ADVANCE– Atherosclerotic Disease Vascular
Function and Genetic Epidemiology

Genome Wide Association Study  (GWAS)

Group Photo

Most candidate gene case-control studies to date of complex traits have been disappointing.  In CAD alone, many initially positive reports have not withstood the test of replication in other cohorts 1-12. The reasons for the overall failure of candidate gene studies to date are many, but likely stem primarily from the very low pre-test probability that any given gene (out of the estimated 30,000 genes in the human genome) contributes to the susceptibility of a complex trait despite a priori hypotheses based on cell, tissue, or animal model experiments.  Other reasons include the use of underpowered sample sizes, multiple testing, phenotypic heterogeneity, poor phenotype characterization, selection bias, population stratification, and incomplete knowledge of the complete set of allelic variants in the region of a candidate gene 13, 14.

A long anticipated alternative design has been the genome wide association (GWA) design 15, 16.  The GWA design calls for the use of high throughput genotyping platforms to genotype as many SNPs in the genome as possible in a set of cases and controls irrespective of the location of these SNPs relative to genes.  No prior information on gene function is necessary to select SNPs for genotyping.  In the last few years, the GWA design has become analytically and economically feasible primarily as a result of whole genome resequencing efforts by the International HapMap project and Perlegen in a large number of racially diverse subjects 17, 18.  As of October, 2005, these efforts have produced genotypes, frequencies, and assay information on close to 6 million SNPs out of the estimated 11 to 15 million SNPs in the human genome with a minor allele frequency of >1%.  In turn, this information has been mobilized by two companies, Affymetrix and Ilumina, to develop high-throughput and highly parallel genotyping technology that allows for up to 550,000 SNPs to be genotyped in a single individual at a fraction of the cost per genotype compared to other reliable platforms used in candidate gene studies to date such as the TaqMan assay.

Reports of successful localization of common genetic variants influencing complex traits using a GWA design have been recently published 19, 20.  In the first study of only 96 cases and 50 controls, the GWA scan identified a susceptibility locus in the complement factor H gene (CFH) with an odds ratio of 7.4 for age-related macular degeneration in a region of chromosome 1 repeatedly linked to this phenotype by linkage.  In a second study19, Framingham investigators screened participants of the Framingham Heart study for novel genetic determinants of BMI.  Of the top 10 SNPs tested under a recessive model, which was found to have the greatest power during the screening procedure, only one SNP near the INSIG2 gene reached overall significance (unadjusted FBAT-PC P value, 0.0026). However, associations with this SNP and BMI were subsequently demonstrated in 4 out 5 other cohorts tested for this SNP.  Both these studies used 100K platforms and it is expected that 500K platforms will be significantly more revealing.

Phase II Study Design Overview:

Specific Aim 1: Perform a genome wide association study (GWAS) by genotyping 550,000 tagSNPs on the Illumina Infinium platform in an ethnically diverse cohort of ~ 500 young individuals with premature CAD and ~ 500 controls frequency matched on gender and ages; identify allelic variation that is associated with disease status as well as several clinically relevant phenotypes, including BMI, blood pressure, serum lipoprotein levels, insulin resistance, diabetes, and C-Reactive Protein (CRP) levels.

Specific Aim 2: Perform a second-stage follow up by performing regional targeted genotyping using the Illumina Custom Infinium platform in not only the subjects described in Specific Aim 1 but also ~ 1,100 new cases and ~ 1000 new controls among the older-age subjects in our ADVANCE study followed by a combined analysis of the two stages.  The custom SNPs will be chosen to cover the most significant ones discovered in Specific Aim 1, with comprehensive coverage for our most promising findings, while adding the best SNPs and genes from other concurrent WGA studies. 

Specific Aim 3: Attempt to replicate our most significant findings in a cohort of ~1,500 early onset CAD cases and ~1,500 matched controls collected by the INTERHEART study. 

Phase 2 Study Design

References

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