A Genomic Revolution for Cardiovascular Disease - A Progress Report at Five Years

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Abstract

Coronary artery disease (CAD) remains the most common disease and the leading cause of death, with a strong genetic risk. Clinical trials have documented that modification of known risk factors can prevent 30–40 % of CAD.1 However, epidemiologic studies have shown that genetic risk accounts for approximately 50 % of CAD.2 If the aim is to prevent CAD in this century, it will require comprehensive prevention modifying genetic, as well as known, risk factors. In 2006, we proposed that technological advances were ripe for a whole genome-based approach to the discovery of genetic risk factors for CAD.3 The hypothesis that common genetic variants would contribute to the risk of CAD was borne out by an explosion of gene discovery in the past five years made possible by high throughput genotyping arrays. Importantly, the formation of international consortia bringing together data from many genome-wide association studies (GWAS) has led to the discovery of 31 CAD risk loci. Although these loci account for only 10 % of the heritability of CAD, most loci do not associate with conventional risk factors for CAD, like cholesterol, demonstrating that much more work will be required to understand the mechanistic underpinnings of CAD.

Citation
Am Heart Hosp J. 2011;9(1):19-23

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Coronary artery disease (CAD) remains the most common disease and the leading cause of death, with a strong genetic risk. Clinical trials have documented that modification of known risk factors can prevent 30–40 % of CAD.1 However, epidemiologic studies have shown that genetic risk accounts for approximately 50 % of CAD.2 If the aim is to prevent CAD in this century, it will require comprehensive prevention modifying genetic, as well as known, risk factors. In 2006, we proposed that technological advances were ripe for a whole genome-based approach to the discovery of genetic risk factors for CAD.3 The hypothesis that common genetic variants would contribute to the risk of CAD was borne out by an explosion of gene discovery in the past five years made possible by high throughput genotyping arrays. Importantly, the formation of international consortia bringing together data from many genome-wide association studies (GWAS) has led to the discovery of 31 CAD risk loci. Although these loci account for only 10 % of the heritability of CAD, most loci do not associate with conventional risk factors for CAD, like cholesterol, demonstrating that much more work will be required to understand the mechanistic underpinnings of CAD.

Technological Advances in Whole-genome Genotyping

Genetic variants, most commonly seen as single nucleotide polymorphisms (SNPs), can now be genotyped across the entire genome thanks to two important technological advances. First, microlithography and nanotechnology have enabled the mass production of microarrays that interrogate between 500,000 to one million SNPs. Second, by genotyping more than 2,000 selected human genomes with over 13,000,000 SNPs the Thousand Genomes project has enabled the fine mapping of genetic haplotypes so that for any individual genotyped on a microarray, genotypes of as many as 11,000,000 SNPs can be imputed with accuracy to an allele frequency as low as 0.02.4 This provides an unprecedented degree of genomic coverage, with one SNP every 300 base pairs. The drawback to whole-genome genotyping is that any association, to be statistically valid, must overcome a stringent threshold of significance to account for multiple testing. In the case of arrays that genotype 1,000,000 SNPs, this threshold is p<5 x 10-8, or p<0.05 divided by 1,000,000 (assuming each SNP tested is independent). Thus, enormous sample sizes including well-defined cases and controls are required.

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