Concept, Design and Implementation of a Cardiovascular Gene-Centric 50 K SNP Array for Large-Scale Genomic Association Studies

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.

Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes

“…Fourth, we used self-report to assign ethnicity, which may result in some misclassification. However, in a separate analysis where we genotyped EpiDREAM participants using a custom-made 50K single nucleotide polymorphism chip for variation in genes related to cardiometabolic risk [36], we found that self-reported ethnicity was strongly correlated with genotype cluster and hence ancestral origin determined by multidimensional scaling [37]. Fifth, we were not able to explore the biological basis of associations and interactions observed in this study.…”

Gene-based interaction analysis by incorporating external linkage disequilibrium information

“…All study subjects were genotyped using the IBC 50K SNP array. 19 Our previous SNP pairwise interaction analysis on this data set reveals that a number of SNPs in CETP significantly interact with several SNPs in BCAT1. It is well known that CETP promotes the transfer of cholesteryl esters from HDL to low-density lipoprotein, and individuals that are genetically deficient for CETP often have extremely high HDL levels.…”

Genetics: Implications for Prevention and Management of Coronary Artery Disease

“…The decreasing cost of genotyping over time also allowed the IBC 50k CAD Consortium to revisit the candidate gene approach using a customized chip that comprehensively surveyed common genetic variation at ~2,100 candidate genes, representing a diverse spectrum of cardiovascular diseases (71). Well-powered studies using this array firmly established associations between CAD and genetic variants in LPA, the gene encoding lipoprotein(a), and confirmed several early GWAS discoveries for CAD (9p21, COL4A1/COL4A2, ZC3HC1, and CYP17A1) (72,73).…”