DOI: 10.60645/bdc-b877-1cs5
title: Building on GWAS for NHLBI-Diseases: The U.S. CHARGE Consortium - Sequencing (CHARGE-S): CHS

description: 
**Note: This substudy phs000667 CHARGE-S Cardiovascular Health Study contains harmonized phenotype data, whole genome, exome, targeted sequencing and exome chip data of a subset of the CHS cohort selected for NHLBI&#39;s CHARGE-S CONSORTIUM Project. Summary level phenotypes of the Cardiovascular Health Cohort study participants may be viewed at the top-level study page, phs000287 Cardiovascular Health Study (CHS) Cohort. Individual level phenotype data and molecular data for the top-level Cardiovascular Health Study and its substudies are available by requesting Authorized Access to the Cardiovascular Health Study (CHS) Cohort study [phs000287](./study.cgi?study_id=phs000287). **

Genome-wide association studies (GWAS) have successfully localized multiple loci containing common variations influencing coronary heart disease and its risk factors, but in most cases neither the gene underlying disease susceptibility nor the spectrum of candidate functional variants has been identified. Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium (the CHARGE sequencing (CHARGE-S) consortium) is a collaborative effort to leverage existing population, laboratory and computational resources to identify susceptibility genes underlying genome-wide significant and well-replicated GWAS findings for heart, lung and blood diseases and their risk factors. The sequencing approach was funded by NHLBI with funds provided by the American Recovery and Reinvestment Act of 2009 (ARRA). The U.S. CHARGE consortium consists of multiple large population-based longitudinal cohort studies, including the Atherosclerosis Risk in Communities (ARIC) Study (N=15,792), the Cardiovascular Health Study (CHS) (N=5,888), and the Framingham Heart Study (FHS) (N=14,428).

The study has taken a two pronged approach to following-up GWAS. First, regional capture targeted sequencing was performed in genomic regions influencing 15 phenotypes to localize causal variants that are responsible for the GWAS signal. The phenotypes examined were atrial fibrillation, blood pressure, body mass index (BMI), bone mineral density, C-reactive protein (CRP), carotid intima-media thickness (IMT), echocardiography, electrocardiogram PR and QRS interval, fasting insulin, hematocrit, pleiotropy, pulmonary function, retinal venule diameter, and stroke. A case-cohort study design was used in which a common reference sample was selected from all three cohorts at baseline. The cohort random sample included 2,000 individuals composed of 1,000 participants from the ARIC study, 500 participants from FHS, and 500 participants from CHS in a 1:1 gender ratio. The comparison groups were either selected cases for discrete phenotypes, or participants drawn from the top and/or bottom tail of the distribution for quantitative phenotypes. The size of each comparison group was 200 individuals. Approximately 2 Mb of the genome was sequenced for the targeted loci.

Second, whole exome capture sequencing and low-pass whole genome sequencing was completed for the cohort random sample and 7 phenotypes for which there were more than 3 GWAS signals in coding regions to detect novel rare and common variants. The phenotypes investigated by whole exome sequencing were age at menopause, electrocardiogram QT interval, fasting blood glucose, fibrinogen level, renal function, Stamler-Kannel-like extremes of risk factors, and waist-to-hip ratio.

Follow-up genotyping using the Illumina HumanExome BeadChip has also been completed. Additional information including variant annotation is available at: [http://www.chargeconsortium.com/main/exomechip](http://www.chargeconsortium.com/main/exomechip).

All sequencing was performed at the Human Genome Sequencing Center at the Baylor College of Medicine, and all genotyping with the HumanExome BeadChip was performed at Cedars-Sinai Medical Center. This study contains the Cardiovascular Health Study (CHS) study subset of CHARGE-S. Additional data from CHARGE-S is also available via dbGaP.