Recently, consortia of genome-wide association studies (GWAS) have formed around specific phenotypes such as type 2 diabetes and lipids to identify associations with genetic variants. In contrast, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed in Feb 2008 to facilitate GWAS prospective meta-analyses of a wide range of phenotypes among large population-based cohort studies, including the Age, Gene/Environment Susceptibility Study, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Framingham Heart Study, and the Rotterdam Study. The Health Aging and Body Composition Study, Multi-Ethnic Study of Atherosclerosis, and Coronary Artery Risk Development in Young Adults Study are now participating as well. With more than 53,000 participants, these cohort studies have both genome-wide data and repeated measures of risk factors, subclinical disease measures, and cardiovascular events all collected in a standardized fashion. The CHARGE collaboration, which takes advantage of the hundreds of millions of dollars already invested in these cohort studies, represents a major innovation in consortium structure because the organizing principle is the cohort study design rather than the phenotype. In just over a year and a half of collaboration, the CHARGE investigators have 21 papers published or in press, 14 papers under review, and about 50 other analyses or papers in progress. The CHARGE consortium represents an unfunded voluntary federation of large complex studies, one that lacks infra-structural support to sustain its increasingly complex operations. The two functions that none of the cohorts can offer in a sustained way are: 1) administrative Coordinating-Center-like support for working groups, committees, conference calls, meetings, tracking publications, and upgrades to the website and wiki;and 2) modest genotyping resources for follow-up and replication efforts often required by editors and reviewers. In the proposed R01, we plan to provide not only Coordinating-Center support and modest genotyping resources, but also support for students, fellows and junior investigators, including new opportunities for junior investigators from one site to spend time working at another site (exchanges). Junior investigators have often taken a leading role in CHARGE analyses and manuscripts with the result that the CHARGE consortium has become a kind of de facto international training ground for collaborative epidemiological efforts in the genetics of aging and cardiovascular disease. All CHARGE papers have junior investigators among the set of investigators identified as contributing equally as first authors. First-first authors of CHARGE meta-analysis papers have frequently been doctoral students (n=4), post-doctoral fellows (n=2), or junior investigators (n=5). Support for students and junior investigators and support for between-cohort exchanges will foster collaboration, enhance the current science, and improve the training of our future scientists.

Public Health Relevance

The proposed project will assist in the discovery of genetic variants associated with a variety of cardiovascular and aging conditions. The findings may lead to a new understanding about a disease processes, prevention and treatment.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL105756-03
Application #
8402649
Study Section
Cardiovascular and Sleep Epidemiology (CASE)
Program Officer
Papanicolaou, George
Project Start
2011-02-15
Project End
2014-12-31
Budget Start
2013-01-01
Budget End
2014-12-31
Support Year
3
Fiscal Year
2013
Total Cost
$636,606
Indirect Cost
$93,820
Name
University of Washington
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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Ibrahim-Verbaas, C A; Bressler, J; Debette, S et al. (2016) GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Mol Psychiatry 21:189-97
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Lin, Honghuang; Mueller-Nurasyid, Martina; Smith, Albert V et al. (2016) Gene-gene Interaction Analyses for Atrial Fibrillation. Sci Rep 6:35371
de Vries, Paul S; Chasman, Daniel I; Sabater-Lleal, Maria et al. (2016) A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration. Hum Mol Genet 25:358-70
Lupton, Michelle K; Strike, Lachlan; Hansell, Narelle K et al. (2016) The effect of increased genetic risk for Alzheimer's disease on hippocampal and amygdala volume. Neurobiol Aging 40:68-77
Kunkle, Brian W; Jaworski, James; Barral, Sandra et al. (2016) Genome-wide linkage analyses of non-Hispanic white families identify novel loci for familial late-onset Alzheimer's disease. Alzheimers Dement 12:2-10
Yu, Bing; Pulit, Sara L; Hwang, Shih-Jen et al. (2016) Rare Exome Sequence Variants in CLCN6 Reduce Blood Pressure Levels and Hypertension Risk. Circ Cardiovasc Genet 9:64-70
Chouraki, Vincent; Reitz, Christiane; Maury, Fleur et al. (2016) Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease. J Alzheimers Dis 53:921-32
Pickrell, Joseph K; Berisa, Tomaz; Liu, Jimmy Z et al. (2016) Detection and interpretation of shared genetic influences on 42 human traits. Nat Genet 48:709-17

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