Authors

Brendan J. Keating, The Institute for Translational Medicine and Therapeutics, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvannia, United States of America
Sam Tischfield, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, 3 Divisions of Genetics, Endocrinology & Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America; Divisions of Genetics, Endocrinology & Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America
Sarah S. Murray, Scripps Genomic Medicine, La Jolla, California, United States of America
Tushar Bhangale
Thomas S. Price
Joseph T. Glessner
Luana Galver
Jeffrey C. Barrett
Struan F A Grant
Deborah N. Farlow
Hareesh R. Chandrupatla
Mark Hansen
Saad Ajmal
George J. Papanicolaou
Yiran Guo
Mingyao Li
Stephanie Derohannessian
Paul I W. de Bakker
Swneke D. Bailey
Alexandre Montpetit
Andrew C. Edmondson
Kent Taylor
Xiaowu Gai
Susanna S. Wang
Myriam Fornage, Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States of AmericaFollow
Tamim Shaikh
Leif Groop
Michael Boehnke
Alistair S. Hall
Andrew T. Hattersley
Edward Frackelton
Nick Patterson
Charleston K W Chiang
Cecelia E. Kim
Richard R. Fabsitz
Willem Ouwehand
Alkes L. Price
Patricia Munroe
Mark Caulfield
Thomas Drake, Human Genetics Center, University of Texas Health Science Center, Houston, Texas, United States of America,
Eric Boerwinkle
David Reich
A Stephen Whitehead
Thomas P. Cappola
Nilesh J. Samani
A Jake Lusis
Eric Schadt
James G. Wilson
Wolfgang Koenig
Mark I. McCarthy
Sekar Kathiresan
Stacey B. Gabriel
Hakon Hakonarson
Sonia S. Anand
Muredach Reilly
James C. Engert
Deborah A. Nickerson
Daniel J. Rader
Joel N. Hirschhorn
Garret A. Fitzgerald

Publication Date

10-31-2008

Journal

PLoS ONE. 2008;3(10):e3583. Epub 2008 Oct 31

Abstract

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

Keywords

Cardiovascular Diseases, Concept Formation, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Population Groups, Quality Control, Research Design

Comments

PMCID: PMC2571995

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