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 ∼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.
Highlights
Cardiovascular disease (CVD), the leading cause of death in the developed world [1], has been shown to have significant heritability [2,3,4,5,6]
The pattern of CVD in developed countries has changed as the detection and management of risk factors such as hypertension, hypercholesterolemia and predisposition to thrombosis has coincided with a decline in the incidence of myocardial infarction (MI) and stroke [7]
Custom single nucleotide polymorphism (SNP) selection allowed us to: (a) ensure selective and consistent coverage for a range of prioritized loci across multiple ancestries, (b) provide additional representative coverage to HapMap in loci of major interest, using SNP content from various sources including recent resequencing efforts; and (c) assay directly specific SNPs of interest such as those derived from previously published studies and known non-synonymous SNPs with minor allele frequencies (MAFs).0.01
Summary
Cardiovascular disease (CVD), the leading cause of death in the developed world [1], has been shown to have significant heritability [2,3,4,5,6]. Many apparent associations have not replicated for reasons including inadequate sample size, imprecise or inaccurate phenotyping, insufficiently stringent statistical thresholds, genuine heterogeneity of causality and population stratification [8,9]. The International HapMap Project [10], combined with advances in genotyping technologies, has led to the generation of multiple array-based SNP genotyping products for GWAS. These developments enable reasonably dense and unbiased global scans of the human genome which have already identified novel loci associated with CVD [11,12,13,14]. GWAS have relatively low power to detect subtle, but potentially important effects, in studies of ‘‘typical’’ sample sizes.
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