related to COVID-19 Treated With Hydroxychloroquine Among Inpatients With Symptomatic Disease (ORCHID) Trial,2023-09-28,"Name: ORCHID_HMB, short name: ORCHID.","ORCHID was a multicenter, blinded, placebo-controlled randomized trial conducted at 34 hospitals in the US between April 2 and June 19, 2020. Adults hospitalized with respiratory symptoms from severe acute respiratory syndrome coronavirus 2 infection were enrolled, with the last outcome assessment on July 17, 2020. The planned sample size was 510 patients with five interim analyses; however, the trial was stopped at the fourth interim analysis for futility with a sample size of 479 patients.The distribution of the day 14 clinical status score (measured using a 7-category ordinal scale) was not significantly different for patients randomized to receive hydroxychloroquine compared with placebo.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.    Study Weblinks:   PETAL Network ORCHID Study    Study Design:       Clinical Trial    Study Type:  Clinical Trial Controlled Trial Placebo-Controlled Randomized Randomized Controlled Clinical Trial   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002299.v1.p1 on 2021-03-25 and may not include exact formatting or images."
-phs002348.v1.p1,c1,Multicenter Study of Hydroxyurea (MSH),2023-09-28,"Name: MSH_GRU, short name: MSH.","This study aimed to determine whether or not treatment with hydroxyurea titrated to maximum tolerated doses would reduce the frequency of vaso-occlusive (painful) crises by at least 50% in 299 men and women between 18 and 50 years old with a diagnosis of sickle cell anemia by gel electrophoresis conducted by a Core Laboratory. A secondary objective investigated correlations of fetal hemoglobin (HbF) levels and other patient or treatment characteristics with the occurrence of vaso-occlusive (painful) crises, and the effect of treatment on the quality of life.This controlled trial made hydroxyurea the first drug of proven benefit in preventing vaso-occlusive pain crisis and acute chest syndrome caused by sickle cell disease, with additional findings including reduced mortality in adult patients taking hydroxyurea for frequent painful sickle cell episodes after 9 of years follow-up. No significant side-effects of hydroxyurea therapy were noted.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.    Study Weblinks:      ClinicalTrials.gov (MSH) NHLBI BioLINCC (MSH)    Study Design:       Clinical Trial    Study Type:  Double-Blind Randomized Controlled Clinical Trial   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
-phs002362.v1.p1,c1,Cooperative Study of Sickle Cell Disease (CSSCD),2023-09-28,"Name: CSSCD_GRU, short name: CSSCD.","The Cooperative Study of Sickle Cell Disease was initiated in 1977 to determine the natural history of sickle cell disease (SCD) from birth to death in order to identify those factors contributing to the morbidity and mortality of the disease. Specific objectives included: 1) to study the effect of sickle cell disease on growth and development from birth through adolescence 2) to study the conditions or events that may be related to the onset of painful crises 3) to obtain data on the nature, duration, and outcome of major complications of SCD 4) determine the nature, prevalence, and age- related incidence of organ damage due to SCD, and 5) study the role of SCD and its interaction with selected health events.Phases 2 and 3 of the study involved followup of the infant cohort. A total of 709 infants (age less than 6 months) were enrolled during Phase 1 of the Cooperative Study of Sickle Cell Disease (CSSCD), and Phases 2 and 3 of the CSSCD was designed to follow these children for an additional 10 years. The study objectives included: 1) define prospectively the natural history of sickle cell disease; 2) determine the relationships between cognitive and academic functioning and brain status as determined by MRI; 3) determine the cognitive or behavioral markers of silent infarct; 4) determine the relationship of family functioning on the Family Environment Scale (FES) to brain status, cognitive functioning, and social and demographic factors; 5) continue studies that will enhance the state of knowledge on the influence of sickle cell disease on the psychosocial adjustment of children and adolescents. Phase 2A of the study sought to examine the progression of organ damage in the heart, lung, kidney, and liver in adult cohort patients (born before 1/1/56) enrolled in phase 1 of the study between 3/79 and 5/81. A total of 620 patients from 11 centers were eligible for phase 2A.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.     Study Weblinks:      ClinicalTrials.gov (CSSCD) BioLINCC (CSSCD) - For biospecimen requests    Study Design:       Clinical Trial    Study Type:  Case-Control Clinical Trial   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
-phs002363.v1.p1,c1,PETAL - Repository of Electronic Data COVID-19 Observational Study,2023-09-28,"Name: RED_CORAL_HMB, short name: RED_CORAL_HMB.","To describe characteristics, treatment, and outcomes among patients hospitalized with COVID-19 early in the pandemic, 1480 consecutive adult inpatients with laboratory-confirmed, symptomatic SARS-CoV-2 infection admitted to 57 US hospitals from March 1 to April 1, 2020 were studied.It was found that in a geographically diverse early-pandemic COVID-19 cohort with complete hospital folllow-up, hospital mortality was associated with older age, comorbidity burden, and male sex. Intensive care unit admissions occurred early and were associated with protracted hospital stays. Survivors often required new health care services or respiratory support at discharge.The PETAL Network central institutional review board at Vanderbilt University and the institutional review boards at each participating hospital approved the study or determined that the study was exempt from review.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: PETAL Network RED CORAL StudyNHLBI BioLINCC (RED CORAL) Study Design:     Control Set Study Type:Case-CohortClinical CohortCohortMulticenter NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images."
-phs002383.v1.p1,c1,Treatment of Pulmonary Hypertension and Sickle Cell Disease With Sildenafil Therapy (walk-PHaSST),2023-09-28,"Name: Walk_PHaSST_GRU, short name: Walk_PHaSST_GRU.","Pulmonary arterial hypertension (PAH) is a progressive condition characterized by narrowing or stiffening pulmonary arterioles resulting in increased pulmonary blood pressure and reduced delivery of oxygenated blood to the body. It is a common complication of sickle cell disease and initially presents with the symptom of shortness of breath (dyspnea) on exertion. As the condition worsens, other symptoms such as dizziness, lower extremity edema, and chest pain can develop. The drug, sildenafil, works by relaxing blood vessels in the lungs which reduces pulmonary blood pressure and allows more oxygenated blood to circulate. Increased levels of oxygenated blood allows individuals with PAH to tolerate more activity, but guidelines for using sildenafil in patients with PAH and sickle cell disease were unavailable at the time of the Walk-PHaSST trial.Participants were screened for the existence of pulmonary hypertension with a six minute walk test and a Doppler echocardiogram that assessed TRV, diastolic function, and valvular and systolic function. Subjects with TRV ≥ 2.7 m/s received further clinical evaluation for possible causes of pulmonary hypertension. Other screening data included medical history, a physical exam, and standard laboratory testing. For individuals with moderate to severe pulmonary hypertension (TRV ≥ 3.0), a cardiac catheterization was done at the baseline and week 16 data collection periods.Subjects eligible for the main intervention trial based on screening results were randomized in a 1:1 double blind fashion to receive sildenafil or placebo for 16 weeks. Subjects received 20 mg of oral sildenafil or matching placebo 3 times daily for 6 weeks, followed by 40 mg 3 times daily for 4 weeks, followed by 80 mg 3 times daily for 6 weeks, as tolerated. Participants could also receive other therapies as needed to manage sickle cell and related complications. The primary outcome measure of the trial was change in the six minute walk test, a standard indicator of a person's heart and lung function and exercise capacity, from baseline to week 16. After completing the study treatment (or placebo), participants could choose to be part of the open-label follow-up phase of the study and continue to be assessed for up to one year.The study was intended to screen about 1000 subjects and randomize 132 subjects, however it was terminated early due to the unforeseen increase in adverse events in participants treated with sildenafil as compared to placebo. When the study was stopped, 33 participants had completed the trial. Subjects continued to be monitored, but were instructed to taper sildenafil treatment over three to seven days.There was no evidence that treatment with sildenafil impacted the six minute walk distance from baseline to week 16. In addition, treatment with sildenafil appeared to increase rates of hospitalization due to sickle cell disease pain.Due to in part to the early termination of the trial, the majority of subject data was collected from the screening phase of the study (n=720), as opposed to the main intervention trial (n=74).Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.   Study Weblinks:      ClinicalTrials.gov (Walk-PHaSST) BioLINCC (Walk-PHaSST)    Study Design:       Clinical Trial    Study Type:  Clinical Trial Double-Blind   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
-phs002385.v1.p1,c1,Hematopoietic Cell Transplant for Sickle Cell Disease (HCT for SCD),2023-09-28,"Name: CIBMTR_GRU, short name: CIBMTR.","The Center for International Blood and Marrow Transplant Research (CIBMTR) is a hematopoietic cell transplant registry that was established in 1972 at the Medical College of Wisconsin. The overarching goal of the registry is to study trends in transplantations and to advance the understanding and application of allogeneic hematopoietic cell transplantation for malignant and non-malignant diseases. Included in this dataset are children, adolescents and young adults with severe sickle cell disease who received an allogeneic hematopoietic cell transplant in the United States and provided written informed consent for research.Hematopoietic cell transplant for sickle cell disease is curative. Offering this treatment for patients with severe disease is challenging as only about 20-25% of patients expected to benefit have an HLA-matched sibling. Consequently, several transplantations have utilized an HLA-matched or mismatched unrelated adult donor and HLA-mismatched relative. Transplantation strategies have also evolved over time that has included transplant conditioning regimens of varying intensity, grafts other than bone marrow and novel approaches to overcome the donor-recipient histocompatibility barrier and limit graft-versus-host disease. The data that is available for sickle cell disease transplants have been utilized to report on outcomes after transplantation and compare outcomes after transplantation of grafts HLA-matched related, HLA-mismatched related, HLA-matched and HLA-mismatched unrelated donors. Collectively, these data have advanced our knowledge and understanding of hematopoietic cell transplant for this disease. These data can also serve as 'contemporaneous controls' for comparison with other more recent curative treatments like gene therapy and gene editing.Data available for request include allogeneic hematopoietic cell transplants for sickle cell disease (Hb SS and Hb Sβ thalassemia) in the United States from 1991 to 2019. Follow-up data through December 2020 are available.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.   Study Weblinks:      ClinicalTrials.gov (HCT for SCD) BioLINCC (HCT for SCD)    Study Design:       Prospective Longitudinal Cohort    Study Type:  Clinical Cohort Cohort Control Set Longitudinal Longitudinal Cohort Multicenter Observational   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
-phs002386.v1.p1,c1,Optimizing Primary Stroke Prevention in Children with Sickle Cell Anemia (STOP II),2023-09-28,"Name: STOPII_GRU, short name: STOPII.","The STOP II trial evaluated whether prophylactic transfusion in patients with sickle cell disease and high risk of stroke can be safely halted after 30 months of treatment during which patients became low risk for stroke.Stroke causes substantial morbidity in children with sickle cell disease. To prevent first strokes, the Stroke Prevention Trial in Sickle Cell Anemia (STOP) used prophylactic transfusions in children who were identified by transcranial Doppler (TCD) ultrasonography as being at high risk for stroke. This strategy reduced the incidence of stroke among such children from 10% per year to less than 1% per year, leading to recommendations for TCD screening and prophylactic transfusion for children with abnormal velocities on ultrasonography. Despite the reduced risk of stroke, long-term use of transfusions can cause adverse side effects, such as iron overload or alloimmunization. However, cessation of transfusions is associated with recurrence of stroke, and at the time of the STOP II trial, there were no clinical or laboratory indicators to guide the duration of prophylaxis. Therefore the STOP II trial was initiated to determine whether transfusions could be limited by monitoring patients with TCD examinations after transfusions were halted and resuming transfusions if the examination indicated a high risk of stroke.The trial was halted for safety concerns after 79 of a planned 100 children were randomized. Discontinuation of transfusion for the prevention of stroke in children with sickle cell disease resulted in a high rate of reversion to abnormal blood-flow velocities on Doppler studies and stroke incidence.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.    Study Weblinks:      BioLINCC (STOP II) ClinicalTrials.gov (STOP II)    Study Design:       Clinical Trial    Study Type:  Clinical Trial Randomized   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
-phs002415.v1.p1,c1,Hydroxyurea to Prevent Organ Damage in Children with Sickle Cell Anemia (BABY HUG),2023-09-28,"Name: BabyHug_DS-SCD-IRB-RD, short name: BabyHug.","Sickle cell anemia is associated with substantial morbidity from acute complications and organ dysfunction beginning in the first year of life. In 1995, the Multicenter Study of Hydroxyurea (MSH) (dbGaP phs002348) demonstrated that, in adults, hydroxyurea is effective in decreasing the frequency of painful crises, hospitalizations for crises, acute chest syndrome, and blood transfusions by 50%. The phase I/II study of hydroxyurea in children (HUG KIDS) demonstrated that children have a response to hydroxyurea similar to that seen in adults in terms of increasing fetal hemoglobin levels and total hemoglobin, and decreasing complications associated with sickle cell anemia. In addition, this study demonstrated that the drug does not adversely affect growth and development between the ages of 5 and 15. A pilot study of hydroxyurea (HUSOFT) given to children between the ages of 6 months and 24 months demonstrated that the drug was well tolerated and that the fetal hemoglobin levels rose and remained elevated compared to baseline with continued hydroxyurea administration.A Special Emphasis Panel (SEP) met on April 12, 1996 to review the results of the MSH trial and the progress to date of the HUG KIDS study. The SEP recommended that NHLBI undertake the BABY HUG trial.The BABY HUG Randomized Controlled Trial concluded that hydroxyurea treatment in very young children seemed to have an acceptable safety profile and to reduce complications of sickle cell anemia. However, more data were needed on the long-term safety of hydroxyurea use in very young children. As a result, follow-up studies were initiated. The Follow-Up Study II provided longer follow-up than Follow-Up Study I, and included more assessment types than Follow-Up Study I.The BABY HUG program consisted of three related studies, each of which has associated datasets and bio-specimens.A randomized controlled trial comparing hydroxyurea to placebo in very young children with sickle cell anemia (BABY HUG Randomized Controlled Trial)The first observational follow-up study of children from the randomized controlled trial (BABY HUG Follow-Up Study I). All children in Follow-Up Study I were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The second observational follow-up study of children from BABY HUG Follow-Up Study I. All children in Follow-Up Study II were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The purpose of the Randomized Controlled Trial was to determine if hydroxyurea can safely prevent early end organ damage in very young children with sickle cell anemia.The purpose of the BABY HUG Follow-up Study I was to provide structured follow-up of the children enrolled in the BABY HUG Randomized Controlled Trial, in order to characterize the long-term toxicities and unexpected risks (if any) associated with treatment with hydroxyurea at an early age.The objective of Follow-Up Study II was to obtain additional data about the long-term safety and efficacy of hydroxyurea use in children with Sickle Cell Anemia through at least the first decade of life.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks:     Randomized Control TrialFollow-Up Study IFollow-Up Study IIBioLINCC - BABY HUG Study Design:     Clinical Trial Study Type:Clinical CohortClinical TrialCollectionControlled TrialDouble-BlindNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images."
-phs002694.v3.p1,c1,Accelerating COVID-19 Therapeutic Interventions and Vaccines 4 ACUTE (ACTIV-4A),2023-09-28,"Name: ACTIV4A_GRU, short name: ACTIV4A_GRU.","This is a randomized, open label, adaptive platform trial to compare the effectiveness of antithrombotic strategies for prevention of adverse outcomes in COVID-19 positive inpatients. Study Design:     Interventional Study Type:Clinical TrialControlled TrialInterventionalRandomizedRandomized Controlled Clinical TrialSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-07 and may not include exact formatting or images."
-phs002710.v1.p1,c1,COVID-19 Outpatient Thrombosis Prevention Trial (ACTIV-4B),2023-09-28,"Name: ACTIV4B_GRU, short name: ACTIV-4B.",An adaptive randomized double-blind placebo-controlled platform trial to compare the effectiveness of anticoagulation with antiplatelet agents and with placebo to prevent thrombotic events in patients diagnosed with COVID-19 who are not admitted to hospital as COVID-19 related symptoms are currently stable. Study Design:     Interventional Study Type:Clinical TrialDouble-BlindInterventionalPlacebo-ControlledRandomizedRandomized Controlled Clinical TrialNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images.
-phs002715.v1.p1,c1,Cleveland Family Study,2023-09-28,"Name: NSRR-CFS_DS-HLBS-IRB-NPU, short name: NSRR-CFS.","The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders.  The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes.  Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance. Study Weblinks: Cleveland Family Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal CohortNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
-phs002752.v1.p1,c1,Clinical-trial of COVID-19 Convalescent Plasma in Outpatients (C3PO),2023-09-28,"Name: C3PO_GRU, short name: C3PO.","The overarching goal of this project is to confirm or refute the role of passive immunization as a safe and efficacious therapy in preventing the progression from mild to severe/critical COVID-19 illness and to understand the immunologic kinetics of anti-SARS-CoV-2 antibodies after passive immunization.The primary objective is to determine the efficacy and safety of a single dose of convalescent plasma (CP) for preventing the progression from mild to severe COVID-19 illness. The secondary objective is to characterize the immunologic response to CP administration.This study will enroll adults presenting to the emergency department (ED) with mild, symptomatic, laboratory-confirmed COVID-19 illness, who are at high risk for progression to severe/critical illness, but who are clinically stable for outpatient management at randomization."
-phs002808.v1.p1,c1,NHLBI TOPMed: Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b),2023-09-28,"Name: Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be, short name: nuMoM2b_GRU-IRB.","Participants from study sites that recruited during the original study funded by NICHD of pregnant people, called nuMoM2b, participated in this study. The nuMoM2b-HHS1 was a prospective observational follow-up study of the nuMoM2b cohort consisting of interval contacts via phone or web every 6 months to about a year, and an in-person visit 2 to 7 years after the end of the nuMoM2b pregnancy including: Demographics Self-administered questionnaires Clinical measurements Lab results An in-home sleep breathing assessment for the subset of participants with at least one valid sleep breathing assessment during nuMoM2b Abstraction of medical records for pregnancies subsequent to nuMoM2b involving self-reported adverse pregnancy outcomes or multiple births Abstraction of medical records of selected cardiovascular risk-related events or procedures reported by participants. The study capitalized on the rich and unique data prospectively collected during nuMoM2b (biomarkers, uterine artery Doppler studies, fetal growth, psychosocial determinants, sleep, and blood pressure) and rigorous definitions of adverse pregnancy outcomes. These data are stored in the NICHD repository DASH (https://dash.nichd.nih.gov/study/226675). A total of 8,838 nuMoM2b participants were targeted for contact during nuMoM2b-HHS and 7,872 participants were reached, of whom 7,003 completed one or more interval contacts. Of these, 5,206 agreed to the visit, and 4,508 attended an in-person visit. Study Weblinks: nuMoM2b website Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-04-25 and may not include exact formatting or images."
-phs003063.v1.p1,c1,COVID-19 Post-hospital Thrombosis Prevention Study (ACTIV-4C),2023-09-28,"Name: COVID-19 Post-hospital Thrombosis Prevention Study (ACTIV-4C), short name: ACTIV4C_GRU.","This study is an adaptive, prospective, randomized trial designed to compare the effectiveness and safety of antithrombotic therapy with no antithrombotic therapy after hospitalization for 48 hours or longer for COVID-19. For Stage 1 of this study, participants will be randomized to either prophylactic anticoagulation or no anticoagulant therapy for 30 days, and then followed for an additional 60 days after the completion of treatment (total duration of follow-up, approximately 90 days). Biobanking of samples for future biomarker and mechanistic studies will be available for centers able to participate and collect samples from eligible participants. Samples will be collected at the time of enrollment and after the completion of 30 days of therapy. Study Weblinks: Clinical Trials Study Design:     Interventional Study Type:Clinical TrialDouble-BlindInterventionalPlacebo-ControlledRandomizedRandomized Controlled Clinical TrialSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-01 and may not include exact formatting or images."
-phs003212.v1.p1,c1,Complement Inhibition Using Eculizumab to Overcome Platelet Transfusion Refractoriness in Patients with Severe Thrombocytopenia (DIR-Eculizumab_GRU),2023-09-28,"Name: Eculizumab_GRU, short name: Eculizumab_GRU.","Platelet transfusion can be a life-saving procedure in preventing or treating serious bleeding in patients who have low and/or dysfunctional platelets. Heavily transfused patients frequently develop human leukocyte antigen (HLA) allo-immunization resulting in platelet transfusion refractoriness and a high risk for life-threatening thrombocytopenia. Data suggest complement activation leading to the destruction of platelets bound by HLA allo-antibodies may play a pathophysiologic role in platelet refractoriness. We conducted a pilot trial to investigate the use of eculizumab to treat platelet transfusion refractoriness in allo-immunized patients with severe thrombocytopenia. We hypothesized that when we treated patients having platelet refractoriness with eculizumab, platelet counts would increase to higher numbers after platelet transfusions, decreasing the risk of bleeding complications associated with having a low platelet count. The response of the treatment was assessed by the corrected platelet count increment (CCI) 10 - 60 min and 18 - 24 h post transfusion, and any requirement for subsequent platelet transfusions following eculizumab. Reference 1 (PMID: 32086819) contains the main results for this trial.  Study Design:     Clinical Trial Study Type:Clinical TrialSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-01 and may not include exact formatting or images."
+Accession,Consent,Study Name,Program,Last modified,Notes,Description
+phs000007.v31.p12,c1,Framingham Cohort,parent,2024-05-09,"Name: FHS_HMB-IRB-MDS_, short name: FHS.","See Grouping of Framingham Phenotype Datasets Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the ""Variables"" tab above.  The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000007 Framingham Cohort.  phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES   The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.   Study Weblinks:   The Framingham Heart Study    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000007.v31.p12 on 2021-03-25 and may not include exact formatting or images."
+phs000007.v31.p12,c2,Framingham Cohort,parent,2024-05-09,"Name: FHS_HMB-IRB-NPU-MDS_, short name: FHS.","See Grouping of Framingham Phenotype Datasets Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the ""Variables"" tab above.  The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000007 Framingham Cohort.  phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES   The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.   Study Weblinks:   The Framingham Heart Study    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000007.v31.p12 on 2021-03-25 and may not include exact formatting or images."
+phs000166.v2.p1,c1,"National Heart, Lung, and Blood Institute SNP Health Association Asthma Resource Project (SHARP)",parent,2024-05-09,"Name: SHARP_ARR_, short name: SHARP.","SNP Health Association Resource (SHARe) Asthma Resource project (SHARP) is conducting a genome-wide analysis in adults and children who have participated in National Heart, Lung, and Blood Institute's clinical research trials on asthma. This includes 1041 children with asthma who participated in the Childhood Asthma Management Program (CAMP), 994 children who participated in one or five clinical trials conducted by the Childhood Asthma Research and Education (CARE) network, and 701 adults who participated in one of six clinical trials conducted by the Asthma Clinical Research Network (ACRN). There are three study types. The longitudinal clinical trials can be subsetted for population-based and/or case-control analyses. Each of the childhood asthma studies has a majority of children participating as part of a parent-child trio. The ACRN (adult) studies are probands alone. Control genotypes will be provided for case-control analyses.   Study Weblinks:   CAMP CARE ACRN    Study Design:       Cross-Sectional    Study Type:  Longitudinal Parent-Offspring Trios Case-Control   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000166.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000179.v6.p2,c1,"Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute",parent,2024-05-09,"Name: COPDGene_HMB_, short name: COPDGene.","Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this top-level study page phs000179 COPDGene_v6 Cohort.  phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno     Study Weblinks:   COPDGene    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000179.v6.p2 on 2021-03-25 and may not include exact formatting or images."
+phs000179.v6.p2,c2,"Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute",parent,2024-05-09,"Name: COPDGene_DS-CS_, short name: COPDGene.","Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" section of this top-level study page phs000179 COPDGene_v6 Cohort.  phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno     Study Weblinks:   COPDGene    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000179.v6.p2 on 2021-03-25 and may not include exact formatting or images."
+phs000200.v12.p3,c1,Women's Health Initiative Clinical Trial and Observational Study,parent,2024-05-09,"Name: WHI_HMB-IRB_, short name: WHI.","The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are:  Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo.   The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to 'WHI dbGaP Cohort Data Release Data Preparation Guide May 2018' for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000200 WHI Cohort.  phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS     Study Weblinks:   Scientific Resources Website: Women's Health Initiative NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Partial Factorial Randomized Double-Blind Placebo-Controlled Cohort Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000200.v12.p3 on 2021-03-25 and may not include exact formatting or images."
+phs000200.v12.p3,c2,Women's Health Initiative Clinical Trial and Observational Study,parent,2024-05-09,"Name: WHI_HMB-IRB-NPU_, short name: WHI.","The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are:  Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo.   The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to 'WHI dbGaP Cohort Data Release Data Preparation Guide May 2018' for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000200 WHI Cohort.  phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS     Study Weblinks:   Scientific Resources Website: Women's Health Initiative NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Partial Factorial Randomized Double-Blind Placebo-Controlled Cohort Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000200.v12.p3 on 2021-03-25 and may not include exact formatting or images."
+phs000209.v13.p3,c1,Multi-Ethnic Study of Atherosclerosis (MESA) Cohort,parent,2024-05-09,"Name: MESA_HMB_, short name: MESA.","MESA The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by four examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. MESA Air The general goal of the Multi-Ethnic Study of Atherosclerosis and Air Pollution ('MESA Air') is to prospectively examine the relation between an individual level assessment of long-term ambient air pollution exposures (including PM2.5 and the progression of subclinical cardiovascular disease in a multi-city, multi-ethnic cohort. MESA Air will also prospectively examine the relationship between an individual level assessment of long-term ambient air pollution exposures and the incidence of cardiovascular disease, including myocardial infarction and cardiovascular death. MESA AIR is funded by a grant from the United States Environmental Protection Agency to the University of Washington and subcontracts from the UW to other participating institutions. MESA Air will assess if ambient air pollution is associated with changes over time in subclinical measures of atherosclerosis and plasma markers of inflammation, oxidative damage, and endothelial activation in a longitudinal data model, adjusting for age, race/ethnicity, socioeconomic status, and specific cardiovascular risk factors (such as diabetes, hypertension, smoking, and diet). The study will similarly assess if the incidence of cardiovascular events is associated with long-term exposure to ambient air pollution, using a proportional hazards model. The study includes refinement of statistical tools, and explores joint/independent effects of acute and long-term pollutant exposure in the occurrence of cardiovascular disease. The MESA Air study is built on the foundation of the ongoing MESA study. The parent MESA Study cohort is located in six geographic areas ('Field Centers') that capture tremendous exposure heterogeneity, comparable to or greater than the variability in locations of prior U.S. cohort studies. In addition to the six Field Centers, the study involves a Coordinating Center, a Central Laboratory, and Reading Centers for Computed Tomography (CT), ultrasound and air pollution data. The cohort for the MESA Air study currently includes 6226 subjects: 5479 enrolled in the parent MESA study; 257 recruited specifically for this study, and 490 recruited from the MESA Family study. The entire MESA Air cohort will be followed over a 10-year project period for the occurrence of cardiovascular disease events. On two occasions over the ten-year study period, 3600 subjects from the MESA Air cohort, residing in nine locales, will undergo computed tomography scanning to assess presence and extent of coronary artery calcification (CAC), and ultrasound of the carotid artery to determine intima-media thickness (IMT). We will also repeatedly assess plasma markers of inflammation, oxidative damage, and endothelial function in 720 subjects. MESA Air adds state-of-the-art air pollution exposure assessment information to the MESA cohort study, and introduces new subjects and outcome measures to achieve our aims. The study will assess long-term individual-level exposure to ambient air pollutants for each subject using community-scale monitoring, outdoor spatial variation, subject proximity to pollution sources, pollutants' infiltration efficiency, and personal time-activity information. The exposure models will be validated using detailed monitoring in a subset of subjects. The MESA Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000209 MESA Cohort.  phs000420 MESA SHARe phs000283 MESA CARe phs000403 MESA ESP Heart-GO     Study Weblinks:   MESA MESA Air    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Family   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000209.v13.p3 on 2021-03-25 and may not include exact formatting or images."
+phs000209.v13.p3,c2,Multi-Ethnic Study of Atherosclerosis (MESA) Cohort,parent,2024-05-09,"Name: MESA_HMB-NPU_, short name: MESA.","MESA The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by four examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. MESA Air The general goal of the Multi-Ethnic Study of Atherosclerosis and Air Pollution ('MESA Air') is to prospectively examine the relation between an individual level assessment of long-term ambient air pollution exposures (including PM2.5 and the progression of subclinical cardiovascular disease in a multi-city, multi-ethnic cohort. MESA Air will also prospectively examine the relationship between an individual level assessment of long-term ambient air pollution exposures and the incidence of cardiovascular disease, including myocardial infarction and cardiovascular death. MESA AIR is funded by a grant from the United States Environmental Protection Agency to the University of Washington and subcontracts from the UW to other participating institutions. MESA Air will assess if ambient air pollution is associated with changes over time in subclinical measures of atherosclerosis and plasma markers of inflammation, oxidative damage, and endothelial activation in a longitudinal data model, adjusting for age, race/ethnicity, socioeconomic status, and specific cardiovascular risk factors (such as diabetes, hypertension, smoking, and diet). The study will similarly assess if the incidence of cardiovascular events is associated with long-term exposure to ambient air pollution, using a proportional hazards model. The study includes refinement of statistical tools, and explores joint/independent effects of acute and long-term pollutant exposure in the occurrence of cardiovascular disease. The MESA Air study is built on the foundation of the ongoing MESA study. The parent MESA Study cohort is located in six geographic areas ('Field Centers') that capture tremendous exposure heterogeneity, comparable to or greater than the variability in locations of prior U.S. cohort studies. In addition to the six Field Centers, the study involves a Coordinating Center, a Central Laboratory, and Reading Centers for Computed Tomography (CT), ultrasound and air pollution data. The cohort for the MESA Air study currently includes 6226 subjects: 5479 enrolled in the parent MESA study; 257 recruited specifically for this study, and 490 recruited from the MESA Family study. The entire MESA Air cohort will be followed over a 10-year project period for the occurrence of cardiovascular disease events. On two occasions over the ten-year study period, 3600 subjects from the MESA Air cohort, residing in nine locales, will undergo computed tomography scanning to assess presence and extent of coronary artery calcification (CAC), and ultrasound of the carotid artery to determine intima-media thickness (IMT). We will also repeatedly assess plasma markers of inflammation, oxidative damage, and endothelial function in 720 subjects. MESA Air adds state-of-the-art air pollution exposure assessment information to the MESA cohort study, and introduces new subjects and outcome measures to achieve our aims. The study will assess long-term individual-level exposure to ambient air pollutants for each subject using community-scale monitoring, outdoor spatial variation, subject proximity to pollution sources, pollutants' infiltration efficiency, and personal time-activity information. The exposure models will be validated using detailed monitoring in a subset of subjects. The MESA Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000209 MESA Cohort.  phs000420 MESA SHARe phs000283 MESA CARe phs000403 MESA ESP Heart-GO     Study Weblinks:   MESA MESA Air    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Family   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000209.v13.p3 on 2021-03-25 and may not include exact formatting or images."
+phs000284.v2.p1,c1,NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe),parent,2024-05-09,"Name: CFS_DS-HLBS-IRB-NPU_, short name: CFS.","The Cleveland Family Study is the largest family-based study of sleep apnea world-wide, consisting of 2284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study was begun in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. NIH renewals provided expansion of the original cohort (including increased minority recruitment) and longitudinal follow-up, with the last exam occurring in February 2006. Index probands (n=275) were recruited from 3 area hospital sleep labs if they had a confirmed diagnosis of sleep apnea and at least 2 first-degree relatives available to be studied. In the first 5 years of the study, neighborhood control probands (n=87) with at least 2 living relatives available for study were selected at random from a list provided by the index family and also studied. All available first degree relatives and spouses of the case and control probands also were recruited. Second-degree relatives, including half-sibs, aunts, uncles and grandparents, were also included if they lived near the first degree relatives (cases or controls), or if the family had been found to have two or more relatives with sleep apnea. Blood was sampled and DNA isolated for participants seen in the last two exam cycles (n=1447). The sample, which is enriched with individuals with sleep apnea, also contains a high prevalence of individuals with sleep apnea-related traits, including: obesity, impaired glucose tolerance, and HTN. Phenotyping data have been collected over 4 exam cycles, each occurring ~every 4 years. The last three exams targeted all subjects who had been studied at earlier exams, as well as new minority families and family members of previously studied probands who had been unavailable at prior exams. Data from one, two, three and four visits are available for 412, 630, 329 and 67, participants, respectively. In the first 3 exams, participants underwent overnight in-home sleep studies, allowing determination of the number and duration of hypopneas and apneas, sleep period, heart rate, and oxygen saturation levels; anthropometry (weight, height, and waist, hip, and neck circumferences); resting blood pressure; spirometry; standardized questionnaire evaluation of symptoms, medications, sleep patterns, quality of life, daytime sleepiness measures and health history; venipuncture and measurement of total and HDL cholesterol. The 4th exam (2001-2006) was designed to collect more detailed measurements of sleep, metabolic and CVD phenotypes and included measurement of state-of-the-art polysomnography, with both collection of blood and measurement of blood pressure before and after sleep, and anthropometry, upper airway assessments, spirometry, exhaled nitric oxide, and ECG performed the morning after the sleep study. Data have been collected by trained research assistants or GCRC nurses following written Manuals of Procedures who were certified following standard approaches for each study procedure. Ongoing data quality, with assessment of within or between individual drift, has been monitored on an ongoing basis, using statistical techniques as well as regular re-certification procedures. Between and within scorer reliabilities for key sleep apnea indices have been excellent, with intra-class correlation coefficients (ICCs) exceeding 0.92 for the apnea-hypopnea index (AHI). Sleep staging, assessed with epoch specific comparisons, also demonstrate excellent reliability for stage identification (kappas>0.82). There has been no evidence of significant time trends-between or within scorers- for the AHI variables. We also have evaluated the night-to-night variability of the AHI and other sleep variables in 91 subjects, with each measurement made 1-3 months apart. There is high night to night consistency for the AHI (ICC: 0.80), the arousal index (0.76), and the % sleep time in slow-wave sleep (0.73). We have demonstrated the comparability of the apnea estimates (AHI) determined from limited channel studies obtained at in-home settings with in full in-laboratory polysomnography. In addition to our published validation study, we more recently compared the AHI in 169 Cleveland Family Study participants undergoing both assessments (in-home and in-laboratory) within one week apart. These showed excellent levels of agreement (ICC=0.83), demonstrating the feasibility of examining data from either in-home or in-laboratory studies for apnea phenotyping. Data collected in the GCRC were obtained, when possible, with comparable, if not identical techniques, as were the same measures collected at prior exams performed in the participants' homes. To address the comparability of data collected over different exams, we calculated the crude age-adjusted correlations ~3 year within individual correlations between measures made in the most recent GCRC exam with measures made in a prior exam and demonstrated excellent levels of agreement for BMI (r=.91); waist circumference (0.91); FVC (0.88); and FEV1 (0.86). As expected due to higher biological and measurement variability, 149 somewhat lower 3-year correlations were demonstrated for SBP (0.56); Diastolic BP (0.48); AHI (0.62); and nocturnal oxygen desaturation (0.60). NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Cooperative Study of Sickle Cell Disease (CSSCD), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data will be created that includes records for approximately 50,000 study participants with approximately 50,000 SNPs from more than 1,200 selected candidate genes. In addition, a genome wide association study using a 1,000K SNP Chip will be conducted on approximately 9,500 African American participants drawn from the 50,000 participants in the nine cohorts. Some relevant CARe publications CARe Study: PMID 20400780 CVD Chip Design: PMID 18974833    Study Weblinks:   Cleveland Family Study    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000284.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000287.v7.p1,c1,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,parent,2024-05-09,"Name: CHS_HMB-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000287.v7.p1,c2,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,parent,2024-05-09,"Name: CHS_HMB-NPU-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000287.v7.p1,c3,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,parent,2024-05-09,"Name: CHS_DS-CVD-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000287.v7.p1,c4,Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older,parent,2024-05-09,"Name: CHS_DS-CVD-NPU-MDS_, short name: CHS.","The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93.  Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health.  Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older.  phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS)   Study Weblinks:   CHS    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000289.v2.p1,c1,National Human Genome Research Institute (NHGRI) GENEVA Genome-Wide Association Study of Venous Thrombosis (GWAS of VTE),parent,2024-05-09,"Name: Mayo_VTE_GRU_, short name: Mayo_VTE.","Overview: Our overall long-term goal is to determine risk factors for the complex (multifactorial) disease, venous thromboembolism (VTE), that will allow physicians to stratify individual patient risk and target VTE prophylaxis to those who would benefit most. In this genome-wide association case-control study (1300 cases and 1300 controls) we hope to identify susceptibility variants for VTE. Mutations within genes encoding for important components of the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways are risk factors for VTE. We hypothesize that other genes within these four pathways or within other pathways also are VTE disease-susceptibility genes. Therefore, we performed a genome wide association (GWA) screen and analysis using the Illumina 660W platform to identify SNPs within 1,300 clinic-based, non-cancer VTE cases primarily from Minnesota and the upper Midwest USA, and 1300 clinic-based, unrelated controls frequency-matched on patient age, gender, myocardial infarction/stroke status and state of residence. This is a subset of a slightly larger candidate gene study using 1500 case-control pairs to identify haplotype-tagging SNPs (ht-SNPs) in a large set of candidate genes (n~750) within the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways. Study Populations. Cases. VTE cases were consecutive Mayo Clinic outpatients with objectively-diagnosed deep vein thrombosis (DVT) and/or pulmonary embolism (PE) residing in the upper Midwest and referred by Mayo Clinic physician to the Mayo Clinic Special Coagulation Laboratory for clinical diagnostic testing to evaluate for an acquired or inherited thrombophilia, or to the Mayo Clinic Thrombophilia Center. Any person contacted to be a control but discovered to have had a VTE was evaluated for inclusion as a case. Cases were primarily residents from Minnesota, Wisconsin, Iowa, Michigan, Illinois, North or South Dakota, Nebraska, Kansas, Missouri and Indiana. A DVT or PE was categorized as objectively diagnosed when (a) confirmed by venography or pulmonary angiography, or pathology examination of thrombus removed at surgery, or (b) if at least one non-invasive test (compression duplex ultrasonography, lung scan, computed tomography scan, magnetic resonance imaging) was positive. A VTE was defined as:  Proximal leg deep vein thrombosis (DVT), which includes the common iliac, internal iliac, external iliac, common femoral, superficial [now termed ""femoral""] femoral, deep femoral [sometimes referred to as ""profunda"" femoral] and/or popliteal veins. (Note: greater and lesser saphenous veins, or other superficial or perforator veins, were not included as proximal or distal leg DVT). Distal leg DVT (or ""isolated calf DVT""), which includes the anterior tibial, posterior tibial and/or peroneal veins. (Note: gastrocnemius, soleal and/or sural [e.g., ""deep muscular veins"" of the calf] vein thrombosis was not included as distal leg DVT). Arm DVT, which includes the axillary, subclavian and/or innominate (brachiocephalic) veins. (Note: jugular [internal or external], cephalic and brachial vein thrombosis was not included in ""arm DVT""). Hepatic, portal, splenic, superior or inferior mesenteric, and/or renal vein thrombosis. (Note: ovarian, testicular, peri-prostatic and/or pelvic vein thrombosis was not included). Cerebral vein thrombosis (includes cerebral or dural sinus or vein, saggital sinus or vein, and/or transverse sinus or vein thrombosis). Inferior vena cava (IVC) thrombosis Superior vena cava (SVC) thrombosis Pulmonary embolism   Patients with VTE related to active cancer, antiphospholipid syndrome, inflammatory bowel disease, vasculitis, a rheumatoid or other autoimmune disorder, a vascular anomaly (e.g., Klippel-Trénaunay syndrome, etc.), heparin-induced thrombocytopenia, or a mechanical cause for DVT (e.g., arm DVT or SVC thrombosis related to a central venous catheter or transvenous pacemaker, portal and/or splenic vein thrombosis related to liver cirrhosis, IVC thrombosis related to retroperitoneal fibrosis, etc.), with hemodialysis arteriovenous fistula thrombosis, or with prior liver or bone marrow transplantation were excluded.  Controls. A Mayo Clinic outpatient control group was prospectively recruited for this study. Controls were frequency-matched on the age group (18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+ years), sex, myocardial infarction/stroke status, and state of residence distribution of the cases. We selected clinic-based controls using a controls' database of persons undergoing general medical examinations in the Mayo Clinic Departments of General Internal Medicine or Primary Care Internal Medicine. Additionally persons undergoing evaluation at the Mayo Clinic Sports Medicine Center, and the Department of Family Medicine were screened for inclusion as controls. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to venous thrombosis through large-scale genome-wide association studies of 1,300 clinic-based, VTE cases and 1300 clinic-based, unrelated controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000289.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000422.v1.p1,c1,NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Asthma): Genetic variants affecting susceptibility and severity,parent,2024-05-09,"Name: Asthma_GRU_, short name: Asthma.","The NHLBI ""Grand Opportunity"" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the ""exome"") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: 19892860). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (phs000355, Illumina platform).   Study Design:       Case Set    Study Type:  Case Set   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000422.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000571.v6.p2,c1,Congenital Heart Disease Genetic Network Study,PCGC,2024-05-09,"Name: CHD-GENES_HMB, short name: CHD-GENES_HMB.","This substudy phs000571 PCGC contains whole exome sequences, targeted sequences, and SNP array data. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194.  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Study Weblinks:Bench to Bassinet Program Study Design:     Prospective Longitudinal Cohort Study Type:Parent-Offspring TriosCohortdbGaP estimated ancestry usingGRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-10-11 and may not include exact formatting or images."
+phs000703.v1.p1,c1,CATHeterization GENetics (CATHGEN),parent,2024-05-09,"Name: CATHGEN_DS-CVD-IRB_, short name: CATHGEN.","The CATHGEN biorepository consists of biological samples collected on 9334 sequential consenting individuals undergoing cardiac catheterization at Duke University Medical Center between 2001 and 2010 inclusive. The Institutional Review Board informed consent allowed for 50 mL of blood to be collected from fasting patients through the femoral arterial sheath during the catheterization procedure. Three 7.5 mL EDTA tubes for DNA extraction are stored at -80°C. The Duke Database for Cardiovascular Disease (DDCD) provides the bulk of the clinical data used for analysis. Follow-up includes mortality information gleaned from the National Death Index and Social Security Death Index plus follow-up phone calls and written questionnaires regarding MI, stroke, re-hospitalization, coronary re-vascularization procedures, smoking, exercise, and medication use.   Study Weblinks:   CATHGEN    Study Design:       Cross-Sectional    Study Type:  Longitudinal   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000703.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000784.v3.p1,c1,Genetic Epidemiology Network of Salt Sensitivity (GenSalt),parent,2024-05-09,"Name: GenSalt_DS-HCR-IRB_, short name: GenSal.",The GenSalt study is aimed at identifying novel genes which interact with the effect of dietary sodium and potassium intake or cold pressor on blood pressure.   Study Design:       Interventional    Study Type:  Family Interventional     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000784.v3.p1 on 2021-03-25 and may not include exact formatting or images.
+phs000810.v1.p1,c1,Hispanic Community Health Study /Study of Latinos (HCHS/SOL),parent,2024-05-09,"Name: HCHS-SOL_HMB-NPU_, short name: HCHS-SOL.","The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" box located on the right hand side of this top-level study page phs000810 HCHS SOL Cohort.  phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)     Study Weblinks:   Hispanic Community Health Study / Study of Latinos    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000810.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000810.v1.p1,c2,Hispanic Community Health Study /Study of Latinos (HCHS/SOL),parent,2024-05-09,"Name: HCHS-SOL_HMB_, short name: HCHS-SOL.","The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the ""Sub-studies"" box located on the right hand side of this top-level study page phs000810 HCHS SOL Cohort.  phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)     Study Weblinks:   Hispanic Community Health Study / Study of Latinos    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000810.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000820.v1.p1,c1,The Cleveland Clinic Foundation's Lone Atrial Fibrillation GWAS Study,parent,2024-05-09,"Name: CCAF_GRU_, short name: CCAF.",Blood samples were taken from patients who have lone atrial fibrillation. DNA samples were processed with Illumina Hap550 and Hap 610 chips.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000820.v1.p1 on 2021-03-25 and may not include exact formatting or images.
+phs000914.v1.p1,c1,Genome-Wide Association Study of Adiposity in Samoans,parent,2024-05-09,"Name: SAS_GRU-IRB-PUB-COL-NPU-GSO_, short name: SAS.","The research goal of this study is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Population     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000914.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000920.v5.p2,c2,NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II),topmed,2024-05-09,"Name: NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II), short name: GALAII_DS-LD-IRB-COL.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  """"TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180. Study Weblinks:Study Populations and Research Staff Study Design:     Case Set Study Type:Case SetdbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000920 on 2021-03-17 and may not include exact formatting or images."""
+phs000921.v4.p1,c2,"NHLBI TOPMed: Study of African Americans, Asthma, Genes and Environment (SAGE)",topmed,2024-05-09,"Name: SAGE_DS-LD-IRB-COL, short name: SAGE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a parallel case-control pharmacogenetic study of bronchodilator drug response among African American children with and without asthma. Each participant had spirometry measured using the KoKo PFT System. Asthmatic participants were administered with 4 puffs of HFA Albuterol. Healthy participants were given a baseline spirometry test. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants were 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications.   Study Weblinks:   Study Populations and Research Staff    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000921.v4.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000946.v5.p1,c1,NHLBI TOPMed: Boston Early-Onset COPD Study (EOCOPD),topmed,2024-05-09,"Name: NHLBI TOPMed: Boston Early-Onset COPD Study (EOCOPD), short name: EOCOPD_DS-CS-RD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project collected a set of extended pedigrees ascertained through subjects with severe, early-onset COPD. This study has enrolled subjects with severe COPD (forced expiratory volume in one second (FEV1) < 40% predicted) at an early age (< 53 years) without alpha-1 antitrypsin deficiency (a known Mendelian risk factor for COPD). Extended pedigrees are enrolled, primarily in New England, although some more geographically distant subjects have been included. This study has been used for epidemiological studies, familial aggregation analysis, linkage analysis, and candidate gene association analysis. Approximately 80 of the severe, early-onset COPD probands will undergo whole genome sequencing in this project with sequencing data available through dbGaP. Study Weblinks: Boston COPD Study Design:     Family/Twin/Trios Study Type:Pedigree Whole Genome Sequencing dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000951.v5.p4,c1,NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene),topmed,2024-05-09,"Name: NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene), short name: COPDGene_HMB.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  """"TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are:  Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed.  Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179. Study Weblinks:COPDGenephs000179 Study Design:     Case-Control Study Type:Case-ControldbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000951 on 2021-03-17 and may not include exact formatting or images."""
+phs000951.v5.p4,c2,NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene),topmed,2024-05-09,"Name: NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene), short name: COPDGene_DS-CS-RD.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  """"TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are:  Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed.  Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179. Study Weblinks:COPDGenephs000179 Study Design:     Case-Control Study Type:Case-ControldbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000951 on 2021-03-17 and may not include exact formatting or images."""
+phs000954.v4.p2,c1,NHLBI TOPMed: The Cleveland Family Study (CFS),topmed,2024-05-09,"Name: NHLBI TOPMed: The Cleveland Family Study (CFS), short name: CFS_DS-HLBS-IRB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Cleveland Family Study (CFS) is one cohort involved in the WGS project. The CFS was designed to provide fundamental epidemiological data on genetic and non-genetic risk factors for sleep disordered breathing (SDB). In brief, the CFS is a family-based study that enrolled a total of 2284 individuals from 361 families between 1990 and 2006. The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first degree relatives, spouses and available second degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first degree relatives. Each exam, occurring at approximately 4 year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in the participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. The GCRC exam (n=735 selected individuals) included more comprehensive phenotype data on a focused subsample of the larger cohort, to permit linking SDB phenotypes with cardio-metabolic phenotypes, with an interest in identifying genetic loci that are associated with these related phenotypes. In this last round of data collection, a subset of 735 individuals was selected based on expected genetic informativity by choosing pedigrees where siblings had extremes of the apnea hypopnea index (AHI). Participants underwent detailed phenotyping including laboratory polysomnography (PSG), ECG, spirometry, nasal and oral acoustic reflectometry, vigilance testing, and blood and urine collection before and after sleep and after an oral glucose tolerance test. A wide range of biochemical measures of inflammation and metabolism were assayed by a Core Laboratory at the University of Vermont. 994 individuals were sequenced as part of TOPMed Phase 1, including 507 African-Americans and 487 European-Americans. Among the sequenced individuals, 156 were probands with diagnosed sleep apnea, an additional 706 were members of families with probands, and 132 were from neighborhood control families.  298 individuals were sequenced as part of TOPMed Phase 3.5, including 169 African-Americans and 129 European-Americans. Among the newly sequenced individuals, 33 were probands with diagnosed sleep apnea, an additional 214 were members of families with probands, and 51 were from neighborhood control families. Please note: Phenotype and pedigree data are available through ""NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)"", phs000284.  Study Weblinks: Cleveland Family Study (CFS) Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000956.v5.p1,c2,NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish (Amish),topmed,2024-05-09,"Name: NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish (Amish), short name: Amish_HMB-IRB-MDS.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Amish Complex Disease Research Program includes a set of large community-based studies focused largely on cardiometabolic health carried out in the Old Order Amish (OOA) community of Lancaster, Pennsylvania (http://medschool.umaryland.edu/endocrinology/amish/research-program.asp). The OOA population of Lancaster County, PA immigrated to the Colonies from Western Europe in the early 1700's. There are now over 30,000 OOA individuals in the Lancaster area, nearly all of whom can trace their ancestry back 12-14 generations to approximately 700 founders. Investigators at the University of Maryland School of Medicine have been studying the genetic determinants of cardiometabolic health in this population since 1993. To date, over 7,000 Amish adults have participated in one or more of our studies. Due to their ancestral history, the OOA may be enriched for rare variants that arose in the population from a single founder (or small number of founders) and propagated through genetic drift. Many of these variants have large effect sizes and identifying them can lead to new biological insights about health and disease. The parent study for this WGS project provides one (of multiple) examples. In our parent study, we identified through a genome-wide association analysis a haplotype that was highly enriched in the OOA that is associated with very high LDL-cholesterol levels. At the present time, the identity of the causative SNP - and even the implicated gene - is not known because the associated haplotype contains numerous genes, none of which are obvious lipid candidate genes. A major goal of the WGS that will be obtained through the NHLBI TOPMed Consortium will be to identify functional variants that underlie some of the large effect associations observed in this unique population. Study Weblinks: University of Maryland School of Medicine - Amish Studies Study Design:     Family/Twin/Trios Study Type:Family dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 1123    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs000964.v5.p1,c1,NHLBI TOPMed: The Jackson Heart Study (JHS),topmed,2024-05-09,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_HMB-IRB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000964.v5.p1,c2,NHLBI TOPMed: The Jackson Heart Study (JHS),topmed,2024-05-09,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_DS-FDO-IRB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000964.v5.p1,c3,NHLBI TOPMed: The Jackson Heart Study (JHS),topmed,2024-05-09,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_HMB-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000964.v5.p1,c4,NHLBI TOPMed: The Jackson Heart Study (JHS),topmed,2024-05-09,"Name: NHLBI TOPMed: The Jackson Heart Study (JHS), short name: JHS_DS-FDO-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an ""opt out"" to an ""opt in"" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1  1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000972.v4.p1,c1,NHLBI TOPMed: Genome-Wide Association Study of Adiposity in Samoans,topmed,2024-05-09,"Name: SAS_GRU-IRB-PUB-COL-NPU-GSO, short name: SAS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The individuals sequenced here represent a small subset of the parent study (described below) and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing. The research goal of the parent study (dbGaP ID phs000914) is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Population     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000972.v4.p1 on 2021-03-25 and may not include exact formatting or images."
+phs000974.v5.p3,c1,NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS),topmed,2024-05-09,"Name: NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS), short name: FHS_HMB-IRB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"" and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 subjects and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007. Study Weblinks:Framingham Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:CohortdbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000974 on 2021-03-17 and may not include exact formatting or images."
+phs000974.v5.p3,c2,NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS),topmed,2024-05-09,"Name: NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study (FHS), short name: FHS_HMB-IRB-NPU-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"" and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 subjects and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007. Study Weblinks:Framingham Heart Study Study Design:     Prospective Longitudinal Cohort Study Type:CohortdbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs000974 on 2021-03-17 and may not include exact formatting or images."
+phs000988.v5.p1,c1,NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica (CRA),topmed,2024-05-09,"Name: NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica (CRA), short name: CRA_DS-ASTHMA-IRB-MDS-RD.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.This administrative supplement to the project, """"The Genetic Epidemiology of Asthma in Costa Rica"""" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set. Study Design:     Family/Twin/Trios Study Type:Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 4230    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs000993.v5.p2,c1,NHLBI TOPMed: Heart and Vascular Health Study (HVH),topmed,2024-05-09,"Name: NHLBI TOPMed: Heart and Vascular Health Study (HVH), short name: HVH_HMB-IRB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000993.v5.p2,c2,NHLBI TOPMed: Heart and Vascular Health Study (HVH)),topmed,2024-05-09,"Name: NHLBI TOPMed: Heart and Vascular Health Study (HVH)), short name: HVH_DS-CVD-IRB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs000997.v5.p2,c1,NHLBI TOPMed - NHGRI CCDG: The Vanderbilt AF Ablation Registry,topmed,2024-05-09,"Name: NHLBI TOPMed - NHGRI CCDG: The Vanderbilt AF Ablation Registry, short name: VAFAR_HMB-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Vanderbilt Atrial Fibrillation Ablation Registry (VAFAR) was founded in 2011. Patients with AF referred for AF ablation are prospectively enrolled. A detailed clinical history is recorded, along with imaging data (cardiac MRI or CT). Blood samples are obtained for DNA extraction at the time of ablation. Details of the ablation procedure are recorded. Patients are longitudinally followed to monitor for AF recurrence. VAFAR contributed 171 samples submitted to dbGaP for WGS: 115 were from male subjects, of which 113 were white/non-Hispanic and 2 were Hispanic; 56 were from females, of which all 56 were white/non-Hispanic. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001001.v1.p1,c1,Massachusetts General Hospital (MGH) Atrial Fibrillation Study,parent,2024-05-09,"Name: MGH_AF_HMB-IRB_, short name: MGH_AF.","The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study.  phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing     Study Design:       Case Set    Study Type:  Case Set   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001001.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001001.v1.p1,c2,Massachusetts General Hospital (MGH) Atrial Fibrillation Study,parent,2024-05-09,"Name: MGH_AF_DS-AF-IRB-RD_, short name: MGH_AF.","The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study.  phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing     Study Design:       Case Set    Study Type:  Case Set   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001001.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001012.v1.p1,c1,The Diabetes Heart Study (DHS),parent,2024-05-09,"Name: DHS_DS-DRC-IRB_, short name: DHS.","The Diabetes Heart Study is a family based study enriched for type 2 diabetes (T2D). The cohort included 1220 self-reported European Americans from 475 families (Bowden et al 2010 Review of Diabetic Studies 7:188-201: PMID: 21409311; Bowden et al 2008 Annals of Human Genetics 72:598-601 PMID: 18460048) and included siblings concordant for T2D; where possible unaffected siblings were also recruited. The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery and abdominal aorta all determined from non-contrast computed tomography scans.    Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001012.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001013.v3.p2,c1,Heart and Vascular Health Study (HVH),parent,2024-05-09,"Name: HVH_HMB-IRB-MDS_, short name: HVH.","Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001013.v3.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001013.v3.p2,c2,Heart and Vascular Health Study (HVH),parent,2024-05-09,"Name: HVH_DS-CVD-IRB-MDS_, short name: HVH.","Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001013.v3.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001024.v4.p1,c1,NHLBI TOPMed: Partners HealthCare Biobank,topmed,2024-05-09,"Name: PARTNERS_HMB, short name: PARTNERS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Atrial Fibrillation Genetics Consortium (AFGen) was organized to identify common and rare genetic variation associated with atrial fibrillation risk. In the current study, we have performed whole genome sequencing in cases with early-onset atrial fibrillation. Samples in this study were enrolled as a part of the Partners HealthCare Biobank. Cases with early-onset atrial fibrillation were identified from the Biobank (defined as atrial fibrillation onset prior to 61 years and in the absence of structural heart disease).    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs001024 on 2021-03-17 and may not include exact formatting or images."
+phs001032.v6.p2,c1,NHLBI TOPMed: Heart and Vascular Health Study (HVH),topmed,2024-05-09,"Name: NHLBI TOPMed: Heart and Vascular Health Study (HVH), short name: VU_AF_GRU-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Vanderbilt Atrial Fibrillation (AF) Registry was founded in 2001. Patients with AF and family members are prospectively enrolled. At enrollment a detailed past medical history is obtained along with an AF symptom severity assessment. Blood samples are obtained for DNA extraction. Patients are followed longitudinally along with serial collection of AF symptom severity assessments. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001040.v4.p1,c1,NHLBI TOPMed: Novel Risk Factors for the Development of Atrial Fibrillation in Women,topmed,2024-05-09,"Name: WGHS_HMB, short name: WGHS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Women's Genome Health Study (WGHS) is a prospective cohort comprised of over 25,000 initially healthy female health professionals enrolled in the Women's Health Study, which began in 1992-1994. All participants in WGHS provided baseline blood samples and extensive survey data. Women who reported atrial fibrillation during the course of the study were asked to report diagnoses of AF at baseline, 48 months, and then annually thereafter. Participants enrolled in the continued observational follow-up who reported an incident AF event on at least one yearly questionnaire were sent an additional questionnaire to confirm the episode and to collect additional information. They were also asked for permission to review their medical records, particularly available ECGs, rhythm strips, 24-hour ECGs, and information on cardiac structure and function. For all deceased participants who reported AF during the trial and extended follow-up period, family members were contacted to obtain consent and additional relevant information. An end-point committee of physicians reviewed medical records for reported events according to predefined criteria. An incident AF event was confirmed if there was ECG evidence of AF or if a medical report clearly indicated a personal history of AF. The earliest date in the medical records when documentation was believed to have occurred was set as the date of onset of AF.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001040.v4.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001062.v4.p2,c1,NHLBI TOPMed - NHGRI CCDG: Massachusetts General Hospital (MGH) Atrial Fibrillation Study,topmed,2024-05-09,"Name: MGH_AF_HMB-IRB, short name: MGH_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. For the TOPMed WGS project only early-onset atrial fibrillation cases were sequenced. Early-onset atrial fibrillation was defined as an age of onset prior to 66 years of age. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs001001.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001062.v4.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001062.v4.p2,c2,NHLBI TOPMed - NHGRI CCDG: Massachusetts General Hospital (MGH) Atrial Fibrillation Study,topmed,2024-05-09,"Name: MGH_AF_DS-AF-IRB-RD, short name: MGH_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. For the TOPMed WGS project only early-onset atrial fibrillation cases were sequenced. Early-onset atrial fibrillation was defined as an age of onset prior to 66 years of age. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs001001.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs001062 on 2021-03-17 and may not include exact formatting or images."
+phs001074.v1.p1,c2,GeneSTAR (Genetic Study of Atherosclerosis Risk) NextGen Consortium: Functional Genomics of Platelet Aggregation Using iPS and Derived Megakaryocytes,parent,2024-05-09,"Name: GeneSTAR_DS-CVD-IRB-NPU-RD_, short name: GeneSTAR.","The causal mechanisms of common diseases and their therapies have been only marginally illuminated by genetic variants identified in genome wide association studies (GWAS) utilizing single nucleotide polymorphism (SNPs). Platelet activation pathways reflecting hemostasis and thrombosis are the underlying substrate for many cardiovascular diseases and related acute events. To overcome GWAS limitations, genomic studies are needed that integrate molecular surrogates for platelet-related phenotypes assayed in cell-based models derived from individuals of known genotypes and phenotypes. In our GWAS study of native platelet aggregation phenotypes and aggregation in response to low dose aspirin in 2200 subjects (GeneSTAR, Genetic Study of Aspirin Responsiveness), important genome wide ""signals"" (p<5x10-8) associated with native platelet aggregation and important ""signals"" associated with platelet responsiveness to aspirin were identified and replicated. Although we are currently performing functional genomics studies to elucidate our most promising findings in known genes (PEAR1, MET, PIKC3G), most ""signals"" occurred in intergenic regions or in introns. Mechanistic interpretation is limited by uncertainty as to which gene(s) are up- or down-regulated in the presence of most SNP modifications. In this 3 phase proposal, we will (1) create pluripotent stem cells (iPS) from peripheral blood mononuclear cells, and then differentiate these stem cells into megakaryocytes (2) develop an efficient strategy to produce iPS and megakaryocytes using a novel pooling method, and (3) produce iPS and megakaryocytes from 250 subjects in GeneSTAR (European Americans and African Americans), selected based on specific hypotheses derived from GWAS signals in native and post aspirin platelet function; characterize genetic mRNA transcripts using a comprehensive Affymetrix array; measure protein expression for transcripts of interest using mass spectrometry; examine mRNA and protein expression patterns for each GWAS signal to determine the functional pathway(s) involved in native platelet phenotypes; and examine the functional genomics of variations in responsiveness to aspirin using our prior genotyped and phenotyped population. Precise information about the exact functional processes in megakaryocytes and platelets may lead to innovative and tailored approaches to risk assessment and novel therapeutic targets to prevent first and recurrent cardiovascular and related thrombotic events.   Study Weblinks:   GeneSTAR Research Center, Genetic Studies of Atherosclerosis Risk    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Cohort Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001074.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001143.v4.p1,c1,NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados,topmed,2024-05-09,"Name: NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados, short name: BAGS_GRU-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Asthma is a complex disease where the interplay between genetic factors and environmental exposures influences susceptibility and disease prognosis. Asthmatics of African descent tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry. The baseline prevalence of asthma in Barbados is high (~20%), and from admixture analyses, we have determined that the proportion of African ancestry among Barbadian founders is similar to U.S. African Americans, rendering this a unique population to disentangle the genetic basis for asthma disparities among African ancestry populations in general. We therefore performed whole genome sequencing on 1,100 individuals from the Barbados Genetics of Asthma Study (BAGS), in order to generate additional discovery of rare and structural variants that may control risk to asthma. Study Design:     Family/Twin/Trios Study Type:Family dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001180.v2.p1,c2,Genes-Environments and Admixture in Latino Asthmatics (GALA II) Study,parent,2024-05-09,"Name: GALAII_DS-LD-IRB-COL_, short name: GALAII.","A case-control pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. The GALAII Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" box located on the right hand side of this top-level study page phs001180 GALAII Study.  phs001274phs001274 GALAII GWAS     Study Weblinks:   Asthma Collaboratory    Study Design:       Case-Control    Study Type:  Case-Control   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001180.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001189.v4.p1,c1,NHLBI TOPMed: Cleveland Clinic Atrial Fibrillation (CCAF) Study,topmed,2024-05-09,"Name: NHLBI TOPMed: Cleveland Clinic Atrial Fibrillation (CCAF) Study, short name: CCAF_AF_GRU-IRB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Cleveland Clinic Atrial Fibrillation Study consists of clinical and genetic data of patients with atrial fibrillation and control cohorts from the Cleveland Clinic CV/Arrhythmia Biobank, including the Cleveland Clinic Lone Atrial Fibrillation GeneBank. The Cleveland Clinic Lone AF GeneBank Study has enrolled patients with lone AF, defined as AF in the absence of significant structural heart disease. The CV/Arrhythmia Biobank has also enrolled participants with non-lone atrial fibrillation. All patients provided written informed consent. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001194.v2.p2,c1,"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study",parent,2024-05-09,"Name: PCGC_HMB_, short name: PCGC.","Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. The PCGC Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001194 PCGC Cohort.  phs000571 The Pediatric Cardiac Genetics Consortium (PCGC)   The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.   Study Weblinks:   From Bench to Bassinet: CHD Genes    Study Design:       Prospective Longitudinal Cohort    Study Type:  Parent-Offspring Trios Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001194.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001194.v2.p2,c2,"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study",parent,2024-05-09,"Name: PCGC_DS-CHD_, short name: PCGC.","Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. The PCGC Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the ""Substudies"" section of this top-level study page phs001194 PCGC Cohort.  phs000571 The Pediatric Cardiac Genetics Consortium (PCGC)   The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.   Study Weblinks:   From Bench to Bassinet: CHD Genes    Study Design:       Prospective Longitudinal Cohort    Study Type:  Parent-Offspring Trios Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001194.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001207.v2.p1,c1,NHLBI TOPMed: African American Sarcoidosis Genetics Resource,topmed,2024-05-09,"Name: Sarcoidosis_DS-SAR-IRB, short name: Sarcoidosis.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study aims to comprehensively interrogate the genomes of African American sarcoidosis families. Sarcoidosis is characterized by a hyperimmune response resulting in granuloma formation in multiple organs. It affects African Americans (AAs) more frequently and more severely than whites. While previous linkage, admixture, candidate gene and genome-wide association (GWA) studies show statistically compelling effects, causal variants are still unknown and much of sarcoidosis heritability is yet to be explained. This ""missing"" heritability likely includes effects of both common (minor allele frequency (MAF)>5%) and rare variants (MAF<5%), since, in AAs, the former are inadequately represented and the latter are completely unexplored by commercial genotyping arrays. These facts, coupled with the availability of next-generation sequencing compel us to perform an exhaustive search for genetic variants that form the basis of sarcoidosis. The data generated are certain to identify candidate causal variants, provide fundamental insight for functional studies and lead to important new hypotheses of inflammation resulting in new treatments in not only sarcoidosis but other inflammatory diseases as well.   Study Design:       Family/Twin/Trios    Study Type:  Family Affected Sib Pairs     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001207.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001211.v4.p2,c1,NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC),topmed,2024-05-09,"Name: NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC), short name: ARIC_HMB-IRB.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  """"TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative. Study Design:     Case-Control Study Type:Case-ControldbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs001211 on 2021-03-17 and may not include exact formatting or images."""
+phs001211.v4.p2,c2,NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC),topmed,2024-05-09,"Name: NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC), short name: ARIC_DS-CVD-IRB.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents,  """"TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative. Study Design:     Case-Control Study Type:Case-ControldbGaP estimated ancestry usingGRAF-popNumber of study subjects that have individual-level data available through Authorized Access:NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/phs001211 on 2021-03-17 and may not include exact formatting or images."""
+phs001215.v3.p2,c1,NHLBI TOPMed: San Antonio Family Heart Study (SAFHS),topmed,2024-05-09,"Name: SAFHS_DS-DHD-IRB-PUB-MDS-RD, short name: SAFHS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The San Antonio Family Heart Study (SAFHS) is a complex pedigree-based mixed longitudinal study designed to identify low frequency or rare variants influencing susceptibility to cardiovascular disease, using whole genome sequence (WGS) information from 2,590 individuals in large Mexican American pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for CVD, as well as to find novel low frequency or rare variants influencing susceptibility to CVD. WGS of the SAFHS cohort has been obtained through three efforts. Approximately 540 WGS were performed commercially at 50X by Complete Genomics, Inc (CGI) as part of the large T2D-GENES Project. The phenotype and genotype data for this group is available at dbGaP under accession number phs000462. An additional ~900 WGS at 30X were obtained through Illumina as part of the R01HL113322 ""Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk"" project. Finally, ~1,150 WGS at 30X WGS were obtained through Illumina funded by a supplement as part of the NHLBI's TOPMed program. Extensive phenotype data are provided for sequenced individuals primarily obtained from the P01HL45522 ""Genetics of Atherosclerosis in Mexican Americans"" for adults and R01HD049051 for children in these same families. Phenotype information was collected between 1991 and 2016. For this dataset, the SAFHS appellation represents an amalgamation of the original SAFHS participants and an expansion that reexamined families previously recruited for the San Antonio Family Diabetes Study (R01DK042273) and the San Antonio Family Gall Bladder Study (R01DK053889). Due to this substantial examination history, participants may have information from up to five visits. The clinical variables reported are coordinated with TOPMed and include major adverse cardiac events (MACE), T2D status and age at diagnosis, glycemic traits (fasting glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides). Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. PBMC derived gene expression assays for a subset of ~1,060 individuals obtained using the Illumina Sentrix-6 chip is also available from the baseline examination. The WGS data have been jointly called and are available in the current TOPMed accession (phs001215).   Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001215.v3.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001217.v2.p1,c1,NHLBI TOPMed: Genetic Epidemiology Network of Salt Sensitivity (GenSalt),topmed,2024-05-09,"Name: GenSalt_DS-HCR-IRB, short name: GenSalt.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The GenSalt study aims to identify genes which interact with dietary sodium and potassium intake to influence blood pressure in Han Chinese participants from rural north China. Whole genome sequencing will be conducted among 1,860 participants of the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) Study. We will work in collaboration with participating TOPMed studies to identify novel common, low-frequency and rare variants associated with an array of cardiometabolic phenotypes. In addition, we will explore the relation of low-frequency and rare variants with salt-sensitivity among GenSalt study participants.   Study Design:       Family/Twin/Trios    Study Type:  Parent-Offspring Trios Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001217.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001218.v2.p1,c2,NHLBI TOPMed: Genetic Study of Atherosclerosis Risk (GeneSTAR),topmed,2024-05-09,"Name: GeneSTAR_DS-CVD-IRB-NPU-MDS, short name: GeneSTAR.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. GeneSTAR began in 1982 as the Johns Hopkins Sibling and Family Heart Study, a prospective longitudinal family-based study conducted originally in healthy adult siblings of people with documented early onset coronary disease under 60 years of age. Commencing in 2003, the siblings, their offspring, and the coparent of the offspring participated in a 2 week trial of aspirin 81 mg/day with pre and post ex vivo platelet function assessed using multiple agonists in whole blood and platelet rich plasma. Extensive additional cardiovascular testing and risk assessment was done at baseline and serially. Follow-up was carried out to determine incident cardiovascular disease, stroke, peripheral arterial disease, diabetes, cancer, and related comorbidities, from 5 to 30 years after study entry. The goal of several additional phenotyping and interventional substudies has been to discover and amplify understanding of the mechanisms of atherogenic vascular diseases and attendant comorbidities.   Study Weblinks:   GeneSTAR    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal Cohort Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001218.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001237.v2.p1,c1,NHLBI TOPMed: Women's Health Initiative (WHI),topmed,2024-05-09,"Name: WHI_HMB-IRB, short name: WHI.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200.   Study Weblinks:   WHI NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001237.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001237.v2.p1,c2,NHLBI TOPMed: Women's Health Initiative (WHI),topmed,2024-05-09,"Name: WHI_HMB-IRB-NPU, short name: WHI.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200.   Study Weblinks:   WHI NHLBI Women's Health Initiative    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001237.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001238.v2.p1,c1,Genetic Epidemiology Network of Arteriopathy (GENOA),parent,2024-05-09,"Name: GENOA_DS-ASC-RF-NPU_, short name: GENOA.","The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals.   Study Weblinks:   FBPP STAMPEED    Study Design:       Prospective Longitudinal Cohort    Study Type:  Sibling Cohort   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001238.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001252.v1.p1,c1,Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE),parent,2024-05-09,"Name: ECLIPSE_DS-COPD-RD_, short name: ECLIPSE.","ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo, European Respiratory Journal 2008; 31: 869). Inclusion criteria included age 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% predicted and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, NEJM 2010; 363: 1128) and lung function decline in COPD (Vestbo, NEJM 2011; 365: 1184). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers(Faner, Thorax 2014; 69: 666). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects.   Study Weblinks:   ECLIPSE    Study Design:       Case-Control    Study Type:  Case-Control Longitudinal Cohort Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001252.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001293.v2.p1,c1,NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy,topmed,2024-05-09,"Name: HyperGEN_GRU-IRB, short name: HyperGEN.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study.   Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001293.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001293.v2.p1,c2,NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy,topmed,2024-05-09,"Name: HyperGEN_DS-CVD-IRB-RD, short name: HyperGEN.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study.   Study Design:       Family/Twin/Trios    Study Type:  Family     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001293.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001345.v3.p1,c1,NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA),topmed,2024-05-09,"Name: NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA), short name: GENOA_DS-ASC-RF-NPU.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238. Study Weblinks: FBPPSTAMPEED Study Design:     Family/Twin/Trios Study Type:CohortSibling Cohort dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 1854    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs001359.v3.p1,c1,NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate (GOLDN),topmed,2024-05-09,"Name: NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate (GOLDN), short name: GOLDN_DS-CVD-IRB.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741. Study Weblinks: GOLDN Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 1069    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs001368.v3.p2,c1,NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study,topmed,2024-05-09,"Name: NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study, short name: CHS_HMB-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE). Study Weblinks: CHS-NHLBI Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001368.v3.p2,c2,NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study,topmed,2024-05-09,"Name: NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study, short name: CHS_HMB-NPU-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE). Study Weblinks: CHS-NHLBI Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001368.v3.p2,c4,NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study,topmed,2024-05-09,"Name: NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study, short name: CHS_DS-CVD-NPU-MDS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE). Study Weblinks: CHS-NHLBI Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001387.v2.p1,c3,NHLBI TOPMed: Rare Variants for Hypertension in Taiwan Chinese (THRV),topmed,2024-05-09,"Name: THRV_DS-CVD-IRB-COL-NPU-RD, short name: THRV.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The THRV-TOPMed study consists of three cohorts: The SAPPHIRe Family cohort (N=1,271), TSGH (Tri-Service General Hospital, a hospital-based cohort, N=160), and TCVGH (Taichung Veterans General Hospital, another hospital-based cohort, N=922), all based in Taiwan. 1,271 subjects were previously recruited as part of the NHLBI-sponsored SAPPHIRe Network (which is part of the Family Blood Pressure Program, FBPP). The SAPPHIRe families were recruited to have two or more hypertensive sibs, some families also with one normotensive/hypotensive sib. The two Hospital-based cohorts (TSGH and TCVGH) both recruited unrelated subjects with different recruitment criteria (matched with SAPPHIRe subjects for age, sex, and BMI category).   Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001387.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001395.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Hispanic Community Health Study/Study of Latinos (HCHS/SOL),topmed,2024-05-09,"Name: HCHS-SOL_HMB-NPU, short name: HCHS-SOL.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study contains whole genome sequence data. A case-control sample of individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multicenter prospective cohort study of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American background (phs000810), was selected for whole genome sequencing, including participants with a history of physician-diagnosed asthma and asthma-free participants.   Study Weblinks:   Hispanic Community Health Study / Study of Latinos NHLBI Trans-Omics for Precision Medicine Whole Genome Sequencing Program    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001395.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001395.v1.p1,c2,NHLBI TOPMed - NHGRI CCDG: Hispanic Community Health Study/Study of Latinos (HCHS/SOL),topmed,2024-05-09,"Name: HCHS-SOL_HMB, short name: HCHS-SOL.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study contains whole genome sequence data. A case-control sample of individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multicenter prospective cohort study of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American background (phs000810), was selected for whole genome sequencing, including participants with a history of physician-diagnosed asthma and asthma-free participants.   Study Weblinks:   Hispanic Community Health Study / Study of Latinos NHLBI Trans-Omics for Precision Medicine Whole Genome Sequencing Program    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001395.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001402.v2.p1,c1,NHLBI TOPMed: Whole Genome Sequencing of Venous Thromboembolism (WGS of VTE),topmed,2024-05-09,"Name: Mayo_VTE_GRU, short name: Mayo_VTE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This study consists of 338 VTE cases from an inception cohort of Olmsted County, MN residents (OC) with a first lifetime objectively-diagnosed idiopathic VTE during the 40-year study period, 1966-2005. All living study subjects were invited to provide a whole blood sample at the Mayo Clinical Research Unit for leukocyte genomic DNA and plasma collection. For living study subjects who did not provide a blood sample, we retrieved any leftover blood (""waste"" blood) from samples collected as part of routine clinical diagnostic testing and used this to extract DNA after obtaining patient consent. For deceased cases, with IRB approval, we extracted DNA from any available stored tissue within the Mayo Tissue Archive. This ""tissue"" DNA has been successfully genotyped in prior studies. Three trained and experienced study nurse abstractors reviewed the complete medical records in the community of all potential cases. Note: WGS sample IDs for the previous GENEVA study cases (phs000289) are included in this dataset. The phenotypes for the GENEVA study are located under the above phs number.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001402.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001412.v3.p1,c1,NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC),topmed,2024-05-09,"Name: NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC), short name: AACAC_HMB-IRB-COL-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans. Study Design:     Cross-Sectional Study Type:CohortCross-Sectional dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001412.v3.p1,c2,NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC),topmed,2024-05-09,"Name: NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC), short name: AACAC_DS-DHD-IRB-COL-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans. Study Design:     Cross-Sectional Study Type:CohortCross-Sectional dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001416.v3.p1,c1,NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC),topmed,2024-05-09,"Name: NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC), short name: MESA_HMB.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. Study Weblinks: MESA Study Design:     Prospective Longitudinal Cohort Study Type:FamilyLongitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001416.v3.p1,c2,NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC),topmed,2024-05-09,"Name: NHLBI TOPMed: MESA and MESA Family AA-CAC (AACAC), short name: MESA_HMB-NPU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. Study Weblinks: MESA Study Design:     Prospective Longitudinal Cohort Study Type:FamilyLongitudinal dbGaP estimated ancestry using GRAF-popSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-07-24 and may not include exact formatting or images."
+phs001434.v2.p1,c1,NHLBI TOPMed: Defining the time-dependent genetic and transcriptomic responses to cardiac injury among patients with arrhythmias (miRhythm),topmed,2024-05-09,"Name: NHLBI TOPMed: Defining the time-dependent genetic and transcriptomic responses to cardiac injury among patients with arrhythmias (miRhythm), short name: miRhythm_GRU.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The UMMS miRhythm Study is an ongoing study of adult patients undergoing an elective electrophysiology study or arrhythmia ablation procedure for a supraventricular or ventricular arrhythmia, including atrial fibrillation (AF). Atrial fibrillation is a major clinical and public health problem that is related to atrial pathologic remodeling. Few tools are available to quantify the activity or extent of this remodeling, rendering it difficult to identify individuals at risk for AF. Previous studies have suggested an important role for miRNA in cardiovascular disease through gene expression regulation, making this a promising avenue for studying AF mechanisms. The aim of the study is to determine the time-dependent changes to key circulating miRNAs in a model of planned atrial injury and remodeling via ablation. Such knowledge might provide additional insight into the biology and activity of the acute atrial injury response, and furthermore, inform new targets for development of preventative interventions or allow for better AF risk stratification. To assess pathways regulating atrial pathological remodeling, patient blood samples are collected prior to their ablation procedures and also at a regularly scheduled 1-month follow-up appointment. Plasma expression of miRNA is measured using high-throughput quantitative reverse transcriptase polymerase chain reaction (RT-qPCR), providing novel insights into the regulatory processes underlying AF, as well as acute atrial injury in vivo. Additionally, data collected from whole-genome sequencing (WGS) is used to supplement miRNA analyses and further explore new relations between genes and abnormal heart rhythm. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 65    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs001435.v1.p1,c1,NHLBI TOPMed: Australian Familial Atrial Fibrillation Study,topmed,2024-05-09,"Name: AustralianFamilialAF_HMB-NPU-MDS, short name: AustralianFamilialAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. In the Australian Familial AF Study, a cohort of probands with familial AF was recruited for genetics studies at the Victor Chang Cardiac Research Institute. Familial AF cases were identified from in-patient and out-patient populations at St. Vincent's Hospital and by referral from collaborating physicians throughout Australia. Study subjects underwent clinical evaluation with history, ECG and echocardiogram, and informed consent was obtained from all participants. 151 probands aged <66 years at the time of diagnosis were included in this analysis. The control cohort was comprised of age- and sex-matched individuals (n=151) who had no history of cardiovascular disease. In the current TOPMed study, we have performed whole genome sequencing in European Ancestry cases with early-onset atrial fibrillation (defined as atrial fibrillation onset prior to 61 years).   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001435.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001466.v1.p1,c1,NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU),topmed,2024-05-09,"Name: pharmHU_HMB, short name: pharmHU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001466.v1.p1,c2,NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU),topmed,2024-05-09,"Name: pharmHU_DS-SCD-RD, short name: pharmHU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001466.v1.p1,c3,NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU),topmed,2024-05-09,"Name: pharmHU_DS-SCD, short name: pharmHU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001467.v1.p1,c1,NHLBI TOPMed: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE),topmed,2024-05-09,"Name: SAPPHIRE_asthma_DS-ASTHMA-IRB-COL, short name: SAPPHIRE_asthma.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Started in 2007, the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) is one of the largest asthma cohort studies in the United States. Its overarching goal is to elucidate the genetic underpinnings of asthma and asthma medication treatment response. The cohort was recruited from a large health care system serving southeast Michigan and the Detroit metropolitan area, and the participants broadly represent the demographic and socioeconomic diversity of the region. Control participants (i.e., patients without a diagnosis with asthma) were recruited from the same health system and geographic region. By virtue of their health system enrollment, both asthma case and control patients have longitudinal clinical information which was routinely collected as part of their care. Both case and control patients underwent at detailed evaluation at the time of enrollment which included lung function testing and bronchodilator response. The SAPPHIRE cohort is a member of the Asthma Translational Genomics Collaborative (ATGC). The latter was selected for whole genome sequencing in Phase 3 of the National Heart Lung and Blood Institute's TOPMed Program. The SAPPHIRE sample selected for sequencing includes African American and/or Latino individuals with and without asthma.   Study Weblinks:   Williams Lab - SAPPHIRE    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001467.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001468.v3.p1,c1,NHLBI TOPMed: REDS-III Brazil Sickle Cell Disease Cohort (REDS-BSCDC),topmed,2024-05-09,"Name: NHLBI TOPMed: REDS-III Brazil Sickle Cell Disease Cohort (REDS-BSCDC), short name: REDS-III_Brazil_SCD_GRU-IRB-PUB-NPU.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Establishing a Brazilian Sickle Cell Disease Cohort and Identifying Molecular Determinants of Response to Transfusions, Genetic Determinants of Alloimmunization, and Risk Factors Associated with HIV Infection. The REDS-III Brazil SCD Cohort study focused on transfusion practices and predictors of health outcomes in patients with Sickle Cell Disease (SCD) and began in the Fall of 2013. The four primary aims of this study are: 1) Aim A - Establish a cohort of SCD patients with a comprehensive centralized electronic database of detailed clinical, laboratory and transfusion information, as well as establish a repository of blood samples to support biological studies relevant to SCD pathogenesis and transfusion complications; 2) Aim B - Characterize changes in markers of inflammation in response to transfusion by analyzing chemokine/cytokine panels in serial post transfusion specimens; 3) Aim C - Identify single nucleotide polymorphisms (SNPs) that contribute to the risk of red blood cell alloimmunization in SCD by performing a genome-wide association (GWA) study in transfused SCD patients; and, 4) Aim D - Characterize risk of HIV and HIV outcomes in the Brazilian SCD population and compare SCD outcomes among HIV sero-positive and sero-negative SCD patients. Patients are enrolled from six hospitals affiliated with the participating four REDS-III Brazil hemocenters. Study Weblinks: REDS-III Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 2795    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs001472.v2.p1,c1,NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE),topmed,2024-05-09,"Name: NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE), short name: ECLIPSE_DS-COPD-MDS-RD.","""This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, """"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"""" and """"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"""". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID:  18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID:  20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID:  21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID:  24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252. Study Weblinks: What is ECLIPSE Study Design:     Case-Control Study Type:Case-ControlLongitudinal dbGaP estimated ancestry using GRAF-pop    Total number of consented subjects: 2465    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."""
+phs001514.v1.p1,c1,NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD),topmed,2024-05-09,"Name: Walk_PHaSST_SCD_HMB-IRB-PUB-COL-NPU-MDS-GSO, short name: Walk_PHaSST_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Clinical Trial     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001514.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001514.v1.p1,c2,NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD),topmed,2024-05-09,"Name: Walk_PHaSST_SCD_DS-SCD-IRB-PUB-COL-NPU-MDS-RD, short name: Walk_PHaSST_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS.   Study Design:       Cross-Sectional    Study Type:  Cross-Sectional Clinical Trial     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001514.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001515.v1.p1,c1,NHLBI TOPMed: MyLifeOurFuture (MLOF) Research Repository of patients with hemophilia A (factor VIII deficiency) or hemophilia B (factor IX deficiency),topmed,2024-05-09,"Name: MLOF_HMB-PUB, short name: MLOF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Hemophilia A and B are X-linked bleeding disorders resulting from a deficiency in coagulation factor VIII (FVIII) or factor IX (FIX), respectively. Hemophilia affects approximately 1/5000 male births worldwide, and results in premature death and disability due to bleeding if coagulation factor replacement therapy is not used effectively. Hemophilia is clinically categorized by coagulation factor activity levels and ranges in severity from mild (6% to 30%) to moderate (1-5%) to severe (<1%). Many female ""carriers"" of hemophilia also have decreased factor activity and morbidity from bleeding. Hemophilia A and B are almost always caused by identifiable mutations in the F8 and F9 genes, respectively, and these mutations are found throughout the structural genes. Although the hemophilias are monogenic disorders, there are wide variations in disease severity and therapeutic outcomes which are not readily explained by the disease causing mutations alone. The My Life Our Future (MLOF) project (www.mylifeourfuture.org) is a national resource developed by a partnership of BloodworksNW (BWNW, formerly the Puget Sound Blood Center), the American Thrombosis and Hemostasis Network (ATHN), the National Hemophilia Foundation (NHF) and Bioverativ, to provide free F8 and F9 gene variant analysis to patients with hemophilia A or B, and to establish a research repository of DNA sequence, DNA, RNA, buffy coat, serum and plasma. The sequence analysis and serum samples are linked to a phenotypic database hosted by ATHN, with samples submitted and clinical data entered at ~100 hemophilia treatment centers (HTCs) nationwide. (See ATHN Research Report Brief in the resource center at www.athn.org). MLOF has become the largest hemophilia genetic project worldwide. The roles of the MLOF partners are: BWNW, to serve as the central laboratory for the project and house the research repository; ATHN, to support and provide the administrative link with HTCs, to facilitate the collection of accurate phenotypic data, to conduct research review and approval for use of the repository and with BWNW to provide samples and data for research projects; NHF, to provide consumer education and facilitate consumer input into the project; and Bioverativ, to provide financial support and scientific input. The project is governed by a Steering Committee consisting of one representative from each organization. Subject samples chosen from the MLOF parent study for TOPMed and WGS were drawn from those who gave (or parents gave) informed consent for the Research Repository and included patients of all severities and type, but with an emphasis on those with severe hemophilia and others at increased risk of neutralizing antibody (inhibitor) formation and who had samples in the Research Repository (plasma, serum, RNA) for potential additional -omic studies. Also included were samples from subjects where a likely causative variant for hemophilia was not found in the F8 or F9 coding region, intron-exon boundaries or immediate upstream and downstream regions. Since hemophilia is an X-linked disorder, the majority of subjects are male. Racial distribution is similar to the overall population distribution.   Study Weblinks:   mylifeourfuture    Study Design:       Cross-Sectional    Study Type:  Cross-Sectional     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001515.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001542.v1.p1,c2,NHLBI TOPMed: Genetics of Asthma in Latino Americans (GALA),topmed,2024-05-09,"Name: GALA_DS-LD-IRB-COL, short name: GALA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. A Case pharmacogenetic study of bronchodilator drug response (Albuterol) among racially admixed Latino children with asthma between the ages of 8-40. Lung function testing was performed using the KoKo PFT system and each participant was administered albuterol dependent on age. Participants under 16 years of age, were administered 2 puffs of albuterol from a standard metered dose inhaler and 4 puffs for participants over 16 years old. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants with asthma have physician-diagnosed asthma, symptoms and medications.   Study Weblinks:   Asthma Collaboratory    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001542.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001543.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: AF Biobank LMU in the context of the MED Biobank LMU,topmed,2024-05-09,"Name: AFLMU_HMB-IRB-PUB-COL-NPU-MDS, short name: AFLMU.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Atrial Fibrillation Biobank Ludwig Maximilian University (AFLMU) Study contributes to the spectrum of disease by adding carefully characterized patients with atrial fibrillation. Atrial fibrillation, one of the most common human arrhythmias confers major morbidity, mortality and health care cost, and has been demonstrated to be caused and influenced by genetic and -omics factors. Particularly, AFLMU enrolled patients with an early onset of atrial fibrillation to increase the genetic burden on disease pathophysiology. All patients were recruited applying standardized protocols to maintain homogeneity in data and DNA quality.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001543.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001544.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Malmo Preventive Project (MPP),topmed,2024-05-09,"Name: MPP_HMB-NPU-MDS, short name: MPP.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Malmö Preventive Project (MPP) was a community-based disease prevention program including 33,346 inhabitants from the city of Malmö in Southern Sweden. Complete birth cohorts between 1921-1949 were invited, and the participation rate was 71%. Participants underwent screening between 1974 to 1992 for cardiovascular risk factors, alcohol abuse, and breast cancer. Between 2002-2006, surviving participants were invited to a reexamination which included blood sampling from which DNA has been extracted. Subjects with prevalent or incident AF were identified from national registers as previously described, and cases with DNA were then matched in a 1:1 fashion to controls with DNA from the same cohort by sex, age (±1 year), and date of baseline exam (±1 year). Also, controls required a follow-up exceeding that of the corresponding AF case.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001544.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001545.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Intermountain INSPIRE Registry,topmed,2024-05-09,"Name: INSPIRE_AF_DS-MULTIPLE_DISEASES-MDS, short name: INSPIRE_AF_DS-MULTIPLE.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The INtermountain Healthcare Biological Samples Collection Project and Investigational REgistry for the On-going Study of Disease Origin, Progression and Treatment (Intermountain INSPIRE Registry) purpose is to collect biological samples, clinical information and laboratory data from Intermountain Healthcare patients. The registry originally collected samples in patients undergoing a coronary angiography as part of the Intermountain Heart Collaborative Study. It has been expanded to collect samples in patients diagnosed with all types of medical conditions, and patients from the general population including those who have not been diagnosed with health related issues. Just over 25,000 individuals have provided samples as part of this registry. The registry enables researchers to develop a comprehensive collection of information that may help in disease management, including determining best medical practices for predicting, preventing and treating medical conditions.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001545.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001546.v1.p1,c1,NHLBI TOPMed: Determining the association of chromosomal variants with non-PV triggers and ablation-outcome in AF (DECAF),topmed,2024-05-09,"Name: DECAF_GRU, short name: DECAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The DECAF trial was conducted at the Texas Cardiac Arrhythmia Institute (TCAI) in 2013 in collaboration with the University of Texas at Austin. Four hundred consecutive AF patients undergoing catheter ablation were enrolled. All participants provided voluntary informed consents. Blood samples were collected before the ablation procedure and labeled with anonymous patient identifier. The researchers at UT Austin responsible for DNA extraction and genetic analysis were blinded about the clinical characteristics and identification of the study participants. AF cases included adults >18 years of age from both sex and all AF types.   Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001546.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001547.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The GENetics in Atrial Fibrillation (GENAF) Study,topmed,2024-05-09,"Name: GENAF_HMB-NPU, short name: GENAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Genetics in AF (GENAF) study enrolled individuals with early-onset lone AF before age 50 in Norway between 2009 and 2016. Early-onset was defined as diagnosis of AF before age 50. Lone AF was defined as AF in the absence of clinical or echocardiographic findings of cardiovascular disease, hypertension, metabolic or pulmonary disease. AF was documented in ECG. All participants underwent clinical examination, including ECG, echocardiography, and blood draw, from which DNA has been extracted. The study conforms to the principles of the Declaration of Helsinki and was approved by the Regional Ethics Committee (REK) in Norway (Protocol reference number: 2009/2224-5). All included patients gave written informed consent.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001547.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001598.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study,topmed,2024-05-09,"Name: JHU_AF_HMB-NPU-MDS, short name: JHU_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001598.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001599.v1.p1,c1,NHLBI TOPMed: Boston-Brazil Sickle Cell Disease (SCD) Cohort,topmed,2024-05-09,"Name: BostonBrazil_SCD_HMB-IRB-COL, short name: BostonBrazil_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.This study involves sequencing of patients with a diagnosis of sickle cell disease from Brazil. No exclusionary criteria were employed and any eligible patients that consented to this study were recruited. Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-07-13 and may not include exact formatting or images."
+phs001600.v2.p2,c1,NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort,topmed,2024-05-09,"Name: CATHGEN_DS-CVD-IRB, short name: CATHGEN.","'This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ''TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4'' and ''TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4''. Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing. Study Design:     Case Set Study Type:Case Set dbGaP estimated ancestry using GRAF-pop NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images.'"
+phs001601.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: Penn Medicine BioBank Early Onset Atrial Fibrillation Study,topmed,2024-05-09,"Name: CCDG_PMBB_AF_HMB-IRB-PUB, short name: CCDG_PMBB_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   'TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2'  and 'TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4'.  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Cases with early-onset atrial fibrillation were selected from the Penn Biobank based on an age of atrial fibrillation onset prior to 61 years of age, and in the absence of a myocardial infarction, heart failure or severe valvular disease.   Study Design:       Case Set    Study Type:  Case Set        dbGaP estimated ancestry using     GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
+phs001602.v1.p1,c1,NHLBI TOPMed: Children's Health Study (CHS) Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP),topmed,2024-05-09,"Name: ChildrensHS_GAP_GRU, short name: ChildrensHS_GAP.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP) study was proposed to use an innovative genetics approach in mice and humans to identify novel variants that interact with traffic-related pollutant exposures to affect lung function phenotypes and the risk of childhood asthma. The study participants were enrolled from the original southern California Children's Health Study (CHS). In the TOPMed project, seven Hispanic White participants who did not have asthma history were included in the WGS analysis.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001602.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001603.v1.p1,c1,NHLBI TOPMed: Children's Health Study (CHS) Integrative Genomics and Environmental Research of Asthma (IGERA),topmed,2024-05-09,"Name: ChildrensHS_IGERA_GRU, short name: ChildrensHS_IGERA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Integrative Genomics and Environmental Research of Asthma (IGERA) Study was proposed to collect immortalized cell lines, RNA, cDNA and DNA from 400 well-characterized subjects who participated in the southern California Children's Health Study (CHS) and to develop an accompanying database for these samples consisting of extensive phenotype, exposure, genome-wide genotype, gene expression, and methylation data. A subset of Hispanic-White participants (n=160) were included in the TOPMed project, including 77 asthma cases and 83 controls.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001603.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001604.v1.p1,c1,NHLBI TOPMed: Children's Health Study (CHS) Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR),topmed,2024-05-09,"Name: ChildrensHS_MetaAir_GRU, short name: ChildrensHS_MetaAir.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR) study was proposed to study a subset of the Children's Health Study (CHS) participants representing the extremes of long-term traffic-related air pollution exposure occurring in Southern California CHS communities. The primary aim of the Meta-AIR study was to investigate whether lifetime exposure to air pollution increases risk for obesity and metabolic dysfunction at 17-18 years of age. A total of 56 Hispanic White participants (16 asthma cases and 40 controls) were included in the TOPMed project.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001604.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001605.v1.p1,c2,NHLBI TOPMed: Chicago Initiative to Raise Asthma Health Equity (CHIRAH),topmed,2024-05-09,"Name: CHIRAH_DS-ASTHMA-IRB-COL, short name: CHIRAH.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The CHIRAH project was a community based study of the factors associated with asthma morbidity in the African American population. CHIRAH evaluated the role of various variables (biologic / environmental, psychologic / behavioral, and socioeconomic) on asthma morbidity and the function of changes in these variables on asthma morbidity in a longitudinal fashion. This involved collection of a cohort based on school screening which was sampled to include similar numbers of underprivileged and non-underprivileged subjects which roughly equally represented self-classified African Americans and self-classified non-African Americans. Subjects were followed-up every 3 months of this cohort over the course of 2 years.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001605.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001606.v1.p1,c1,NHLBI TOPMed: Early-onset Atrial Fibrillation in the Estonian Biobank,topmed,2024-05-09,"Name: EGCUT_GRU, short name: EGCUT.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up.   Study Weblinks:   EGCUT Estonian BioBank    Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001606.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001607.v2.p2,c1,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,topmed,2024-05-09,"Name: IPF_DS-ILD-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001607.v2.p2,c2,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,topmed,2024-05-09,"Name: IPF_DS-LD-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001607.v2.p2,c3,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,topmed,2024-05-09,"Name: IPF_DS-PFIB-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001607.v2.p2,c4,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,topmed,2024-05-09,"Name: IPF_DS-PUL-ILD-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001607.v2.p2,c5,NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing,topmed,2024-05-09,"Name: IPF_HMB-IRB-NPU, short name: IPF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001607.v2.p2 on 2021-03-25 and may not include exact formatting or images."
+phs001608.v1.p1,c1,NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG),topmed,2024-05-09,"Name: OMG_SCD_DS-SCD-IRB-PUB-COL-MDS-RD, short name: OMG_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, ""Outcome Modifying Genes in Sickle Cell Disease"" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001608.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001612.v1.p1,c1,NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA),topmed,2024-05-09,"Name: CARDIA_HMB-IRB, short name: CARDIA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.   Study Weblinks:   CARDIA: Coronary Artery Risk Development in Young Adults    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001612.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001612.v1.p1,c2,NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA),topmed,2024-05-09,"Name: CARDIA_HMB-IRB-NPU, short name: CARDIA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.   Study Weblinks:   CARDIA: Coronary Artery Risk Development in Young Adults    Study Design:       Prospective Longitudinal Cohort    Study Type:  Longitudinal     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001612.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001624.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The Vanderbilt University BioVU Atrial Fibrillation Genetics Study,topmed,2024-05-09,"Name: BioVU_AF_HMB-GSO, short name: BioVU_AF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. At least 2.7 million Americans are living with AFib. Individuals with early onset atrial fibrillation (AF) are included in this study of cases from the BioVU sample repository. BioVU is Vanderbilt's biobank of DNA extracted from leftover and otherwise discarded clinical blood specimens. BioVU operates as a consented biorepository; all individuals must sign the BioVU consent form in order to donate future specimens. BioVU subjects are de-identified and linked to the Synthetic Derivative enabling researchers to access genetic data/DNA material as well as dense, longitudinal electronic medical record (EMR) information.   Study Design:       Case Set    Study Type:  Case Set     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001624.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001644.v1.p1,c1,NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai,topmed,2024-05-09,"Name: BioMe_HMB-NPU, short name: BioMe.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants enroll through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a ""data-broker"" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry (Table 1, Figure 1). BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%) (Table 1, Figure 1). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has available a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden.  ** Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. ** Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individual with COPD (62% women) and 1800 as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.   Study Weblinks:   The Charles Bronfman Institute for Personalized Medicine    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001644.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001661.v2.p1,c1,NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A),topmed,2024-05-09,"Name: GCPD-A_DS-ASTHMA-GSO, short name: GCPD-A.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response.   Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001661.v2.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001662.v1.p1,c2,NHLBI TOPMed: Lung Tissue Research Consortium (LTRC),topmed,2024-05-09,"Name: LTRC_HMB-MDS, short name: LTRC.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburg, and Temple University.   Study Weblinks:   LTRC    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001662.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001682.v1.p1,c1,NHLBI TOPMed: Pulmonary Hypertension and the Hypoxic Response in SCD (PUSH),topmed,2024-05-09,"Name: PUSH_SCD_DS-SCD-IRB-PUB-COL, short name: PUSH_SCD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. During Visit One, the PUSH Study will perform echocardiography on 600 children and adolescent with patients with SCD and 100 control children and adolescents at three Field Centers, namely Howard University, Children's National Medical Center and University of Michigan. Patients or their parents will be approached and asked to give informed consent. If they appear to have difficulty reading, reading of the consent will be offered. Patients or their parents not appearing to comprehend the consent will not be eligible. As a part of this visit, each participant or parent will sign informed consent, complete a Participant Contact Information Form, complete a Medical History Form, undergo physical examination with completion of a Physical Examination Form and have blood drawn. Each participant must have echocardiography performed with measurement of Tricuspid Regurgitant Jet Velocity (TRV). In addition attempts will be made 1) to perform a six-minute walk test, 2) to collect information from a recent (within six months) Transcranial Doppler Study (TCD) or to perform TCD, and 3) to perform pulmonary function tests. Study personnel will review all forms for completeness and conduct phlebotomy. Blood will be shipped to the Central Lab. Results of all procedures and tests will be transmitted to the Data Manager at Howard University. Sequencing was only done on sickle cell participants.    Study Design:       Case-Control    Study Type:  Case-Control     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001682.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001725.v1.p1,c1,NHLBI TOPMed CCDG: Groningen Genetics of Atrial Fibrillation (GGAF) Study,topmed,2024-05-09,"Name: GGAF_GRU, short name: GGAF.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. The Groningen Genetics of Atrial Fibrillation (GGAF) cohort is a cohort composed from 5 different sources of individuals with atrial fibrillation (AF) and age and sex-matched controls. Written informed consent was provided from all participating individuals, and all 5 studies were approved by the ethical committee at the University Medical Center (www.atrialfibrillationresearch.nl) and Maastricht University. All samples selected for TOPMed WGS are from individuals with atrial fibrillation.   Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001725.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001726.v1.p1,c1,NHLBI TOPMed: Childhood Asthma Management Program (CAMP),topmed,2024-05-09,"Name: CAMP_DS-AST-COPD, short name: CAMP.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. The Childhood Asthma Management Program (CAMP) was designed to evaluate whether continuous, long-term treatment (over a period of four to six years) with either an inhaled corticosteroid (budesonide) or an inhaled noncorticosteroid drug (nedocromil) safely produces an improvement in lung growth as compared with treatment for symptoms only (with albuterol and, if necessary, prednisone, administered as needed). The primary outcome in the study was lung growth, as assessed by the change in forced expiratory volume in one second (FEV1, expressed as a percentage of the predicted value) after the administration of a bronchodilator. Secondary outcomes included the degree of airway responsiveness, morbidity, physical growth, and psychological development.   Study Design:       Family/Twin/Trios    Study Type:  Parent-Offspring Trios     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001726.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001727.v1.p1,c2,NHLBI TOPMed: Pathways to Immunologically Mediated Asthma (PIMA),topmed,2024-05-09,"Name: PIMA_DS-ASTHMA-IRB-COL, short name: PIMA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Study designed to further our understanding of the pathogenesis of asthma exacerbations in children. Children enrolled in the study (n=217) were all asthmatic and primarily Hispanic white. The children were followed for 18 months until they experienced an asthma exacerbation or completed the follow-up without an exacerbation. The time to the first asthma exacerbation was considered the outcome. The acute and convalescent immune phenotype of each asthma exacerbation was documented.   Study Weblinks:   PIMA    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001727.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001728.v1.p1,c2,NHLBI TOPMed: Best ADd-on Therapy Giving Effective Response (BADGER),topmed,2024-05-09,"Name: CARE_BADGER_DS-ASTHMA-IRB-COL, short name: CARE_BADGER.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. BADGER is a 56-week randomized, double-blind, three-treatment, three-period cross-over trial that will evaluate the differential improvement in control that is achieved following three separate treatment interventions in children whose asthma is not acceptably controlled on a low dose of ICS (per NAEPP guidelines). All participants will enter an 8-week run-in period during which time they will receive a dose of 1x ICS (fluticasone 200 μg/day). During this 8-week time period, running 2-week averages to establish the lack of acceptable asthma control will be calculated. Thus, a child could qualify for randomization at any time during this 8-week run-in period. This approach should maximize both patient safety and successful enrollment. Children will continue to receive 1x ICS during the entire treatment phase. During each period of the treatment phase, they also will receive one add-on therapy in the form of LABA, LTRA or additional 1x ICS. The order of the add-on therapy assignment will be determined by randomization into one of six treatment sequences (order determined randomly). Each treatment period will be 16 weeks in length; the initial 4 weeks of each period will be considered to be the washout period for the previous treatment. The primary outcome measures will be frequency of asthma exacerbations, asthma control days, and FEV1.   Study Weblinks:   BADGER    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001728.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001729.v1.p1,c2,NHLBI TOPMed: Characterizing the Response to a Leukotriene Receptor Antagonist and an Inhaled Corticosteroid (CLIC),topmed,2024-05-09,"Name: CARE_CLIC_DS-ASTHMA-IRB-COL, short name: CARE_CLIC.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. Within-subject clinical responses to either inhaled corticosteroids or Montelukast were compared in 126 children with mild to moderate asthma.   Study Weblinks:   CLIC    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001729.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001730.v1.p1,c2,NHLBI TOPMed: Pediatric Asthma Controller Trial (PACT),topmed,2024-05-09,"Name: CARE_PACT_DS-ASTHMA-IRB-COL, short name: CARE_PACT.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. After a 2-4 week assessment/characterization run-in period, 6-14 year-old children who met NAEPP criteria for mild-moderate persistent asthma specifically based on symptom criteria and methacholine PC20 ≤ 12.5 mg/ml and FEV1 ≥ 80% were randomized to one of the three active treatment arms for 12 months. Randomization was stratified according to clinical center, bronchodilator response (< 12% or ≥ 12%), race (Caucasian or non-Caucasian), and methacholine PC20 (< 2 or ≥ 2 mg/ml). The primary outcome variable was the proportion of asthma-free days during the 12-month treatment period. Secondary outcomes included other measures of asthma control (percentage of rescue-free days, albuterol-free days, and episode-free days; the number of asthma exacerbations requiring prednisone therapy and the time to the first asthma exacerbation), forced oscillation and spirometry, reversibility (FEV1 pre- and post 2 puffs of albuterol MDI), methacholine PC20, exhaled nitric oxide, and asthma-related quality of life.   Study Weblinks:   PACT    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001730.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001732.v1.p1,c2,NHLBI TOPMed: TReating Children to Prevent EXacerbations of Asthma (TREXA),topmed,2024-05-09,"Name: CARE_TREXA_DS-ASTHMA-IRB-COL, short name: CARE_TREXA.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed)  Whole Genome Sequencing Program. TOPMed is part of a broader  Precision Medicine Initiative,  which aims to provide disease treatments that are tailored to an individual's  unique genes and environment. TOPMed will contribute to this initiative through the  integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles,  protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental,  and clinical data. In doing so, this program aims to uncover factors that increase or decrease  the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized  treatments. Two genotype call sets derived from WGS are now available,  Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets.  Information about how to identify other TOPMed WGS accessions for cross-study analysis,  as well as descriptions of TOPMed methods of data acquisition, data processing and quality control,  are provided in the accompanying documents,   ""TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2""  and ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"".  Please check the study list at the top of each of these methods documents to determine whether  it applies to this study accession. TREXA is a 44-week randomized, double-blind, double-masked, four-treatment, parallel trial that will evaluate the weaning strategy that provides the best protection against the development of exacerbations in children whose asthma is acceptably controlled on a low dose of ICS (per NAEPP guidelines). Following the 4 weeks of the run-in period on a 1x dose of ICS (100 µg fluticasone b.i.d. or its equivalent), children who do not meet the definition of acceptable asthma control will be randomized to the parallel BADGER protocol; those who meet the definition of acceptable asthma control will be enrolled into the 44-week treatment phase of the study. The primary outcome measure will be time to first exacerbation requiring a prednisone course.   Study Weblinks:   TREXA    Study Design:       Prospective Longitudinal Cohort    Study Type:  Cohort     dbGaP estimated ancestry using  GRAF-pop  Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001732.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs001735.v2.p1,c1,NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank,topmed,2024-05-09,"Name: PCGC_CHD_HMB, short name: PCGC_CHD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design:     Prospective Longitudinal Cohort Study Type:Case SetParent-Offspring Trios dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-07-13 and may not include exact formatting or images."
+phs001735.v2.p1,c2,NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank,topmed,2024-05-09,"Name: PCGC_CHD_DS-CHD, short name: PCGC_CHD.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design:     Prospective Longitudinal Cohort Study Type:Case SetParent-Offspring Trios dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-07-13 and may not include exact formatting or images."
+phs001843.v1.p2,c1,Pediatric Cardiac Genomics Consortium (PCGC) Study - Centers for Mendelian Genomics Collaboration,PCGC,2024-05-09,"Name: CMG_WGS_HMB, short name: CMG_WGS_HMB.","This substudy phs001843 PCGC Study - CMG Collaboration contains whole genome sequences. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194. Mendelian cardiovascular disorders provide crucial insights into the genetic susceptibility to more common forms of cardiovascular disease. While Mendelian cardiovascular disorders are individually rare, collectively they impose a significant public health burden. This proposal focuses on 2 specific categories of cardiovascular disease for which we have extensive research expertise and existing cohorts, congenital heart disease (CHD) and inherited arrhythmia syndromes. The tremendous burden on the health care system and on families with these Mendelian cardiovascular disorders underscore the urgency to understand their genomic bases, in order to design improved strategies for risk stratification, surveillance and medical intervention. Emerging evidence supports the use of whole-genome sequencing (WGS) over whole-exome sequencing (WES) for detecting coding variants in discovery projects, in addition to the obvious advantages of detecting features invisible to WES: structural variants (SV) and non-coding variants. We believe the way forward lies in widening the scope for discovery to include the patient's entire genome - and all types of variants. While family-based studies are crucial for genomic discovery, obtaining a sufficient number of high-risk pedigrees to achieve meaningful conclusions remains a challenge for most research institutions. For this proposal, we will leverage 2 powerful resources for the identification, ascertainment and recruitment of high-risk cardiovascular disease pedigrees: (1) the NHLBI-sponsored Pediatric Cardiac Genomics Consortium (PCGC) and (2) the Utah Population Database (UPDB). We propose to perform WGS on PCGC and UPDB cohorts with autosomal dominant disease to achieve the following Specific Aims: Aim 1) Identify the genomic basis for CHD in high-risk pedigrees derived from the PCGC and UPDB; and Aim 2) Identify the genomic basis for inherited arrhythmia disorders, using extended pedigrees derived from the UPDB. Aim 2 focuses on familial forms of AF, undiagnosed Long QT Syndrome, Wolff-Parkinson White syndrome and progressive conduction disorders. A WGS approach in high-risk pedigrees coupled with our validated bioinformatics pipeline, will allow the identification and prioritization of disease-causing SVs and sequence variants in coding and non-coding regulatory elements. These variants will be functionally characterized and validated in downstream experiments (heterologous expression systems, zebrafish cardiac assays, induced pluripotent stem cell-derived cardiomyocytes) that are beyond the scope of this X01. For this proposal, we have assembled the right combination of clinical expertise, resources for patient recruitment and computational know-how to enable these game-changing methodologies and to apply them to the challenge of cardiovascular Mendelian disease-gene discovery. Study Weblinks: Bench to Bassinet Program Study Design:     Family/Twin/Trios Study Type:FamilyCohortNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images."
+phs001927.v1.p1,c1,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),topmed,2024-05-09,"Name: SPIROMICS_DS-COPD-NPU, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
+phs001927.v1.p1,c2,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),topmed,2024-05-09,"Name: SPIROMICS_DS-COPD, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
+phs001927.v1.p1,c3,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),topmed,2024-05-09,"Name: SPIROMICS_GRU-NPU, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
+phs001927.v1.p1,c4,NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS),topmed,2024-05-09,"Name: SPIROMICS_GRU, short name: SPIROMICS.","This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, ""TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4"" and ""TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4"". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies  Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data.  The overall objectives of the Exacerbation Substudy are to:  Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by  Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold)   Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation ""stable"" state in COPD using the EXACT, including:  Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability.   Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.  Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design:     Prospective Longitudinal Cohort Study Type:Cohort dbGaP estimated ancestry using GRAF-popNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
+phs001961.v2.p1,c1,LungMAP: Molecular Atlas of Lung Development – Human Lung Tissue,LungMAP,2024-05-09,"Name: MALD_GRU, short name: MALD_GRU.","Mammalian fetal lung development is a complex biological process. Despite considerable progress, a comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. The purpose of this study as part of the LungMAP consortium (www.lungmap.net) is to understand the transcriptional changes in the process of mammalian lung development. Study Weblinks: NCBI GEO GSE161383 Study Design:     Control Set Study Type:LongitudinalSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-01 and may not include exact formatting or images."
+phs002299.v1.p1,c1,PETAL Network: Outcomes Related to COVID-19 Treated With Hydroxychloroquine Among Inpatients With Symptomatic Disease (ORCHID) Trial,COVID19,2024-05-09,"Name: ORCHID_HMB, short name: ORCHID.","ORCHID was a multicenter, blinded, placebo-controlled randomized trial conducted at 34 hospitals in the US between April 2 and June 19, 2020. Adults hospitalized with respiratory symptoms from severe acute respiratory syndrome coronavirus 2 infection were enrolled, with the last outcome assessment on July 17, 2020. The planned sample size was 510 patients with five interim analyses; however, the trial was stopped at the fourth interim analysis for futility with a sample size of 479 patients.The distribution of the day 14 clinical status score (measured using a 7-category ordinal scale) was not significantly different for patients randomized to receive hydroxychloroquine compared with placebo.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.    Study Weblinks:   PETAL Network ORCHID Study    Study Design:       Clinical Trial    Study Type:  Clinical Trial Controlled Trial Placebo-Controlled Randomized Randomized Controlled Clinical Trial   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002299.v1.p1 on 2021-03-25 and may not include exact formatting or images."
+phs002348.v1.p1,c1,Multicenter Study of Hydroxyurea (MSH),BioLINCC,2024-05-09,"Name: MSH_GRU, short name: MSH.","This study aimed to determine whether or not treatment with hydroxyurea titrated to maximum tolerated doses would reduce the frequency of vaso-occlusive (painful) crises by at least 50% in 299 men and women between 18 and 50 years old with a diagnosis of sickle cell anemia by gel electrophoresis conducted by a Core Laboratory. A secondary objective investigated correlations of fetal hemoglobin (HbF) levels and other patient or treatment characteristics with the occurrence of vaso-occlusive (painful) crises, and the effect of treatment on the quality of life.This controlled trial made hydroxyurea the first drug of proven benefit in preventing vaso-occlusive pain crisis and acute chest syndrome caused by sickle cell disease, with additional findings including reduced mortality in adult patients taking hydroxyurea for frequent painful sickle cell episodes after 9 of years follow-up. No significant side-effects of hydroxyurea therapy were noted.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.    Study Weblinks:      ClinicalTrials.gov (MSH) NHLBI BioLINCC (MSH)    Study Design:       Clinical Trial    Study Type:  Double-Blind Randomized Controlled Clinical Trial   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
+phs002362.v1.p1,c1,Cooperative Study of Sickle Cell Disease (CSSCD),BioLINCC,2024-05-09,"Name: CSSCD_GRU, short name: CSSCD.","The Cooperative Study of Sickle Cell Disease was initiated in 1977 to determine the natural history of sickle cell disease (SCD) from birth to death in order to identify those factors contributing to the morbidity and mortality of the disease. Specific objectives included: 1) to study the effect of sickle cell disease on growth and development from birth through adolescence 2) to study the conditions or events that may be related to the onset of painful crises 3) to obtain data on the nature, duration, and outcome of major complications of SCD 4) determine the nature, prevalence, and age- related incidence of organ damage due to SCD, and 5) study the role of SCD and its interaction with selected health events.Phases 2 and 3 of the study involved followup of the infant cohort. A total of 709 infants (age less than 6 months) were enrolled during Phase 1 of the Cooperative Study of Sickle Cell Disease (CSSCD), and Phases 2 and 3 of the CSSCD was designed to follow these children for an additional 10 years. The study objectives included: 1) define prospectively the natural history of sickle cell disease; 2) determine the relationships between cognitive and academic functioning and brain status as determined by MRI; 3) determine the cognitive or behavioral markers of silent infarct; 4) determine the relationship of family functioning on the Family Environment Scale (FES) to brain status, cognitive functioning, and social and demographic factors; 5) continue studies that will enhance the state of knowledge on the influence of sickle cell disease on the psychosocial adjustment of children and adolescents. Phase 2A of the study sought to examine the progression of organ damage in the heart, lung, kidney, and liver in adult cohort patients (born before 1/1/56) enrolled in phase 1 of the study between 3/79 and 5/81. A total of 620 patients from 11 centers were eligible for phase 2A.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.     Study Weblinks:      ClinicalTrials.gov (CSSCD) BioLINCC (CSSCD) - For biospecimen requests    Study Design:       Clinical Trial    Study Type:  Case-Control Clinical Trial   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
+phs002363.v1.p1,c1,PETAL - Repository of Electronic Data COVID-19 Observational Study,COVID19,2024-05-09,"Name: RED_CORAL_HMB, short name: RED_CORAL_HMB.","To describe characteristics, treatment, and outcomes among patients hospitalized with COVID-19 early in the pandemic, 1480 consecutive adult inpatients with laboratory-confirmed, symptomatic SARS-CoV-2 infection admitted to 57 US hospitals from March 1 to April 1, 2020 were studied.It was found that in a geographically diverse early-pandemic COVID-19 cohort with complete hospital folllow-up, hospital mortality was associated with older age, comorbidity burden, and male sex. Intensive care unit admissions occurred early and were associated with protracted hospital stays. Survivors often required new health care services or respiratory support at discharge.The PETAL Network central institutional review board at Vanderbilt University and the institutional review boards at each participating hospital approved the study or determined that the study was exempt from review.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: PETAL Network RED CORAL StudyNHLBI BioLINCC (RED CORAL) Study Design:     Control Set Study Type:Case-CohortClinical CohortCohortMulticenter NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images."
+phs002383.v1.p1,c1,Treatment of Pulmonary Hypertension and Sickle Cell Disease With Sildenafil Therapy (walk-PHaSST),BioLINCC,2024-05-09,"Name: Treatment of Pulmonary Hypertension and Sickle Cell Disease With Sildenafil Therapy (walk-PHaSST), short name: Walk_PHaSST_DS-SCD-IRB-PUB-COL-NPU-MDS-RD.","Pulmonary arterial hypertension (PAH) is a progressive condition characterized by narrowing or stiffening pulmonary arterioles resulting in increased pulmonary blood pressure and reduced delivery of oxygenated blood to the body. It is a common complication of sickle cell disease and initially presents with the symptom of shortness of breath (dyspnea) on exertion. As the condition worsens, other symptoms such as dizziness, lower extremity edema, and chest pain can develop. The drug, sildenafil, works by relaxing blood vessels in the lungs which reduces pulmonary blood pressure and allows more oxygenated blood to circulate. Increased levels of oxygenated blood allows individuals with PAH to tolerate more activity, but guidelines for using sildenafil in patients with PAH and sickle cell disease were unavailable at the time of the Walk-PHaSST trial.Participants were screened for the existence of pulmonary hypertension with a six minute walk test and a Doppler echocardiogram that assessed TRV, diastolic function, and valvular and systolic function. Subjects with TRV ≥ 2.7 m/s received further clinical evaluation for possible causes of pulmonary hypertension. Other screening data included medical history, a physical exam, and standard laboratory testing. For individuals with moderate to severe pulmonary hypertension (TRV ≥ 3.0), a cardiac catheterization was done at the baseline and week 16 data collection periods.Subjects eligible for the main intervention trial based on screening results were randomized in a 1:1 double blind fashion to receive sildenafil or placebo for 16 weeks. Subjects received 20 mg of oral sildenafil or matching placebo 3 times daily for 6 weeks, followed by 40 mg 3 times daily for 4 weeks, followed by 80 mg 3 times daily for 6 weeks, as tolerated. Participants could also receive other therapies as needed to manage sickle cell and related complications. The primary outcome measure of the trial was change in the six minute walk test, a standard indicator of a person's heart and lung function and exercise capacity, from baseline to week 16. After completing the study treatment (or placebo), participants could choose to be part of the open-label follow-up phase of the study and continue to be assessed for up to one year.The study was intended to screen about 1000 subjects and randomize 132 subjects, however it was terminated early due to the unforeseen increase in adverse events in participants treated with sildenafil as compared to placebo. When the study was stopped, 33 participants had completed the trial. Subjects continued to be monitored, but were instructed to taper sildenafil treatment over three to seven days.There was no evidence that treatment with sildenafil impacted the six minute walk distance from baseline to week 16. In addition, treatment with sildenafil appeared to increase rates of hospitalization due to sickle cell disease pain.Due to in part to the early termination of the trial, the majority of subject data was collected from the screening phase of the study (n=720), as opposed to the main intervention trial (n=74).Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: ClinicalTrials.gov (Walk-PHaSST)BioLINCC (Walk-PHaSST) Study Design:     Clinical Trial Study Type:Clinical TrialDouble-Blind    Total number of consented subjects: 720    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs002385.v1.p1,c1,Hematopoietic Cell Transplant for Sickle Cell Disease (HCT for SCD),BioLINCC,2024-05-09,"Name: CIBMTR_GRU, short name: CIBMTR.","The Center for International Blood and Marrow Transplant Research (CIBMTR) is a hematopoietic cell transplant registry that was established in 1972 at the Medical College of Wisconsin. The overarching goal of the registry is to study trends in transplantations and to advance the understanding and application of allogeneic hematopoietic cell transplantation for malignant and non-malignant diseases. Included in this dataset are children, adolescents and young adults with severe sickle cell disease who received an allogeneic hematopoietic cell transplant in the United States and provided written informed consent for research.Hematopoietic cell transplant for sickle cell disease is curative. Offering this treatment for patients with severe disease is challenging as only about 20-25% of patients expected to benefit have an HLA-matched sibling. Consequently, several transplantations have utilized an HLA-matched or mismatched unrelated adult donor and HLA-mismatched relative. Transplantation strategies have also evolved over time that has included transplant conditioning regimens of varying intensity, grafts other than bone marrow and novel approaches to overcome the donor-recipient histocompatibility barrier and limit graft-versus-host disease. The data that is available for sickle cell disease transplants have been utilized to report on outcomes after transplantation and compare outcomes after transplantation of grafts HLA-matched related, HLA-mismatched related, HLA-matched and HLA-mismatched unrelated donors. Collectively, these data have advanced our knowledge and understanding of hematopoietic cell transplant for this disease. These data can also serve as 'contemporaneous controls' for comparison with other more recent curative treatments like gene therapy and gene editing.Data available for request include allogeneic hematopoietic cell transplants for sickle cell disease (Hb SS and Hb Sβ thalassemia) in the United States from 1991 to 2019. Follow-up data through December 2020 are available.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.   Study Weblinks:      ClinicalTrials.gov (HCT for SCD) BioLINCC (HCT for SCD)    Study Design:       Prospective Longitudinal Cohort    Study Type:  Clinical Cohort Cohort Control Set Longitudinal Longitudinal Cohort Multicenter Observational   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
+phs002386.v1.p1,c1,Optimizing Primary Stroke Prevention in Children with Sickle Cell Anemia (STOP II),BioLINCC,2024-05-09,"Name: STOPII_GRU, short name: STOPII.","The STOP II trial evaluated whether prophylactic transfusion in patients with sickle cell disease and high risk of stroke can be safely halted after 30 months of treatment during which patients became low risk for stroke.Stroke causes substantial morbidity in children with sickle cell disease. To prevent first strokes, the Stroke Prevention Trial in Sickle Cell Anemia (STOP) used prophylactic transfusions in children who were identified by transcranial Doppler (TCD) ultrasonography as being at high risk for stroke. This strategy reduced the incidence of stroke among such children from 10% per year to less than 1% per year, leading to recommendations for TCD screening and prophylactic transfusion for children with abnormal velocities on ultrasonography. Despite the reduced risk of stroke, long-term use of transfusions can cause adverse side effects, such as iron overload or alloimmunization. However, cessation of transfusions is associated with recurrence of stroke, and at the time of the STOP II trial, there were no clinical or laboratory indicators to guide the duration of prophylaxis. Therefore the STOP II trial was initiated to determine whether transfusions could be limited by monitoring patients with TCD examinations after transfusions were halted and resuming transfusions if the examination indicated a high risk of stroke.The trial was halted for safety concerns after 79 of a planned 100 children were randomized. Discontinuation of transfusion for the prevention of stroke in children with sickle cell disease resulted in a high rate of reversion to abnormal blood-flow velocities on Doppler studies and stroke incidence.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.    Study Weblinks:      BioLINCC (STOP II) ClinicalTrials.gov (STOP II)    Study Design:       Clinical Trial    Study Type:  Clinical Trial Randomized   Number of study subjects that have individual-level data available through Authorized Access:  NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2021-07-07 and may not include exact formatting or images."
+phs002415.v1.p1,c1,Hydroxyurea to Prevent Organ Damage in Children with Sickle Cell Anemia (BABY HUG),BioLINCC,2024-05-09,"Name: BabyHug_DS-SCD-IRB-RD, short name: BabyHug.","Sickle cell anemia is associated with substantial morbidity from acute complications and organ dysfunction beginning in the first year of life. In 1995, the Multicenter Study of Hydroxyurea (MSH) (dbGaP phs002348) demonstrated that, in adults, hydroxyurea is effective in decreasing the frequency of painful crises, hospitalizations for crises, acute chest syndrome, and blood transfusions by 50%. The phase I/II study of hydroxyurea in children (HUG KIDS) demonstrated that children have a response to hydroxyurea similar to that seen in adults in terms of increasing fetal hemoglobin levels and total hemoglobin, and decreasing complications associated with sickle cell anemia. In addition, this study demonstrated that the drug does not adversely affect growth and development between the ages of 5 and 15. A pilot study of hydroxyurea (HUSOFT) given to children between the ages of 6 months and 24 months demonstrated that the drug was well tolerated and that the fetal hemoglobin levels rose and remained elevated compared to baseline with continued hydroxyurea administration.A Special Emphasis Panel (SEP) met on April 12, 1996 to review the results of the MSH trial and the progress to date of the HUG KIDS study. The SEP recommended that NHLBI undertake the BABY HUG trial.The BABY HUG Randomized Controlled Trial concluded that hydroxyurea treatment in very young children seemed to have an acceptable safety profile and to reduce complications of sickle cell anemia. However, more data were needed on the long-term safety of hydroxyurea use in very young children. As a result, follow-up studies were initiated. The Follow-Up Study II provided longer follow-up than Follow-Up Study I, and included more assessment types than Follow-Up Study I.The BABY HUG program consisted of three related studies, each of which has associated datasets and bio-specimens.A randomized controlled trial comparing hydroxyurea to placebo in very young children with sickle cell anemia (BABY HUG Randomized Controlled Trial)The first observational follow-up study of children from the randomized controlled trial (BABY HUG Follow-Up Study I). All children in Follow-Up Study I were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The second observational follow-up study of children from BABY HUG Follow-Up Study I. All children in Follow-Up Study II were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The purpose of the Randomized Controlled Trial was to determine if hydroxyurea can safely prevent early end organ damage in very young children with sickle cell anemia.The purpose of the BABY HUG Follow-up Study I was to provide structured follow-up of the children enrolled in the BABY HUG Randomized Controlled Trial, in order to characterize the long-term toxicities and unexpected risks (if any) associated with treatment with hydroxyurea at an early age.The objective of Follow-Up Study II was to obtain additional data about the long-term safety and efficacy of hydroxyurea use in children with Sickle Cell Anemia through at least the first decade of life.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks:     Randomized Control TrialFollow-Up Study IFollow-Up Study IIBioLINCC - BABY HUG Study Design:     Clinical Trial Study Type:Clinical CohortClinical TrialCollectionControlled TrialDouble-BlindNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images."
+phs002694.v3.p1,c1,Accelerating COVID-19 Therapeutic Interventions and Vaccines 4 ACUTE (ACTIV-4A),COVID19,2024-05-09,"Name: ACTIV4A_GRU, short name: ACTIV4A_GRU.","This is a randomized, open label, adaptive platform trial to compare the effectiveness of antithrombotic strategies for prevention of adverse outcomes in COVID-19 positive inpatients. Study Design:     Interventional Study Type:Clinical TrialControlled TrialInterventionalRandomizedRandomized Controlled Clinical TrialSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-07 and may not include exact formatting or images."
+phs002710.v1.p1,c1,COVID-19 Outpatient Thrombosis Prevention Trial (ACTIV-4B),COVID19,2024-05-09,"Name: ACTIV4B_GRU, short name: ACTIV-4B.",An adaptive randomized double-blind placebo-controlled platform trial to compare the effectiveness of anticoagulation with antiplatelet agents and with placebo to prevent thrombotic events in patients diagnosed with COVID-19 who are not admitted to hospital as COVID-19 related symptoms are currently stable. Study Design:     Interventional Study Type:Clinical TrialDouble-BlindInterventionalPlacebo-ControlledRandomizedRandomized Controlled Clinical TrialNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-03-29 and may not include exact formatting or images.
+phs002715.v1.p1,c1,Cleveland Family Study,NSRR,2024-05-09,"Name: NSRR-CFS_DS-HLBS-IRB-NPU, short name: NSRR-CFS.","The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders.  The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes.  Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance. Study Weblinks: Cleveland Family Study Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal CohortNOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2022-05-24 and may not include exact formatting or images."
+phs002752.v1.p1,c1,Clinical-trial of COVID-19 Convalescent Plasma in Outpatients (C3PO),COVID19,2024-05-09,"Name: C3PO_GRU, short name: C3PO.","The overarching goal of this project is to confirm or refute the role of passive immunization as a safe and efficacious therapy in preventing the progression from mild to severe/critical COVID-19 illness and to understand the immunologic kinetics of anti-SARS-CoV-2 antibodies after passive immunization.The primary objective is to determine the efficacy and safety of a single dose of convalescent plasma (CP) for preventing the progression from mild to severe COVID-19 illness. The secondary objective is to characterize the immunologic response to CP administration.This study will enroll adults presenting to the emergency department (ED) with mild, symptomatic, laboratory-confirmed COVID-19 illness, who are at high risk for progression to severe/critical illness, but who are clinically stable for outpatient management at randomization."
+phs002770.v1.p1,c1,Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children (MUSIC),COVID19,2024-05-09,"Name: Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children (MUSIC), short name: MUSIC_GRU.","This study is an observational cohort study that will use routinely-collected clinical and cardiac (EKG, echocardiogram, CMR, exercise testing) data to assess the association between MIS-C (multisystem inflammatory syndrome in children) and cardiac outcomes within the first year after hospital discharge. Research funding will be available for EKGs, echocardiograms and MRIs in protocol windows that are not ordered by primary caregivers. Our principal goal is to determine the spectrum and early time course of coronary artery involvement, LV systolic function, and arrhythmias or conduction system abnormalities, and, using these data, to define associated clinical and laboratory factors."
+phs002808.v1.p1,c1,NHLBI TOPMed: Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b),topmed,2024-05-09,"Name: Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be, short name: nuMoM2b_GRU-IRB.","Participants from study sites that recruited during the original study funded by NICHD of pregnant people, called nuMoM2b, participated in this study. The nuMoM2b-HHS1 was a prospective observational follow-up study of the nuMoM2b cohort consisting of interval contacts via phone or web every 6 months to about a year, and an in-person visit 2 to 7 years after the end of the nuMoM2b pregnancy including: Demographics Self-administered questionnaires Clinical measurements Lab results An in-home sleep breathing assessment for the subset of participants with at least one valid sleep breathing assessment during nuMoM2b Abstraction of medical records for pregnancies subsequent to nuMoM2b involving self-reported adverse pregnancy outcomes or multiple births Abstraction of medical records of selected cardiovascular risk-related events or procedures reported by participants. The study capitalized on the rich and unique data prospectively collected during nuMoM2b (biomarkers, uterine artery Doppler studies, fetal growth, psychosocial determinants, sleep, and blood pressure) and rigorous definitions of adverse pregnancy outcomes. These data are stored in the NICHD repository DASH (https://dash.nichd.nih.gov/study/226675). A total of 8,838 nuMoM2b participants were targeted for contact during nuMoM2b-HHS and 7,872 participants were reached, of whom 7,003 completed one or more interval contacts. Of these, 5,206 agreed to the visit, and 4,508 attended an in-person visit. Study Weblinks: nuMoM2b website Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-04-25 and may not include exact formatting or images."
+phs002910.v1.p1,c1,Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene),COVID19,2024-05-09,"Name: Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene), short name: C4R_COPDGENE_HMB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R.  Study Weblinks: C4RCOPDGene Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal CohortProspective    Total number of consented subjects: 4191    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs002910.v1.p1,c2,Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene),COVID19,2024-05-09,"Name: Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene), short name: C4R_COPDGENE_DS-CS.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R.  Study Weblinks: C4RCOPDGene Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal CohortProspective    Total number of consented subjects: 4191    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs002911.v1.p1,c1,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS), short name: C4R_FHS_HMB-IRB-MDS.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort DescriptionIn 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study, consisting of 506 participants, was enrolled. In April 2002 4095 third generation of participants, the grandchildren of the original cohort, were added. In 2003, 103 spouses of the offspring Cohort (NOS), and a second group of 410 Omni participants were enrolled. Through 2019, the original cohort has completed a total of 32 exams, the Offspring cohort 9 exams, the OMNI1 cohort 4 exams, and GEN3, NOS and OMNI2 cohorts each have completed 3 exams. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University.Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 3112 FHS participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 2337 FHS participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 2189 FHS participants in C4R.Derived data includes 43 variables for up to 3151 FHS participants in C4R.Phenotype data includes 113 variables for up to 3151 FHS participants in C4R. Study Weblinks: Collaborative Cohort of Cohorts for COVID-19 Research, (C4R)Framingham Heart Study (FHS) Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 7270    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002911.v1.p1,c2,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS), short name: C4R_FHS_HMB-IRB-NPU-MDS.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort DescriptionIn 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study, consisting of 506 participants, was enrolled. In April 2002 4095 third generation of participants, the grandchildren of the original cohort, were added. In 2003, 103 spouses of the offspring Cohort (NOS), and a second group of 410 Omni participants were enrolled. Through 2019, the original cohort has completed a total of 32 exams, the Offspring cohort 9 exams, the OMNI1 cohort 4 exams, and GEN3, NOS and OMNI2 cohorts each have completed 3 exams. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University.Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 3112 FHS participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 2337 FHS participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 2189 FHS participants in C4R.Derived data includes 43 variables for up to 3151 FHS participants in C4R.Phenotype data includes 113 variables for up to 3151 FHS participants in C4R. Study Weblinks: Collaborative Cohort of Cohorts for COVID-19 Research, (C4R)Framingham Heart Study (FHS) Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 7270    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002913.v1.p1,c1,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP), short name: C4R_SARP_GRU-PUB-NPU.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted  Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4RSARP Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 479    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002913.v1.p1,c2,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP), short name: C4R_SARP_GRU-PUB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted  Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4RSARP Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 479    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002913.v1.p1,c3,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP), short name: C4R_SARP_DS-AAI-PUB-NPU.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted  Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4RSARP Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 479    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002913.v1.p1,c4,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP), short name: C4R_SARP_DS-AAI-PUB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted  Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4RSARP Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 479    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002919.v1.p1,c1,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): REasons for Geographic and Racial Differences in Stroke (REGARDS),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): REasons for Geographic and Racial Differences in Stroke (REGARDS), short name: C4R_REGARDS_HMB-IRB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort DescriptionThe REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort is one of the nation's largest, most comprehensive population-based cohorts, and it uses innovative home- and telephone-based data collection. REGARDS centrally recruited and initially examined 30,239 Black and White men and women aged ≥45 years in 2003-7 to understand why Southerners and Black Americans have a higher incidence of stroke and related diseases that affect brain health.Data Being Submitted  Wave 1 questionnaire data includes 397 variables for 8109 REGARDS participants in C4R. Wave 2 questionnaire data includes 448 variables for 6421 REGARDS participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for 4058 REGARDS participants in C4R. Derived data includes 43 variables for 8606 REGARDS participants in C4R. Phenotype data includes 113 variables for 7880 REGARDS participants in C4R.  Study Weblinks: 1) C4R: www.c4r-nih.org2) REGARDS: https://www.uab.edu/soph/regardsstudy/ Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 8707    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002975.v1.p1,c1,Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Prevent Pulmonary Fibrosis (PrePF),COVID19,2024-05-09,"Name: Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Prevent Pulmonary Fibrosis (PrePF), short name: C4R_PREPF_DS-PMD-IRB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description Prevent Pulmonary Fibrosis (PrePF) has been investigating the clinical, physiologic and genetic phenotypes of interstitial lung disease (ILD) by focusing on families with two or more cases of ILD and individuals with sporadic IPF. It has recruited over 1,200 families with two or more cases of pulmonary fibrosis. These families with pulmonary fibrosis include 2,837 individuals with probable or definite idiopathic interstitial pneumonia (IIP) and 2,404 unaffected FDRs. In addition, PrePF recruited over 10,000 individuals with sporadic idiopathic pulmonary fibrosis (IPF). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 585 PrePF participants in C4R Wave 2 questionnaire data includes 448 variables for up to 370 PrePF participants in C4R Dried Blood Spot/Serosurvey data includes 7 variables for up to 206 PrePF participants in C4R Derived data includes 43 variables for up to 585 PrePF participants in C4R Phenotype data includes 113 variables for up to 585 PrePF participants in C4R  Study Weblinks: C4R Study Design:     Prospective Longitudinal Cohort Study Type:    Total number of consented subjects: 628    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs002988.v1.p1,c1,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R)- Atherosclerosis Risk in Communities (ARIC),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R)- Atherosclerosis Risk in Communities (ARIC), short name: C4R_ARIC_HMB-IRB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Atherosclerosis Risk in Communities (ARIC) study began in the mid-1980s with the initial aims being to describe the presence of subclinical atherosclerosis, the progression of atherosclerosis to clinical cardiovascular disease (CVD), and the association of novel risk factors with CVD. ARIC recruited its cohort of men and women aged 45-64 in 1987-89 from four communities (Forsyth County, NC; Jackson, MS; suburban Minneapolis, MN; and Washington County, MD). As of 2020, ARIC counts over 6,000 participants.Data Submitted Wave 1 questionnaire data includes 397 variables for up to 5326 ARIC participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 4619 ARIC participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 2083 ARIC participants in C4R. Derived data includes 43 variables for up to 5449 ARIC participants in C4R. Phenotype data includes 113 variables for up to 5449 ARIC participants in C4R.  Study Weblinks: C4R:https://c4r-nih.org/ARIC:https://sites.cscc.unc.edu/aric/desc_pub Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 6523    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs002988.v1.p1,c2,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R)- Atherosclerosis Risk in Communities (ARIC),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R)- Atherosclerosis Risk in Communities (ARIC), short name: C4R_ARIC_DS-CVD-IRB.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Atherosclerosis Risk in Communities (ARIC) study began in the mid-1980s with the initial aims being to describe the presence of subclinical atherosclerosis, the progression of atherosclerosis to clinical cardiovascular disease (CVD), and the association of novel risk factors with CVD. ARIC recruited its cohort of men and women aged 45-64 in 1987-89 from four communities (Forsyth County, NC; Jackson, MS; suburban Minneapolis, MN; and Washington County, MD). As of 2020, ARIC counts over 6,000 participants.Data Submitted Wave 1 questionnaire data includes 397 variables for up to 5326 ARIC participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 4619 ARIC participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 2083 ARIC participants in C4R. Derived data includes 43 variables for up to 5449 ARIC participants in C4R. Phenotype data includes 113 variables for up to 5449 ARIC participants in C4R.  Study Weblinks: C4R:https://c4r-nih.org/ARIC:https://sites.cscc.unc.edu/aric/desc_pub Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 6523    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs003028.v1.p1,c1,The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Northern Manhattan Study (NOMAS),COVID19,2024-05-09,"Name: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Northern Manhattan Study (NOMAS), short name: C4R_NOMAS_GRU.","Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects.Cohort Description The Northern Manhattan Study (NOMAS) is a study of the population of Washington Heights in Northern Manhattan. The ongoing study, which began in 1990, has enrolled over 4,400 people, some of whom have suffered a stroke or related neurological syndromes. As the cohort aged, the specific aims grew to include not only vascular determinants of stroke but also cognitive decline, mild cognitive impairment (MCI) and dementia. The overall goal of NOMAS is to investigate stroke risk factors in different race-ethnic groups. NOMAS is also committed to developing better stroke prevention programs to improve the health of the community. The Hispanic population in Northern Manhattan is largely Dominican, along with Puerto Rican, Cuban, and Central and South American components.Data Being Submitted  Wave 1 questionnaire data includes 397 variables for up to 887 NOMAS participants in C4R Wave 2 questionnaire data includes 448 variables for up to 815 NOMAS participants in C4R Derived data includes 43 variables for up to 995 NOMAS participants in C4R Phenotype data includes 113 variables for up to 995 NOMAS participants in C4R   Study Weblinks: C4RNOMAS Study Design:     Prospective Longitudinal Cohort Study Type:    Total number of consented subjects: 995    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-11-14 and may not include exact formatting or images."
+phs003063.v1.p1,c1,COVID-19 Post-hospital Thrombosis Prevention Study (ACTIV-4C),COVID19,2024-05-09,"Name: COVID-19 Post-hospital Thrombosis Prevention Study (ACTIV-4C), short name: ACTIV4C_GRU.","This study is an adaptive, prospective, randomized trial designed to compare the effectiveness and safety of antithrombotic therapy with no antithrombotic therapy after hospitalization for 48 hours or longer for COVID-19. For Stage 1 of this study, participants will be randomized to either prophylactic anticoagulation or no anticoagulant therapy for 30 days, and then followed for an additional 60 days after the completion of treatment (total duration of follow-up, approximately 90 days). Biobanking of samples for future biomarker and mechanistic studies will be available for centers able to participate and collect samples from eligible participants. Samples will be collected at the time of enrollment and after the completion of 30 days of therapy. Study Weblinks: Clinical Trials Study Design:     Interventional Study Type:Clinical TrialDouble-BlindInterventionalPlacebo-ControlledRandomizedRandomized Controlled Clinical TrialSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-01 and may not include exact formatting or images."
+phs003212.v1.p1,c1,Complement Inhibition Using Eculizumab to Overcome Platelet Transfusion Refractoriness in Patients with Severe Thrombocytopenia (DIR-Eculizumab_GRU),DIR,2024-05-09,"Name: Eculizumab_GRU, short name: Eculizumab_GRU.","Platelet transfusion can be a life-saving procedure in preventing or treating serious bleeding in patients who have low and/or dysfunctional platelets. Heavily transfused patients frequently develop human leukocyte antigen (HLA) allo-immunization resulting in platelet transfusion refractoriness and a high risk for life-threatening thrombocytopenia. Data suggest complement activation leading to the destruction of platelets bound by HLA allo-antibodies may play a pathophysiologic role in platelet refractoriness. We conducted a pilot trial to investigate the use of eculizumab to treat platelet transfusion refractoriness in allo-immunized patients with severe thrombocytopenia. We hypothesized that when we treated patients having platelet refractoriness with eculizumab, platelet counts would increase to higher numbers after platelet transfusions, decreasing the risk of bleeding complications associated with having a low platelet count. The response of the treatment was assessed by the corrected platelet count increment (CCI) 10 - 60 min and 18 - 24 h post transfusion, and any requirement for subsequent platelet transfusions following eculizumab. Reference 1 (PMID: 32086819) contains the main results for this trial.  Study Design:     Clinical Trial Study Type:Clinical TrialSubject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2023-06-01 and may not include exact formatting or images."
+phs003231.v1.p1,c1,ApoA-1 and Atherosclerosis in Psoriasis (DIR),DIR,2024-05-09,"Name: ApoA-1 and Atherosclerosis in Psoriasis (DIR), short name: ApoA-1_Atherosclerosis_in_Psoriasis_GRU.","Apolipoprotein A-1 is a protein localized to high-density lipoprotein that functions to remove cholesterol from tissues for transport back to the liver. Psoriasis is a systemic inflammatory disease associated with poor high-density lipoprotein function and accelerated non-calcified burden by coronary computed tomographic angiography. In this study, 310 psoriasis patients from The Psoriasis, Atherosclerosis, and Cardiometabolic Disease Initiative (PACI) were studied at baseline to determine if levels of circulating apolipoprotein A-1 predict early onset coronary artery disease in inflammatory conditions. Of the 310 participants, 124 were followed for four years to determine if apolipoprotein A-1 predicts non-calcified coronary burden over time. The primary outcome of this study was non-calcified coronary burden by coronary computed tomography angiography. To assess non-calcified coronary burden, participants underwent coronary computed tomography angiography using the same scanner (320-detector row Aquilion ONE ViSION, Toshiba, Japan). For ApoA-1 quantification, fasting blood draw was performed the same day as the coronary computed tomography angiography. The 400MHz proton Vantera Clinical Analyzer was used to quantify Plasma apolipoprotein A-1. The study determined that low levels of apolipoprotein A-1 are associated with increased coronary artery burden and that this relationship persists over time. The data are available through dbGaP and the dataset includes all variables reported in the manuscript.     Study Design:     Prospective Longitudinal Cohort Study Type:LongitudinalLongitudinal CohortProspective    Total number of consented subjects: 310    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-01-22 and may not include exact formatting or images."
+phs003288.v1.p1,c1,Multi-Ethnic Study of Atherosclerosis (BioLINCC),BioLINCC,2024-05-09,"Name: Multi-Ethnic Study of Atherosclerosis (BioLINCC), short name: BL_MESA_HMB.","The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent.Data available for request include data from exam 1 through exam 5 and events data updated through calendar year 2015. Also included are data from eleven ancillary studies: #079 (NT-ProBNP and Troponin), #042 (Epidemiology of Vascular Inflammation and Atherosclerosis), #081 (Apolipoproteins B and A-1), #067 (MRI RV-Function), #057 (Cystatin-C), #244 (NT Pro-BNP and HS Cardiac Troponin-T), #205 (Brachial IMT), #113 (Exam 5 Sleep), #047/075 (Vitamin D), #195 (Fatty Acid), #200 (Total FFA), #324 (Lipoprotein A), #023 (Neighborhood Racial Segregation), and #118 (Stress Cortisol)."
+phs003288.v1.p1,c2,Multi-Ethnic Study of Atherosclerosis (BioLINCC),BioLINCC,2024-05-09,"Name: Multi-Ethnic Study of Atherosclerosis (BioLINCC), short name: BL_MESA_HMB-NPU.","The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent.Data available for request include data from exam 1 through exam 5 and events data updated through calendar year 2015. Also included are data from eleven ancillary studies: #079 (NT-ProBNP and Troponin), #042 (Epidemiology of Vascular Inflammation and Atherosclerosis), #081 (Apolipoproteins B and A-1), #067 (MRI RV-Function), #057 (Cystatin-C), #244 (NT Pro-BNP and HS Cardiac Troponin-T), #205 (Brachial IMT), #113 (Exam 5 Sleep), #047/075 (Vitamin D), #195 (Fatty Acid), #200 (Total FFA), #324 (Lipoprotein A), #023 (Neighborhood Racial Segregation), and #118 (Stress Cortisol)."
+phs003419.v1.p1,c1,Prevention and Early Treatment of Acute Lung Injury (PETAL) Network: Biology and Longitudinal Epidemiology of PETAL COVID-19 Observational Study (BLUE CORAL),COVID19,2024-05-09,"Name: BLUE_CORAL_HMB, short name: BLUE_CORAL_HMB.","The BLUE CORAL study is a research study that is collecting information to learn more about SARS-CoV-2, the virus that causes COVID-19, and how to better care for people who are sick from COVID-19. BLUE CORAL is a detailed prospective cohort study of patients hospitalized with acute SARS-CoV2 infection at PETAL Network hospitals. The primary objective of BLUE CORAL is to describe the clinical characteristics, treatments, biology and outcomes of 1500 hospitalized patients with Covid-19. In addition to all hospital data collected in RED CORAL, BLUE CORAL adds (1) in-hospital surveys detailing premorbid function, (2) biospecimen collection, and (3) centralized post-hospital telephone follow-up at 1, 3 and 6 months after hospital discharge."
+phs003463.v1.p1,c1,Adult Observational Cohort Study (RECOVER-RC_Adult),RECOVER,2024-05-09,"Name: Adult Observational Cohort Study (RECOVER-RC_Adult), short name: RC_Adult_GRU.","The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal, observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients with and without known SARS-CoV-2 infection will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows: Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection. Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection.Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs:1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. 2) The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study: A Multi-Center Observational StudyThe RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization.3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.  Study Weblinks: NIH RECOVER Study Design:     Prospective Longitudinal Cohort Study Type:Longitudinal Cohort    Total number of consented subjects: 14662    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs003470.v1.p1,c1,Blood and Marrow Transplant Clinical Trials Network - Unrelated Donor Reduced Intensity Bone Marrow Transplant for Children With Severe Sickle Cell Disease (BMT_CTN-0601),BioLINCC,2024-05-09,"Name: Blood and Marrow Transplant Clinical Trials Network - Unrelated Donor Reduced Intensity Bone Marrow Transplant for Children With Severe Sickle Cell Disease (BMT_CTN-0601), short name: BMT_CTN-0601_GRU.","ObjectivesThe primary objective is to determine event-free survival (EFS) at 1 year after unrelated donor (URD) hematopoietic stem cell transplantation (HCT) using bone marrow (BM) in patients with sickle cell disease (SCD).BackgroundSickle cell disease (SCD), also known as sickle cell anemia, is an inherited blood disease that can cause organ damage, stroke, and intense pain episodes. Children with sickle cell disease experience organ damage, impaired quality of life, and premature mortality. A blood stem cell transplant is a treatment option for someone with a severe form of the disease. Prior to undergoing a transplant, people typically receive a conditioning regimen of high doses of chemotherapy and other medications to prepare the body to accept the transplant. This type of conditioning regimen is known as a myeloablative conditioning regimen, but it can result in toxicities and sterility. A conditioning regimen that uses lower doses of chemotherapy and medications may be safer for transplant recipients. This type of regimen is known as reduced intensity conditioning (RIC) regimen. RIC has a more favorable toxicity profile but is associated with higher rates of graft rejection (GR), especially with graft sources such as umbilical cord blood This study evaluated the safety and effectiveness of blood stem cell transplants, using bone marrow from unrelated donors, in children with severe SCD who receive a RIC regimen prior to the transplant.SubjectsPatients 3.0-19.75 years old with symptomatic SCD AND one or more of the following complications: (1)-(i) a clinically significant neurologic event (stroke) or any neurologic defect lasting > 24 hours and accompanied by an infarct on cerebral magnetic resonance imaging (MRI); OR, (ii) patients who have a Transcranial Doppler (TCD) velocity that exceeds 200 cm/sec by the non-imaging technique (or TCD measurement of >185 cm/sec by the imaging technique) measured at a minimum of 2 separate occasions one month or more apart; OR, (2) Minimum of two episodes of acute chest syndrome within the preceding 2-year period defined as new pulmonary alveolar consolidation involving at least one complete lung segment (associated with acute symptoms including fever, chest pain, tachypnea, wheezing, rales, or cough that is not attributed to asthma or bronchiolitis) despite adequate supportive care measures; OR, (3) History of 3 or more severe pain events (defined as new onset of pain that lasts for at least 2 hours for which there is no other explanation) per year in the 2 years prior to enrollment despite adequate supportive care measures (if patients are receiving hydroxyurea and compliant with therapy, being symptomatic is an indication for transplantation; however, if patients decline hydroxyurea or non-compliant with this therapy, they would still remain eligible for study if pain criteria as described above are met). Lansky/Karnofsky performance score must be ≥ 40. Hemoglobin S must be ≤ 45%. Patients must have an unrelated adult bone marrow donor who is HLA-matched at 8 of 8 HLA-A, -B, -C and -DRB1 at high resolution using DNA-based typing. Patients with bridging fibrosis or cirrhosis of the liver, with uncontrolled bacterial, viral, or fungal infection in the past month, or seropositivity for HIV are excluded. Patients with HLA-matched family donors, or who have received prior HCT, and females who are pregnant or breast feeding are excluded. Thirty patients were enrolled on this study and of these, 29 patients met the criteria and proceeded to the study transplant.DesignParticipants attended a study visit prior to the transplant to undergo a blood collection, neurocognitive testing to measure learning and brain function, magnetic resonance angiogram (MRA) and magnetic resonance imaging (MRI) scans. Questionnaires to assess quality of life were also completed. All patients received erythrocyte transfusions before transplant. Twenty-two days (-22) before the transplant, participants began receiving a reduced intensity conditioning regimen of chemotherapy and medications. On days -21, -20, and -19 participants weighing 10 kg or more received 10 mg, 15 mg, and then 20 mg of Alemtuzumab intravenously (IV) followed by 30 mg/m2/day IV on days -8 through -4 of Fludarabine. Eight days (-8) before the transplant, participants were admitted to the hospital to continue the conditioning regimen which included 140 mg/m2 IV of Melphalan on day -3. Participants received the bone marrow transplant on day 0. Prophylaxis for GVHD consisted of a calcineurin inhibitor (tacrolimus or cyclosporine) administered from day -3 through day 100 after graft infusion, with subsequent taper through day 180; methotrexate 7.5 mg/m2 on days 1, 3, and 6; and methylprednisolone 1 mg/kg per day from days 7 through 28, with subsequent taper by 20% per week. One week after the transplant continuing until the WBC is normal, participants received granulocyte-colony-stimulating factor (G-CSF). After leaving the hospital, participants attended study visits weekly during weeks 1 to 8, at day 60, weekly during weeks 9 to 14, at Day 100, at month 6, and at years 1 and 2. At all study visits, a blood collection, medical history review, and physical exam occurred. In addition, at day 100, month 6, and years 1 and 2, questionnaires to assess quality of life were completed. At select visits the following procedures were conducted: lung function testing, heart function testing, MRA and MRI scans, and neurocognitive testing.The primary outcome was 1-year EFS. Death, disease recurrence or graft rejection by 1 year were considered events for this endpoint.ConclusionsThe trial met its prespecified 1-year EFS, and significantly improved HRQL was reported posttransplant. However, although the Reduced-intensity conditioning (RIC) provided successful engraftment in most patients, the regimen cannot be considered safe for widespread adoption without modification due to the regimen-related toxicity (RRT) and high rate of chronic GVHD, which was the predominant cause of mortality. Study Weblinks: BMT CTN Study Design:     Clinical Trial Study Type:Clinical Trial    Total number of consented subjects: 55    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs003524.v1.p1,c1,Heart Failure Network (HFN) Diuretic Optimization Strategies Evaluation (DOSE) in Acute Heart Failure (BioLINCC-BL_HFN_DOSE_AHF),BioLINCC,2024-05-09,"Name: Heart Failure Network (HFN) Diuretic Optimization Strategies Evaluation (DOSE) in Acute Heart Failure (BioLINCC-BL_HFN_DOSE_AHF), short name: BL_HFN_DOSE_AHF_GRU.","ObjectivesThe DOSE study sought to evaluate the most effective dosing (high vs. low) and administration (continuous infusion vs. intermittent boluses) combination of the diuretic Furosemide in the treatment of patients with acute decompensated heart failure.BackgroundAcute decompensated heart failure is the most common cause of hospital admissions among patients older than 65 years of age and is responsible for more than 1 million hospitalizations annually in the United States. Intravenous loop diuretics are an essential component of current treatment and are administered to approximately 90% of patients who are hospitalized with heart failure. Despite decades of clinical experience with these agents, prospective data to guide the use of loop diuretics are sparse, and current guidelines are based primarily on expert opinion. As a result, clinical practice varies widely with regard to both the mode of administration and the dosing.SubjectsA total of 308 patients were enrolled between March 2008 and November 2009 at 26 clinical sites in the United States and Canada. DesignThe DOSE study was a prospective, randomized, double-blind, controlled trial with a 2-by-2 factorial design. Patients were randomly assigned to either a low-dose strategy (total intravenous furosemide dose equal to their total daily oral loop diuretic dose in furosemide equivalents) or a high-dose strategy (total daily intravenous furosemide dose 2.5 times their total daily oral loop diuretic dose in furosemide equivalents) and to administration of furosemide either by intravenous bolus every 12 hours or by continuous intravenous infusion.The study treatment, with group assignments concealed, was continued for up to 72 hours. At 48 hours, the treating physician had the option of adjusting the diuretic strategy on the basis of the clinical response. An assessment of biomarkers, including creatinine, cystatin C, and N-terminal pro-brain natriuretic peptide, was performed at a central core laboratory at baseline, 72 hours, and 60 days. Patients were followed for clinical events to day 60. The coprimary end points were patients' global assessment of symptoms, quantified as the area under the curve (AUC) of the score on a visual-analogue scale over the course of 72 hours, and the change in the serum creatinine level from baseline to 72 hours.ConclusionsAmong patients with acute decompensated heart failure, there were no significant differences in patients' global assessment of symptoms or in the change in renal function when diuretic therapy was administered by bolus as compared with continuous infusion or at a high dose as compared with a low dose. (Felker et. al., 2011, PMID: 21366472) Study Weblinks: BioLINCC HFN-DOSE study page Study Design:     Clinical Trial Study Type:Clinical Trial    Total number of consented subjects: 308    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs003533.v1.p1,c1,Heart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure Patients (HFN EXACT-BioLINCC),BioLINCC,2024-05-09,"Name: Heart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure Patients (HFN EXACT-BioLINCC), short name: BL_HFN_EXACT-HF_GRU.","ObjectivesTo determine the effect of allopurinol after 24 weeks on a composite clinical endpoint that classifies subject's clinical status (improved, worsened, unchanged) in patients with heart failure and high uric acid levels.BackgroundMorbidity and mortality rates for patients with heart failure are high, despite guideline-recommended therapy. Heart failure is characterized by an imbalance between left ventricular (LV) performance and myocardial energy consumption. There is a growing body of evidence that suggests oxidative stress contributes to ventricular and vascular remodeling, and disease progression in heart failure. Targeting potential source(s) of oxidative stress, e.g. Xanthine oxidase (XO), was the focus of recent clinical trials and epidemiological studies. Increased XO activity has been shown to lead to production of superoxide and uric acid (UA). Serum uric acid levels are included in heart failure risk scores, and hyperuricemia is present in about 25% of patients with heart failure. Hyperuricemia is associated with exercise intolerance, reduced survival, and worsening symptoms. The EXACT-HF trial tested allopurinol, an inhibitor of XO, as a potential target therapy for hyperuricemic heart failure patients.Subjects253 subjects were enrolled in the EXACT-HF study. 128 participants were randomized to the allopurinol arm, and of those participants, 119 completed the trial and 9 did not. 125 participants were randomized to the placebo arm, and of those participants, 116 completed the trial and 9 did not.DesignEXACT-HF was a multi-center, double-blind, placebo controlled, 24-week trial of allopurinol. Eligible participants had to be receiving a stable regimen for at least two weeks (3 months for beta-blockers) prior to randomization. Participants were randomized by an automated system to either the allopurinol or placebo arm, and started treatment within 12 hours of completing the baseline visit. During the first week, participants in both treatment arms received 300mg daily of the respective medications. For the following 23 weeks, participants in both treatment arms received 600mg daily of the respective medications. Patients unable to tolerate 600 mg were maintained on 300 mg.The primary endpoint was a composite clinical endpoint (CCE) that classified a subject's clinical status as improved, worsened, or unchanged at 24 weeks. The CCE was determined based on the following: death; hospitalization, emergency room visit or emergent clinic visit for worsening HF; medication change for worsening HF; and Patient Global Assessment using a 7-point scale. Secondary endpoints at 12 and 24 weeks included changes in quality of life as assessed by the Kansas City Cardiomyopathy Questionnaire, and submaximal exercise capacity as assessed by a 6-minute walk test.ConclusionsParticipants who received allopurinol had significantly less serum uric acid laboratory levels after 24 weeks; however, no significant difference was observed in the primary and secondary endpoints between the allopurinol and placebo-treated patients. Therefore, in high-risk HF patients with reduced ejection fraction and elevated uric acid levels, xanthine oxidase inhibition with allopurinol failed to improve clinical status, exercise capacity, quality of life, or LVEF at 24 weeks (Circulation. 2015 May 19; 131(20):1763-71). Study Weblinks: BioLINCC Repository Study Design:     Clinical Trial Study Type:Clinical Trial    Total number of consented subjects: 253    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs003543.v1.p1,c1,National Sleep Research Resource (NSRR)- Hispanic Community Health Study (HCHS),NSRR,2024-05-09,"Name: National Sleep Research Resource (NSRR)- Hispanic Community Health Study (HCHS), short name: SR_HCHS_HMB-NPU.","The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH) contributed to the first phase of the project. Raw polysomnography data are available from the HCHS/SOL Baseline visit and raw actigraphy data are available from the Sueño Ancillary visit. Primary HCHS/SOL data can be requested through dbGaP phs000810 Hispanic Community Health Study /Study of Latinos (HCHS/SOL). Study Weblinks: Hispanic Community Health Study / Study of Latinos WebsiteNational Sleep Research Resource: Hispanic Community Health Study / Study of Latinos Study Design:     Prospective Longitudinal Cohort Study Type:Cohort    Total number of consented subjects: 12121    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
+phs003543.v1.p1,c2,National Sleep Research Resource (NSRR)- Hispanic Community Health Study (HCHS),NSRR,2024-05-09,"Name: National Sleep Research Resource (NSRR)- Hispanic Community Health Study (HCHS), short name: SR_HCHS_HMB.","The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH) contributed to the first phase of the project. Raw polysomnography data are available from the HCHS/SOL Baseline visit and raw actigraphy data are available from the Sueño Ancillary visit. Primary HCHS/SOL data can be requested through dbGaP phs000810 Hispanic Community Health Study /Study of Latinos (HCHS/SOL). Study Weblinks: Hispanic Community Health Study / Study of Latinos WebsiteNational Sleep Research Resource: Hispanic Community Health Study / Study of Latinos Study Design:     Prospective Longitudinal Cohort Study Type:Cohort    Total number of consented subjects: 12121    Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2024-04-02 and may not include exact formatting or images."
diff --git a/docker-compose.yaml b/docker-compose.yaml
index 8e8d27d2..664524d2 100644
--- a/docker-compose.yaml
+++ b/docker-compose.yaml
@@ -40,11 +40,9 @@ services:
       REDIS_PASSWORD: "$REDIS_PASSWORD"
       FLASK_ENV: "development"
       PYTHONUNBUFFERED: "TRUE"
-    entrypoint: [ "gunicorn",
-                     "--workers=$API_WORKERS", "--name=dug",
-                     "--bind=0.0.0.0:$API_PORT", "--timeout=$API_TIMEOUT",
-                     "--log-level=DEBUG", "--enable-stdio-inheritance",
-                     "-k", "uvicorn.workers.UvicornWorker", "--reload", "dug.server:APP" ]
+    entrypoint: [ "uvicorn",
+                     "--host", "0.0.0.0" , "--port" , "$API_PORT",
+                     "--log-level=debug",  "--reload-dir", "/home/dug/dug/",  "--reload", "dug.server:APP" ]
     volumes:
       - ./src:/home/dug/dug/
     ports:
diff --git a/requirements.txt b/requirements.txt
index 2bbadabe..694cf680 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -21,7 +21,7 @@ requests
 redis
 requests-cache
 six
-
+retrying
 # Click for command line arguments
 # We use Click 7.0 because that's what one of the pinned packages above use.
 click
diff --git a/src/dug/config.py b/src/dug/config.py
index b070cac1..c60ff4fc 100644
--- a/src/dug/config.py
+++ b/src/dug/config.py
@@ -27,6 +27,13 @@ class Config:
     nboost_host: str = "nboost"
     nboost_port: int = 8000
 
+    program_sort_list: str = ""
+    program_description: dict=field(default_factory=lambda:{})
+    consent_id_path: str= ""
+    missing_studies_path: str=""
+    missing_program_path: str=""
+    
+
     # Preprocessor config that will be passed to annotate.Preprocessor constructor
     preprocessor: dict = field(
         default_factory=lambda: {
@@ -43,8 +50,23 @@ class Config:
             },
             "sapbert": {
                 "classification_url": "https://med-nemo.apps.renci.org/annotate/",
-                "annotator_url": "https://babel-sapbert.apps.renci.org/annotate/",
-            },
+                "annotator_url": "https://sap-qdrant.apps.renci.org/annotate/",
+                "score_threshold": 0.5,
+                "bagel": {
+                    "enabled": True,
+                    "url": "https://bagel.apps.renci.org/group_synonyms_openai",
+                    "prompt": "bagel/ask_classes",
+                    "llm_args": {
+                        "llm_model_name": "gpt-4o-2024-05-13",
+                        "organization": "",
+                        "access_key": "",
+                        "llm_model_args": {
+                            "top_p": 0,
+                            "temperature": 0.1
+                        }
+                    }
+                }
+            }
         }
     )
 
@@ -137,6 +159,10 @@ def from_env(cls):
             "redis_host": "REDIS_HOST",
             "redis_port": "REDIS_PORT",
             "redis_password": "REDIS_PASSWORD",
+            "program_description": "PROGRAM_DESCRIPTION",
+            "consent_id_path": "CONSENT_ID_PATH",
+            "missing_studies_path": "MISSING_STUDIES_PATH",
+            "missing_program_path": "MISSING_PROGRAM_PATH"
         }
 
         kwargs = {}
diff --git a/src/dug/core/annotators/_base.py b/src/dug/core/annotators/_base.py
index 05890517..6d61d008 100644
--- a/src/dug/core/annotators/_base.py
+++ b/src/dug/core/annotators/_base.py
@@ -7,6 +7,7 @@
 from dug import utils as utils
 from requests import Session
 import bmt
+from retrying import retry
 
 logger = logging.getLogger("dug")
 
@@ -198,6 +199,7 @@ def __call__(self, curie: str, http_session):
         result = self.handle_response(curie, response)
         return result
 
+    @retry(stop_max_attempt_number=3)
     def make_request(self, curie: str, http_session: Session):
         # Get response from namelookup reverse lookup op
         # example (https://name-resolution-sri.renci.org/docs#/lookup/lookup_names_reverse_lookup_post)
diff --git a/src/dug/core/annotators/sapbert_annotator.py b/src/dug/core/annotators/sapbert_annotator.py
index 6f2c93a6..a58f860d 100644
--- a/src/dug/core/annotators/sapbert_annotator.py
+++ b/src/dug/core/annotators/sapbert_annotator.py
@@ -1,10 +1,10 @@
 import logging
-from typing import List
+from typing import List, Dict
 from requests import Session
-import json
-
+from retrying import retry
 from dug.core.annotators._base import DugIdentifier, Input
 from dug.core.annotators.utils.biolink_purl_util import BioLinkPURLerizer
+from functools import reduce
 
 logger = logging.getLogger("dug")
 
@@ -12,6 +12,45 @@
 logging.getLogger("urllib3").setLevel(logging.WARNING)
 
 
+class BagelWrapper:
+    def __init__(self, prompt_name, llm_args, url):
+        self.llm_args = llm_args
+        self.url = url
+        self.prompt_name = prompt_name
+
+    @retry(stop_max_attempt_number=3)
+    def __call__(self, description_text, entity, ids: List[DugIdentifier], http_session: Session):
+        response = self.make_request(description_text=description_text, entity=entity, ids=ids, http_session=http_session)
+        result = self.handle_response(ids, response)
+        return result
+
+    def make_request(self, description_text, entity, ids: List[DugIdentifier], http_session: Session):
+        url = self.url
+        if ids:
+            payload = {
+                "prompt_name": self.prompt_name,
+                "context": {
+                    "text": description_text,
+                    "entity": entity,
+                    "synonyms": [{
+                        "label": i.label,
+                        "identifier": i.id,
+                        "description": i.description,
+                        "entity_type": i.types.split(':')[-1],
+                        "color-code": "red"
+                    } for i in ids]
+                },
+                "config": self.llm_args
+            }
+            return http_session.post(self.url, json=payload).json()
+
+        return []
+
+    def handle_response(self, ids: List[DugIdentifier], bagel_json_result: dict):
+        selected_ids = [x['identifier'] for x in bagel_json_result]
+        return list(filter(lambda x: x.id in selected_ids, ids))
+
+
 class AnnotateSapbert:
     """
     Use the RENCI Sapbert API service to fetch ontology IDs found in text
@@ -26,6 +65,7 @@ def __init__(
     ):
         self.classificationUrl = kwargs.get('classification_url')
         self.annotatorUrl = kwargs.get('annotator_url')
+
         if not self.classificationUrl:
             raise TypeError('Classification url needs to be defined for sapbert annotator')
         if not self.annotatorUrl:
@@ -35,46 +75,72 @@ def __init__(
         self.ontology_greenlist = ontology_greenlist
         self.norm_fails_file = "norm_fails.txt"
         self.anno_fails_file = "anno_fails.txt"
+        # threshold marking cutoff point
+        self.score_threshold = float(kwargs.get("score_threshold", 0.8))
+        # indicate if we want values above or below the threshold.
+        self.score_direction_up = True if kwargs.get("score_direction", "up") == "up" else False
+
+        self.bagel_args = kwargs.get("bagel")
+        if self.bagel_args:
+            self.bagel_enabled = self.bagel_args['enabled']
+            self.bagel = BagelWrapper(
+                prompt_name=self.bagel_args["prompt"],
+                llm_args= self.bagel_args["llm_args"],
+                url=self.bagel_args["url"]
+            )
+        else:
+            self.bagel_enabled = False
 
+    @retry(stop_max_attempt_number=3)
     def __call__(self, text, http_session) -> List[DugIdentifier]:
         # Fetch identifiers
         classifiers: List = self.text_classification(text, http_session)
 
-        raw_identifiers: List[DugIdentifier] = self.annotate_classifiers(
+        raw_identifiers_dict: Dict[str, DugIdentifier] = self.annotate_classifiers(
             classifiers, http_session
         )
 
         # Write out to file if text fails to annotate
-        if not raw_identifiers:
+        if not raw_identifiers_dict:
             with open(self.anno_fails_file, "a") as fh:
                 fh.write(f"{text}\n")
 
-        processed_identifiers = []
-        for identifier in raw_identifiers:
-            # Normalize identifier using normalization service
-            norm_id = self.normalizer(identifier, http_session)
+        processed_identifiers = {}
+        for entity, raw_identifiers in raw_identifiers_dict.items():
+            # normalize all ids
+            for identifier in raw_identifiers:
+                # Normalize identifier using normalization service
+                norm_id = self.normalizer(identifier, http_session)
 
-            # Skip adding id if it doesn't normalize
-            if norm_id is None:
-                # Write out to file if identifier doesn't normalize
-                with open(self.norm_fails_file, "a") as fh:
-                    fh.write(f"{identifier.id}\n")
+                # Skip adding id if it doesn't normalize
+                if norm_id is None:
+                    # Write out to file if identifier doesn't normalize
+                    with open(self.norm_fails_file, "a") as fh:
+                        fh.write(f"{identifier.id}\n")
 
-                # Discard non-normalized ident if not in greenlist
-                if identifier.id_type not in self.ontology_greenlist:
-                    continue
+                    # Discard non-normalized ident if not in greenlist
+                    if identifier.id_type not in self.ontology_greenlist:
+                        continue
 
-                # If it is in greenlist just keep moving forward
-                norm_id = identifier
+                    # If it is in greenlist just keep moving forward
+                    norm_id = identifier
 
-            # Add synonyms to identifier
-            norm_id.synonyms = self.synonym_finder(norm_id.id, http_session)
+                # Add synonyms to identifier
+                norm_id.synonyms = self.synonym_finder(norm_id.id, http_session)
 
-            # Get pURL for ontology identifer for more info
-            norm_id.purl = BioLinkPURLerizer.get_curie_purl(norm_id.id)
-            processed_identifiers.append(norm_id)
+                # Get pURL for ontology identifer for more info
+                norm_id.purl = BioLinkPURLerizer.get_curie_purl(norm_id.id)
+                processed_identifiers[entity] = processed_identifiers.get(entity, [])
+                processed_identifiers[entity].append(norm_id)
 
-        return processed_identifiers
+
+            # filter using bagel
+            if self.bagel_enabled:
+                processed_identifiers[entity] = self.bagel(description_text=text,
+                                                           entity=entity,
+                                                           ids=processed_identifiers.get(entity, []),
+                                                           http_session=http_session)
+        return reduce(lambda bucket, key: bucket + processed_identifiers[key], processed_identifiers, [])
 
     def text_classification(self, text, http_session) -> List:
         """
@@ -132,13 +198,13 @@ def handle_classification_response(self, response: dict) -> List:
             text = denotation.get("text", None)
             bl_type = denotation.get("obj", None)
             classifiers.append(
-                {"text": text, "bl_type": bl_type.replace("biolink:", "")}
+                {"text": text, "bl_type": bl_type}
             )
         return classifiers
 
     def annotate_classifiers(
         self, classifiers: List, http_session
-    ) -> List[DugIdentifier]:
+    ) -> Dict[str, DugIdentifier]:
         """
         Send Classified Terms to Sapbert API
 
@@ -170,12 +236,12 @@ def annotate_classifiers(
           TBD: Organize the results by highest score
           Return: List of DugIdentifiers with a Curie ID
         """
-        identifiers = []
+        identifiers = {}
         for term_dict in classifiers:
             logger.debug(f"Annotating: {term_dict['text']}")
 
             response = self.make_annotation_request(term_dict, http_session)
-            identifiers += self.handle_annotation_response(term_dict, response)
+            identifiers[term_dict['text']] =  self.handle_annotation_response(term_dict, response)
 
         return identifiers
 
@@ -184,8 +250,8 @@ def make_annotation_request(self, term_dict: Input, http_session: Session):
         payload = {
             "text": term_dict["text"],
             "model_name": "sapbert",
-            "count": 1000,
-            "args": {"bl_type": term_dict["bl_type"]},
+            "count": 10,
+            # "args": {"bl_type": term_dict["bl_type"]},
         }
         # This could be moved to a config file
         NUM_TRIES = 5
@@ -213,36 +279,14 @@ def handle_annotation_response(self, value, response: dict) -> List[DugIdentifie
                 continue
 
             biolink_type = identifier.get('category')
-            score = identifier.get("score", None)
+            score = float(identifier.get("score", 0))
             label = identifier.get("name")
-            identifiers.append(
-                DugIdentifier(id=curie, label=label, types=[biolink_type], search_text=search_text)
-            )
+            if score >= self.score_threshold and self.score_direction_up:
+                identifiers.append(
+                    DugIdentifier(id=curie, label=label, types=[biolink_type], search_text=search_text)
+                )
+            elif score <= self.score_threshold and not self.score_direction_up:
+                identifiers.append(
+                    DugIdentifier(id=curie, label=label, types=[biolink_type], search_text=search_text)
+                )
         return identifiers
-
-## Testing Purposes
-# if __name__ == "__main__":
-#     from dug.config import Config
-#     import json
-#     import redis
-#     from requests_cache import CachedSession
-#     from dug.core.annotators._base import DefaultNormalizer, DefaultSynonymFinder
-
-#     config = Config.from_env()
-#     annotator = AnnotateSapbert(
-#         normalizer=DefaultNormalizer(**config.normalizer),
-#         synonym_finder=DefaultSynonymFinder(**config.synonym_service),
-#     )
-
-#     redis_config = {
-#         "host": "localhost",
-#         "port": config.redis_port,
-#         "password": config.redis_password,
-#     }
-
-#     http_sesh = CachedSession(
-#         cache_name="annotator",
-#         backend="redis",
-#         connection=redis.StrictRedis(**redis_config),
-#     )
-#     annotator(text="Have you ever had a heart attack?", http_session=http_sesh)
diff --git a/src/dug/core/async_search.py b/src/dug/core/async_search.py
index b39e6a95..e0f8f79d 100644
--- a/src/dug/core/async_search.py
+++ b/src/dug/core/async_search.py
@@ -1,12 +1,11 @@
 """Implements search methods using async interfaces"""
-
 import logging
 from elasticsearch import AsyncElasticsearch
 from elasticsearch.helpers import async_scan
-import ssl
-
+import ssl,json
 from dug.config import Config
 
+
 logger = logging.getLogger('dug')
 
 
@@ -111,107 +110,109 @@ async def agg_data_type(self):
         return data_type_list
 
     @staticmethod
-    def _build_concepts_query(query, fuzziness=1, prefix_length=3):
+    def _get_concepts_query(query, fuzziness=1, prefix_length=3):
         "Static data structure populator, pulled for easier testing"
         query_object = {
-            "bool": {
-                "filter": {
-                    "bool": {
-                        "must": [
-                            {"wildcard": {"description": "?*"}},
-                            {"wildcard": {"name": "?*"}}
-                        ]
-                    }
-                },
-                "should": [
-                    {
-                        "match_phrase": {
-                            "name": {
-                                "query": query,
-                                "boost": 10
-                            }
+            "query" : {
+                "bool": {
+                    "filter": {
+                        "bool": {
+                            "must": [
+                                {"wildcard": {"description": "?*"}},
+                                {"wildcard": {"name": "?*"}}
+                            ]
                         }
                     },
-                    {
-                        "match_phrase": {
-                            "description": {
-                                "query": query,
-                                "boost": 6
+                    "should": [
+                        {
+                            "match_phrase": {
+                                "name": {
+                                    "query": query,
+                                    "boost": 10
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match_phrase": {
-                            "search_terms": {
-                                "query": query,
-                                "boost": 8
+                        },
+                        {
+                            "match_phrase": {
+                                "description": {
+                                    "query": query,
+                                    "boost": 6
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match": {
-                            "name": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 4
+                        },
+                        {
+                            "match_phrase": {
+                                "search_terms": {
+                                    "query": query,
+                                    "boost": 8
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match": {
-                            "search_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 5
+                        },
+                        {
+                            "match": {
+                                "name": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "operator": "and",
+                                    "boost": 4
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match": {
-                            "description": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 3
+                        },
+                        {
+                            "match": {
+                                "search_terms": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "operator": "and",
+                                    "boost": 5
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match": {
-                            "description": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 2
+                        },
+                        {
+                            "match": {
+                                "description": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "operator": "and",
+                                    "boost": 3
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match": {
-                            "search_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 1
+                        },
+                        {
+                            "match": {
+                                "description": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "boost": 2
+                                }
                             }
-                        }
-                    },
-                    {
-                        "match": {
-                            "optional_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length
+                        },
+                        {
+                            "match": {
+                                "search_terms": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "boost": 1
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "optional_terms": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length
+                                }
                             }
                         }
-                    }
-                ],
-                "minimum_should_match": 1,
+                    ],
+                    "minimum_should_match": 1,
+                }
             }
         }
         return query_object
@@ -221,9 +222,11 @@ async def search_concepts(self, query, offset=0, size=None, types=None,
         """
         Changed to a long boolean match query to optimize search results
         """
-        query_dict = self._build_concepts_query(query, **kwargs)
+        if "*" in query or "\"" in query or "+" in query or "-" in query:
+            search_body = self.get_simple_search_query(query)
+        else:
+            search_body = self._get_concepts_query(query, **kwargs)
         # Get aggregated counts of biolink types
-        search_body = {"query": query_dict}
         search_body['aggs'] = {'type-count': {'terms': {'field': 'type'}}}
         if isinstance(types, list):
             search_body['post_filter'] = {
@@ -283,185 +286,26 @@ async def search_variables(self, concept="", query="", size=None,
         If a data_type is passed in, the result will be filtered to only contain
         the passed-in data type.
         """
-        query = {
-            'bool': {
-                'should': {
-                    "match": {
-                        "identifiers": concept
-                    }
-                },
-                'should': [
-                    {
-                        "match_phrase": {
-                            "element_name": {
-                                "query": query,
-                                "boost": 10
-                            }
-                        }
-                    },
-                    {
-                        "match_phrase": {
-                            "element_desc": {
-                                "query": query,
-                                "boost": 6
-                            }
-                        }
-                    },
-                    {
-                        "match_phrase": {
-                            "search_terms": {
-                                "query": query,
-                                "boost": 8
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_name": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 4
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "search_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 5
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_desc": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 3
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_desc": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 2
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_name": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 2
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "search_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 1
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "optional_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length
-                            }
-                        }
-                    }
-                ]
-            }
-        }
-
-        if concept:
-            query['bool']['must'] = {
-                "match": {
-                        "identifiers": concept
-                }
-            }
+        es_query = self._get_var_query(concept, fuzziness, prefix_length, query)
         if index is None:
             index = "variables_index"
-        body = {'query': query}
-        total_items = await self.es.count(body=body, index=index)
+
+        total_items = await self.es.count(body=es_query, index=index)
         search_results = await self.es.search(
             index="variables_index",
-            body=body,
+            body=es_query,
             filter_path=['hits.hits._id', 'hits.hits._type',
                          'hits.hits._source', 'hits.hits._score'],
             from_=offset,
             size=size
         )
 
-        # Reformat Results
-        new_results = {}
-        if not search_results:
-            # we don't want to error on a search not found
-            new_results.update({'total_items': total_items['count']})
-            return new_results
+        search_result_hits = []
 
-        for elem in search_results['hits']['hits']:
-            elem_s = elem['_source']
-            elem_type = elem_s['data_type']
-            if elem_type not in new_results:
-                new_results[elem_type] = {}
+        if "hits" in search_results:
+            search_result_hits = search_results['hits']['hits']
 
-            elem_id = elem_s['element_id']
-            coll_id = elem_s['collection_id']
-            elem_info = {
-                "description": elem_s['element_desc'],
-                "e_link": elem_s['element_action'],
-                "id": elem_id,
-                "name": elem_s['element_name'],
-                "score": round(elem['_score'], 6)
-            }
-
-            # Case: collection not in dictionary for given data_type
-            if coll_id not in new_results[elem_type]:
-                # initialize document
-                doc = {
-                    'c_id': coll_id,
-                    'c_link': elem_s['collection_action'],
-                    'c_name': elem_s['collection_name'],
-                    'elements': [elem_info]
-                }
-                # save document
-                new_results[elem_type][coll_id] = doc
-
-            # Case: collection already in dictionary for given
-            # element_type; append elem_info.  Assumes no duplicate
-            # elements
-            else:
-                new_results[elem_type][coll_id]['elements'].append(elem_info)
-
-        # Flatten dicts to list
-        for i in new_results:
-            new_results[i] = list(new_results[i].values())
-
-        # Return results
-        if bool(data_type):
-            if data_type in new_results:
-                new_results = new_results[data_type]
-            else:
-                new_results = {}
-        return new_results
+        return self._make_result(data_type, search_result_hits , total_items, True)
 
     async def search_vars_unscored(self, concept="", query="",
                                    size=None, data_type=None,
@@ -478,134 +322,21 @@ async def search_vars_unscored(self, concept="", query="",
         If a data_type is passed in, the result will be filtered to only contain
         the passed-in data type.
         """
-        query = {
-            'bool': {
-                'should': {
-                    "match": {
-                        "identifiers": concept
-                    }
-                },
-                'should': [
-                    {
-                        "match_phrase": {
-                            "element_name": {
-                                "query": query,
-                                "boost": 10
-                            }
-                        }
-                    },
-                    {
-                        "match_phrase": {
-                            "element_desc": {
-                                "query": query,
-                                "boost": 6
-                            }
-                        }
-                    },
-                    {
-                        "match_phrase": {
-                            "search_terms": {
-                                "query": query,
-                                "boost": 8
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_name": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 4
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "search_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 5
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_desc": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "operator": "and",
-                                "boost": 3
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_desc": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 2
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "element_name": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 2
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "search_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length,
-                                "boost": 1
-                            }
-                        }
-                    },
-                    {
-                        "match": {
-                            "optional_terms": {
-                                "query": query,
-                                "fuzziness": fuzziness,
-                                "prefix_length": prefix_length
-                            }
-                        }
-                    }
-                ]
-            }
-        }
-
-        if concept:
-            query['bool']['must'] = {
-                "match": {
-                    "identifiers": concept
-                }
-            }
-
-        body = {'query': query}
-        total_items = await self.es.count(body=body, index="variables_index")
+        es_query = self._get_var_query(concept, fuzziness, prefix_length, query)
+        total_items = await self.es.count(body=es_query, index="variables_index")
         search_results = []
-        async for r in async_scan(self.es,
-                                  query=body):
+        async for r in async_scan(self.es, query=es_query):
             search_results.append(r)
+
+        return self._make_result(data_type, search_results, total_items, False)
+
+    def _make_result(self, data_type, search_results, total_items, scored: bool):
         # Reformat Results
         new_results = {}
         if not search_results:
             # we don't want to error on a search not found
             new_results.update({'total_items': total_items['count']})
             return new_results
-
         for elem in search_results:
             elem_s = elem['_source']
             elem_type = elem_s['data_type']
@@ -621,17 +352,18 @@ async def search_vars_unscored(self, concept="", query="",
                 "name": elem_s['element_name']
             }
 
+            if scored:
+                elem_info["score"] = round(elem['_score'], 6)
+
             # Case: collection not in dictionary for given data_type
             if coll_id not in new_results[elem_type]:
                 # initialize document
-                doc = {}
-
-                # add information
-                doc['c_id'] = coll_id
-                doc['c_link'] = elem_s['collection_action']
-                doc['c_name'] = elem_s['collection_name']
-                doc['elements'] = [elem_info]
-
+                doc = {
+                    'c_id': coll_id,
+                    'c_link': elem_s['collection_action'],
+                    'c_name': elem_s['collection_name'],
+                    'elements': [elem_info]
+                }
                 # save document
                 new_results[elem_type][coll_id] = doc
 
@@ -640,18 +372,21 @@ async def search_vars_unscored(self, concept="", query="",
             # elements
             else:
                 new_results[elem_type][coll_id]['elements'].append(elem_info)
-
         # Flatten dicts to list
         for i in new_results:
             new_results[i] = list(new_results[i].values())
-
         # Return results
         if bool(data_type):
             if data_type in new_results:
                 new_results = new_results[data_type]
             else:
                 new_results = {}
-        new_results.update({'total_items': total_items['count']})
+
+        # better to update UI to accept optional "total_items" so it does not fail while fetching data for studies tab
+        # and remove this if
+        if not scored:
+            new_results.update({'total_items': total_items['count']})
+
         return new_results
 
     async def search_kg(self, unique_id, query, offset=0, size=None,
@@ -690,3 +425,317 @@ async def search_kg(self, unique_id, query, offset=0, size=None,
         )
         search_results.update({'total_items': total_items['count']})
         return search_results
+
+    async def search_study(self, study_id=None, study_name=None, offset=0, size=None):
+        """
+        Search for studies by unique_id (ID or name) and/or study_name.
+        """
+        # Define the base query
+         # Define the base query
+        query_body = {
+            "bool": {
+                "must": []
+            }
+        }
+        
+        # Add conditions based on user input
+        if study_id:
+            query_body["bool"]["must"].append({
+                "match": {"collection_id": study_id}
+            })
+        
+        if study_name:
+            query_body["bool"]["must"].append({
+                "match": {"collection_name": study_name}
+            })
+
+        print("query_body",query_body)
+        body = {'query': query_body}
+        total_items = await self.es.count(body=body, index="variables_index")
+        search_results = await self.es.search(
+            index="variables_index",
+            body=body,
+            filter_path=['hits.hits._id', 'hits.hits._type', 'hits.hits._source'],
+            from_=offset,
+            size=size
+        )
+        search_results.update({'total_items': total_items['count']})
+        return search_results
+
+    async def search_program(self, program_name=None, offset=0, size=None):
+        """
+        Search for studies by unique_id (ID or name) and/or study_name.
+        """
+ # Initialize the query_body with the outer structure
+        query_body = {
+            "query": {
+                "bool": {
+                    "must": []
+                }
+            },
+            "aggs": {
+                "unique_collection_ids": {
+                    "terms": {
+                        "field": "collection_id.keyword",
+                        "size":1000
+                    },
+                    "aggs": {
+                        "collection_details": {
+                            "top_hits": {
+                                "_source": ["collection_id", "collection_name", "collection_action"],
+                                "size": 1
+                            }
+                        }
+                    }
+                }
+            }
+        }
+
+        # Add conditions based on user input
+        if program_name:
+            # Lowercase the program_name before adding it to the query
+            # program_name = program_name.lower()
+            query_body["query"]["bool"]["must"].append(
+                {"term": {"data_type.keyword": program_name}}
+            )
+
+        #print("query_body", query_body)
+
+        # Prepare the query body for execution
+        body = query_body
+    
+        # Execute the search query
+        search_results = await self.es.search(
+            index="variables_index",
+            body=body,
+            from_=offset,
+            size=size
+        )
+
+        # The unique collection_ids and their details will be in the 'aggregations' field of the response
+        unique_collection_ids = search_results['aggregations']['unique_collection_ids']['buckets']
+
+        # Prepare a list to hold the collection details
+        collection_details_list = []
+
+        for bucket in unique_collection_ids:
+            collection_details = bucket['collection_details']['hits']['hits'][0]['_source']
+            # Append the details to the list in the desired format
+            collection_details_list.append(collection_details)
+
+    
+            
+
+       #Adding consent to the studies 
+        with open(self._cfg.consent_id_path, 'r') as file:
+            consent_id_mappings = json.load(file)
+        # Add consent_id to the study
+        updated_studies = []
+        for study in collection_details_list:
+            collection_id = study["collection_id"]
+            if collection_id in consent_id_mappings:
+                consent_ids = consent_id_mappings[collection_id]
+                for consent_id in consent_ids:
+                    updated_study = study.copy()
+                    updated_study["collection_id"] = f"{collection_id}.{consent_id}"
+                    updated_study["collection_action"] = f"{study['collection_action']}"
+                    updated_studies.append(updated_study)
+            else:
+                updated_studies.append(study)
+        
+
+
+        #Adding missing studies
+                
+        with open(self._cfg.missing_studies_path, 'r') as file:
+            missing_studies = json.load(file)
+        for program in missing_studies:
+            if program_name.lower() == program['program_name'].lower():
+                updated_studies.extend(program['collections'])
+
+                
+        return updated_studies
+
+
+    async def search_program_list(self):
+        query_body = {
+            "size": 0,  # We don't need the documents themselves, so set the size to 0
+            "aggs": {
+                "unique_program_names": {
+                    "terms": {
+                        "field": "data_type.keyword",
+                        "size": 10000
+                    },
+                    "aggs": {
+                        "No_of_studies": {
+                            "cardinality": {
+                                "field": "collection_id.keyword"
+                            }
+                        }
+                    }
+                }
+            }
+        }
+        # Execute the search query
+        search_results = await self.es.search(
+            index="variables_index",
+            body=query_body
+        )
+        # The unique data_types and their counts of unique collection_ids will be in the 'aggregations' field of the response
+        unique_data_types = search_results['aggregations']['unique_program_names']['buckets']
+        data=unique_data_types
+
+        #Remove Parent program and add Training program
+        
+        data = [item for item in data if item['key'] != 'Parent']
+
+        with open(self._cfg.missing_program_path, 'r') as file:
+            missing_programs = json.load(file)
+        data.extend(missing_programs)
+
+
+        # Sorting the data alphabetically based on 'key'
+        sorted_data = sorted(data, key=lambda x: (x['key'].casefold(), x['key'][1:]))
+
+        #Add description as another field in exisiting data based on the program name
+        descriptions_json = self._cfg.program_description
+        descriptions = json.loads(descriptions_json)
+        description_dict = {item['key']: {'description': item['description'], 'parent_program': item['parent_program']} for item in descriptions}
+
+        # Add descriptions and parent programs to the sorted data
+        for item in sorted_data:
+            desc_info = description_dict.get(item['key'], {'description': '', 'parent_program': []})
+            item['description'] = desc_info['description']
+            item['parent_program'] = desc_info['parent_program']
+
+        return sorted_data
+
+
+    def _get_var_query(self, concept, fuzziness, prefix_length, query):
+        """Returns ES query for variable search"""
+        es_query = {
+            "query": {
+                'bool': {
+                    'should': [
+                        {
+                            "match_phrase": {
+                                "element_name": {
+                                    "query": query,
+                                    "boost": 10
+                                }
+                            }
+                        },
+                        {
+                            "match_phrase": {
+                                "element_desc": {
+                                    "query": query,
+                                    "boost": 6
+                                }
+                            }
+                        },
+                        {
+                            "match_phrase": {
+                                "search_terms": {
+                                    "query": query,
+                                    "boost": 8
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "element_name": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "operator": "and",
+                                    "boost": 4
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "search_terms": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "operator": "and",
+                                    "boost": 5
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "element_desc": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "operator": "and",
+                                    "boost": 3
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "element_desc": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "boost": 2
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "element_name": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "boost": 2
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "search_terms": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length,
+                                    "boost": 1
+                                }
+                            }
+                        },
+                        {
+                            "match": {
+                                "optional_terms": {
+                                    "query": query,
+                                    "fuzziness": fuzziness,
+                                    "prefix_length": prefix_length
+                                }
+                            }
+                        }
+                    ]
+                }
+            }
+        }
+        if concept:
+            es_query["query"]["bool"]["must"] = {
+                "match": {
+                    "identifiers": concept
+                }
+            }
+        return es_query
+
+    def get_simple_search_query(self, query):
+        """Returns ES query that allows to use basic operators like AND, OR, NOT...
+        More info here https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-simple-query-string-query.html."""
+        search_query = {
+            "query": {
+                "simple_query_string": {
+                    "query": query,
+                    "fields": ["name", "description", "search_terms"],
+                    "default_operator": "and",
+                    "flags": "OR|AND|NOT|PHRASE|PREFIX"
+                }
+            }
+        }
+        return search_query
diff --git a/src/dug/core/parsers/__init__.py b/src/dug/core/parsers/__init__.py
index aeec0516..c73c6c68 100644
--- a/src/dug/core/parsers/__init__.py
+++ b/src/dug/core/parsers/__init__.py
@@ -4,7 +4,7 @@
 import pluggy
 
 from ._base import DugElement, DugConcept, Indexable, Parser, FileParser
-from .dbgap_parser import DbGaPParser, AnvilDbGaPParser, KFDRCDbGaPParser, CRDCDbGaPParser
+from .dbgap_parser import *
 from .nida_parser import NIDAParser
 from .scicrunch_parser import SciCrunchParser
 from .topmed_tag_parser import TOPMedTagParser
@@ -13,6 +13,7 @@
 from .bacpac_parser import BACPACParser
 from .heal_dp_parser import HEALDPParser
 from .ctn_parser import CTNParser
+from .radx_parser import RADxParser
 
 
 logger = logging.getLogger('dug')
@@ -35,6 +36,18 @@ def define_parsers(parser_dict: Dict[str, Parser]):
     parser_dict["heal-studies"] = HEALDPParser(study_type="HEAL Studies")
     parser_dict["heal-research"] = HEALDPParser(study_type="HEAL Research Programs")
     parser_dict["ctn"] = CTNParser()
+    parser_dict["biolincc"] = BioLINCCDbGaPParser()
+    parser_dict["covid19"] = Covid19DbGaPParser()
+    parser_dict["dir"] = DIRDbGaPParser()
+    parser_dict["lungmap"] = LungMAPDbGaPParser()
+    parser_dict["nsrr"] = NSRRDbGaPParser()
+    parser_dict["parent"] = ParentDBGaPParser()
+    parser_dict["pcgc"] = PCGCDbGaPParser()
+    parser_dict["recover"] = RECOVERDBGaPParser()
+    parser_dict["topmeddbgap"] = TopmedDBGaPParser()
+    parser_dict["curesc"] = CureSC()
+    parser_dict["radx"] = RADxParser()
+
 
     
 
diff --git a/src/dug/core/parsers/dbgap_parser.py b/src/dug/core/parsers/dbgap_parser.py
index a362d028..5181b320 100644
--- a/src/dug/core/parsers/dbgap_parser.py
+++ b/src/dug/core/parsers/dbgap_parser.py
@@ -92,7 +92,57 @@ class CRDCDbGaPParser(DbGaPParser):
     def _get_element_type(self):
         return "Cancer Data Commons"
 
+
 class KFDRCDbGaPParser(DbGaPParser):
     def _get_element_type(self):
         return "Kids First"
 
+
+class BioLINCCDbGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "BioLINCC"
+
+
+class Covid19DbGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "COVID19"
+
+
+class DIRDbGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "DIR"
+
+
+class LungMAPDbGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "LungMAP"
+
+
+class NSRRDbGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "NSRR"
+
+
+class ParentDBGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "Parent"
+
+
+class PCGCDbGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "PCGC"
+
+
+class RECOVERDBGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "RECOVER"
+
+
+class TopmedDBGaPParser(DbGaPParser):
+    def _get_element_type(self):
+        return "TOPMed"
+
+
+class CureSC(DbGaPParser):
+    def _get_element_type(self):
+        return "CureSC"
diff --git a/src/dug/core/parsers/radx_parser.py b/src/dug/core/parsers/radx_parser.py
new file mode 100644
index 00000000..fe4de977
--- /dev/null
+++ b/src/dug/core/parsers/radx_parser.py
@@ -0,0 +1,36 @@
+import logging
+from typing import List
+from xml.etree import ElementTree as ET
+
+from dug import utils as utils
+from ._base import DugElement, FileParser, Indexable, InputFile
+
+logger = logging.getLogger('dug')
+
+
+class RADxParser(FileParser):
+
+    def __call__(self, input_file: InputFile) -> List[Indexable]:
+        tree = ET.parse(input_file, ET.XMLParser(encoding='utf-8'))
+        root = tree.getroot()
+        study_id = root.attrib['id']        
+        # If still None, raise an error message
+        study_name = root.attrib['study_name']
+        elements = []
+        for variable in root.iter('variable'):
+            desc = variable.find('description').text if variable.find('description') is not None else ''
+            desc = desc or ''
+            elem = DugElement(elem_id=f"{variable.attrib['id']}",
+                              name=variable.find('name').text,
+                              desc=desc,
+                              elem_type=root.attrib['module'],
+                              collection_id=f"{study_id}",
+                              collection_name=study_name)
+
+            # Create DBGaP links as study/variable actions
+            elem.collection_action = utils.get_dbgap_study_link(study_id=elem.collection_id)
+            logger.debug(elem)
+            elements.append(elem)
+
+        # You don't actually create any concepts
+        return elements
\ No newline at end of file
diff --git a/src/dug/core/parsers/topmed_csv_parser.py b/src/dug/core/parsers/topmed_csv_parser.py
index 710bcb63..9725f247 100644
--- a/src/dug/core/parsers/topmed_csv_parser.py
+++ b/src/dug/core/parsers/topmed_csv_parser.py
@@ -34,7 +34,7 @@ def __call__(self, input_file: InputFile) -> List[Indexable]:
                 elem = DugElement(elem_id=row['variable_full_accession'],
                                   name=row['variable_name'],
                                   desc=row['variable_desc'],
-                                  elem_type="dbGaP",
+                                  elem_type="TOPMed",
                                   collection_id=row['study_full_accession'],
                                   collection_name=row['study_name'])
 
diff --git a/src/dug/core/parsers/topmed_tag_parser.py b/src/dug/core/parsers/topmed_tag_parser.py
index f10ed43d..88f04493 100644
--- a/src/dug/core/parsers/topmed_tag_parser.py
+++ b/src/dug/core/parsers/topmed_tag_parser.py
@@ -59,7 +59,7 @@ def __call__(self, input_file: InputFile) -> List[Indexable]:
                     elem_id=row['variable_full_accession'],
                     name=row['variable_name'] if 'variable_name' in row else row['variable_full_accession'],
                     desc=row['variable_description'] if 'variable_description' in row else row['variable_full_accession'],
-                    elem_type="dbGaP",
+                    elem_type="TOPMed",
                     collection_id=row['study_full_accession'],
                     collection_name=row['study_name']
                 )
diff --git a/src/dug/server.py b/src/dug/server.py
index f7a8466a..5502bcd5 100644
--- a/src/dug/server.py
+++ b/src/dug/server.py
@@ -8,6 +8,7 @@
 from dug.core.async_search import Search
 from pydantic import BaseModel
 import asyncio
+from typing import Optional
 
 logger = logging.getLogger (__name__)
 
@@ -49,6 +50,19 @@ class SearchKgQuery(BaseModel):
     index: str = "kg_index"
     size:int = 100
 
+class SearchStudyQuery(BaseModel):
+    #query: str
+    study_id: Optional[str] = None
+    study_name: Optional[str] = None
+    #index: str = "variables_index"
+    size:int = 100
+class SearchProgramQuery(BaseModel):
+    #query: str
+    program_id: Optional[str] = None
+    program_name: Optional[str] = None
+    #index: str = "variables_index"
+    size:int = 100   
+
 search = Search(Config.from_env())
 
 @APP.on_event("shutdown")
@@ -107,5 +121,42 @@ async def search_var(search_query: SearchVariablesQuery):
     }
 
 
+
+@APP.get('/search_study')
+async def search_study(study_id: Optional[str] = None, study_name: Optional[str] = None):
+    """
+    Search for studies by unique_id (ID or name) and/or study_name.
+    """
+    result = await search.search_study(study_id=study_id, study_name=study_name)
+    return {
+        "message": "Search result",
+        "result": result,
+        "status": "success"
+    }
+
+
+@APP.get('/search_program')
+async def search_program( program_name: Optional[str] = None):
+    """
+    Search for studies by unique_id (ID or name) and/or study_name.
+    """
+    result = await search.search_program(program_name=program_name)
+    return {
+        "message": "Search result",
+        "result": result,
+        "status": "success"
+    }
+
+@APP.get('/program_list')
+async def get_program_list():
+    """
+    Search for program by program name.
+    """
+    result = await search.search_program_list()
+    return {
+  
+        "result": result,
+        "status": "success"
+    }
 if __name__ == '__main__':
-    uvicorn.run(APP)
+    uvicorn.run(APP,port=8181)
diff --git a/tests/integration/conftest.py b/tests/integration/conftest.py
index 50f57877..1ae80128 100644
--- a/tests/integration/conftest.py
+++ b/tests/integration/conftest.py
@@ -129,13 +129,13 @@ def sapbert_annotator_api():
                             "name": "attack; cardiovascular",
                             "curie": "UBERON:0007100",
                             "category": "biolink:Disease",
-                            "score": "0.15857231617",
+                            "score": 0.85857231617
                         },
                         {
                             "name": "Angina attack",
                             "curie": "XAO:0000336",
                             "category": "biolink:Disease",
-                            "score": "0.206502258778",
+                            "score": 0.806502258778
                         },
                     ]
                 ),
diff --git a/tests/integration/test_annotators.py b/tests/integration/test_annotators.py
index eecfd1e3..1fb384b4 100644
--- a/tests/integration/test_annotators.py
+++ b/tests/integration/test_annotators.py
@@ -106,43 +106,44 @@ def test_sapbert_annotation_full(
         classifiers, sapbert_annotator_api
     )
     processed_identifiers: List[DugIdentifier] = []
-    for identifier in raw_identifiers:
-        if identifier.id == "UBERON:0007100":
-            # Perform normal normalization
-            output = annotator.normalizer(identifier, normalizer_api)
-            print(output)
-
-            assert isinstance(output, DugIdentifier)
-            assert output.id == "UBERON:0007100"
-            assert output.label == "primary circulatory organ"
-            assert output.equivalent_identifiers == ["UBERON:0007100"]
-            assert output.types == "anatomical entity"
-        else:
-            # act as if this is null
-            output = annotator.normalizer(identifier, null_normalizer_api)
-
-        # Should be returning normalized identifier for each identifier passed in
-        if output is None:
-            output = identifier
-            # Test normalizer when null
-            assert output.id == "XAO:0000336"
-            assert output.label == "Angina attack"
-
-        # Add synonyms to identifier
-        if identifier.id == "UBERON:0007100":
-            output.synonyms = annotator.synonym_finder(output.id, synonym_api)
-            assert output.synonyms == [
-                "primary circulatory organ",
-                "dorsal tube",
-                "adult heart",
-                "heart",
-            ]
-        else:
-            output.synonyms = annotator.synonym_finder(output.id, null_synonym_api)
-            assert output.synonyms == []
-        # Get pURL for ontology identifer for more info
-        output.purl = BioLinkPURLerizer.get_curie_purl(output.id)
-        processed_identifiers.append(output)
+    for entity, identifiers in raw_identifiers.items():
+        for identifier in identifiers:
+            if identifier.id == "UBERON:0007100":
+                # Perform normal normalization
+                output = annotator.normalizer(identifier, normalizer_api)
+                print(output)
+
+                assert isinstance(output, DugIdentifier)
+                assert output.id == "UBERON:0007100"
+                assert output.label == "primary circulatory organ"
+                assert output.equivalent_identifiers == ["UBERON:0007100"]
+                assert output.types == "anatomical entity"
+            else:
+                # act as if this is null
+                output = annotator.normalizer(identifier, null_normalizer_api)
+
+            # Should be returning normalized identifier for each identifier passed in
+            if output is None:
+                output = identifier
+                # Test normalizer when null
+                assert output.id == "XAO:0000336"
+                assert output.label == "Angina attack"
+
+            # Add synonyms to identifier
+            if identifier.id == "UBERON:0007100":
+                output.synonyms = annotator.synonym_finder(output.id, synonym_api)
+                assert output.synonyms == [
+                    "primary circulatory organ",
+                    "dorsal tube",
+                    "adult heart",
+                    "heart",
+                ]
+            else:
+                output.synonyms = annotator.synonym_finder(output.id, null_synonym_api)
+                assert output.synonyms == []
+            # Get pURL for ontology identifer for more info
+            output.purl = BioLinkPURLerizer.get_curie_purl(output.id)
+            processed_identifiers.append(output)
 
     assert isinstance(processed_identifiers, List)
     assert len(processed_identifiers) == 2
diff --git a/tests/unit/test_async_search.py b/tests/unit/test_async_search.py
index c121ce7c..b044a2c6 100644
--- a/tests/unit/test_async_search.py
+++ b/tests/unit/test_async_search.py
@@ -28,7 +28,7 @@ def setUp(self):
         "Build mock elasticsearch responses"
         search_result = _brain_search_result()
         self.search = async_search.Search(Config.from_env())
-        self.query_body = self.search._build_concepts_query("brain")
+        self.query_body = self.search._get_concepts_query("brain")
         self.search.es = es_mock
 
     def test_concepts_search(self):