Genome-wide association with select biomarker traits in the Framingham Heart Study

• Type of Material: Article
• Authors: Emelia J Benjamin, The National Heart Lung and Blood Institute's Framingham Heart Study; Josée Dupuis, The National Heart Lung and Blood Institute's Framingham Heart Study; Martin G Larson, The National Heart Lung and Blood Institute's Framingham Heart Study; Kathryn L Lunetta, The National Heart Lung and Blood Institute's Framingham Heart Study; Sarah L Booth, Tufts University; Diddahally R Govindaraju, The National Heart Lung and Blood Institute's Framingham Heart Study; Sekar Kathiresan, Broad Institute of Massachusetts Institute of Technology; John F Keaney, Jr, Boston University; Michelle J Keyes, The National Heart Lung and Blood Institute's Framingham Heart Study; Jing-Ping Lin, National Institutes of Health; James B Meigs, Harvard Medical School; Sander J Robins, The National Heart Lung and Blood Institute's Framingham Heart Study; Jian Rong, The National Heart Lung and Blood Institute's Framingham Heart Study; Renate Schnabel, The National Heart Lung and Blood Institute's Framingham Heart Study; Joseph A Vita, Boston University; Thomas J Wang, Harvard Medical School; Peter W Wilson, Emory University; Philip A Wolf, The National Heart Lung and Blood Institute's Framingham Heart Study; Ramachandran S Vasan, The National Heart Lung and Blood Institute's Framingham Heart Study
• Language: English
• Date: 2007
• Publisher: BioMed Central
• Publication Version: Final Published Version
• Copyright Statement: © 2007 Benjamin et al; licensee BioMed Central Ltd.
• License: Creative Commons Attribution 2.0 Generic
• Final Published Version (URL): http://www.biomedcentral.com/1471-2350/8/S1/S11
• Title of Journal or Parent Work: BMC Medical Genetics
• ISSN: 1471-2350
• Volume: 8 (Suppl1)
• Start Page: s11
• Grant/Funding Information: A portion of the research was conducted using the Boston University Linux Cluster for Genetic Analysis (LinGA) funded by the NIH NCRR (National Center for Research Resources) Shared Instrumentation grant (1S10RR163736-01A1).; TNF-alpha concentrations were measured via American Diabetes Association Career Development Award and NCRR GCRC M01-RR-01066 (JBM); Natriuretic peptides were measured by Shionogi & Co., Ltd. with an unrestricted research grant; Liver function tests were funded by the core contract; Vitamins were measured by federal funds from the U.S. Department of Agriculture, Agricultural Research Service under Cooperative Agreement No. 58-1950-001 and No. 58-1950-4-401, National Institute of Aging (AG14759).; The core examinations were funded by N01-HC25195.
• Research Categories: Biology, Biostatistics; Biology, Genetics; Health Sciences, General

Abstract

Background Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. Methods We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001. Results With GEE, 58 SNPs had p < 10-6: the top SNPs were rs2494250 (p = 1.00*10-14) and rs4128725 (p = 3.68*10-12) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10-8) and rs2808629 (p = 3.19*10-8) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10-6: the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10-8, and rs2494250, p = 3.55*10-8), and also included B-type natriuretic peptide (rs437021, p = 1.01*10-6) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10-6). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. Conclusion The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.