ID
45284
Description
Principal Investigator: Stephen Rich, PhD, University of Virginia, Charlottesville, VA, USA MeSH: Myocardial Infarction,Brain Ischemia https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000400 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. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000400 contains the Cardiovascular Health Study (CHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.
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- 10/13/22 10/13/22 - Dr. Christian Niklas
Copyright Holder
Stephen Rich, PhD, University of Virginia, Charlottesville, VA, USA
Uploaded on
October 13, 2022
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Creative Commons BY 4.0
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dbGaP phs000400 NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (CHS)
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- Subject - Consent Information
- Subject - Sample - Mapping
- The dataset is focused on LDL data (extremely high/low) of participating subjects of two ethnic groups (Caucasian/African American). In addition to various lipid values, medical background information provides data about blood/urine laboratory values, EKG results, medication taken, body measurements (e.g. height, weight, BMI), the occurrence of cardio-vascular related diagnoses, e.g. diabetes, MI, stroke (including family history), and gender, age of subjects.
Similar models
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- Subject - Consent Information
- Subject - Sample - Mapping
- The dataset is focused on LDL data (extremely high/low) of participating subjects of two ethnic groups (Caucasian/African American). In addition to various lipid values, medical background information provides data about blood/urine laboratory values, EKG results, medication taken, body measurements (e.g. height, weight, BMI), the occurrence of cardio-vascular related diagnoses, e.g. diabetes, MI, stroke (including family history), and gender, age of subjects.
C0680251 (UMLS CUI [1,2])