The Framingham Heart Study 100K SNP Genome-Wide Association Study Resource: Overview of 17 Phenotype Working Group Reports
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Cupples, L Adrienne
Arruda, Heather T
Benjamin, Emelia J
D'Agostino, Ralph B
Demissie, Serkalem
DeStefano, Anita L
Dupuis, Josée
Govindaraju, Diddahally R
Heard-Costa, Nancy L
Hwang, Shih-Jen
Kathiresan, Sekar
Laramie, Jason M
Larson, Martin G
Liu, Chun-Yu
Lunetta, Kathryn L
Mailman, Matthew D
Manning, Alisa K
Murabito, Joanne M
O'Connor, George T
Pandey, Mona
Seshadri, Sudha
Vasan, Ramachandran S
Wilk, Jemma B
Wolf, Philip A
Yang, Qiong
Atwood, Larry D
Levy, Daniel
Wang, Zhen
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.1186/1471-2350-8-S1-S1Metadata
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Cupples, L. Adrienne, Heather T. Arruda, Emelia J. Benjamin, Ralph B. D'Agostino, Serkalem Demissie, Anita L. DeStefano, Josée Dupuis, et al. 2007. The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports. BMC Medical Genetics 8(Suppl 1): S1.Abstract
Background: The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies. Methods: Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests. Results: The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 ± 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency ≥ 10%, genotype call rate ≥ 80%, Hardy-Weinberg equilibrium p-value ≥ 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http:// www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Conclusion: We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1995613/pdf/Terms of Use
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