Genomewide association analysis of coronary artery disease

Abstract

Background: Modern genotyping platforms permit a systematic search for inherited components of complex diseases. We performed a joint analysis of two genomewide association studies of coronary artery disease.

Methods: We first identified chromosomal loci that were strongly associated with coronary artery disease in the Wellcome Trust Case Control Consortium (WTCCC) study (which involved 1926 case subjects with coronary artery disease and 2938 controls) and looked for replication in the German MI [Myocardial Infarction] Family Study (which involved 875 case subjects with myocardial infarction and 1644 controls). Data on other single-nucleotide polymorphisms (SNPs) that were significantly associated with coronary artery disease in either study (P<0.001) were then combined to identify additional loci with a high probability of true association. Genotyping in both studies was performed with the use of the GeneChip Human Mapping 500K Array Set (Affymetrix).

Results: Of thousands of chromosomal loci studied, the same locus had the strongest association with coronary artery disease in both the WTCCC and the German studies: chromosome 9p21.3 (SNP, rs1333049) (P=1.80x10(-14) and P=3.40x10(-6), respectively). Overall, the WTCCC study revealed nine loci that were strongly associated with coronary artery disease (P<1.2x10(-5) and less than a 50% chance of being falsely positive). In addition to chromosome 9p21.3, two of these loci were successfully replicated (adjusted P<0.05) in the German study: chromosome 6q25.1 (rs6922269) and chromosome 2q36.3 (rs2943634). The combined analysis of the two studies identified four additional loci significantly associated with coronary artery disease (P<1.3x10(-6)) and a high probability (>80%) of a true association: chromosomes 1p13.3 (rs599839), 1q41 (rs17465637), 10q11.21 (rs501120), and 15q22.33 (rs17228212).

Conclusions: We identified several genetic loci that, individually and in aggregate, substantially affect the risk of development of coronary artery disease.

Figure 1. Signal-Intensity Plots Showing the Association of Single-Nucleotide Polymorphisms (SNPs) with Coronary Artery Disease or Myocardial Infarction in the Genomewide Association Analysis

The −log P values are for the association of each SNP with coronary artery disease or myocardial infarction, from two-sided Cochran–Armitage tests for trend. Only SNPs of sufficient quality (see the Supplementary Appendix) are shown. The signal-intensity plots of all SNPs with significant associations (P<0.001) were visually inspected by two independent reviewers in each study to rule out possible artifactual results due to miscalling of genotypes (see Supplementary Appendix). Within each chromosome shown on the x axis, the data are plotted from the p-ter end. The y-axis scale for associations in the WTCCC study (Panel A) differs from the scale for the German MI Family Study (Panel B).

Figure 2. Association Signal for Coronary Artery Disease on Chromosome 9

The −log P values, calculated with the use of the two-sided Cochran–Armitage test for trend, according to the location on chromosome 9 are shown (I). Arrows indicate the lead SNP. The inset graph shows the correlation between the odds ratios for coronary artery disease associated with the minor allele of SNPs from the WTCCC and German studies on chromosome 9. The genomic locations of genes or expressed-sequence tags (ESTs) (according to the Reference Sequence collection of the National Center for Biotechnology Information [NCBI]) are also shown (II). All data are from the Genome Browser of the University of California, Santa Cruz (NCBI build 35). Red boxes represent recombination hot spots, as estimated from HapMap data (Phase II, release 21) (III). Disequilibrium coefficient values for SNPs genotyped in case subjects with coronary artery disease in the WTCCC study, generated with the use of Haploview software, are shown (IV). There were two distinct blocks (1 and 2) of SNPs with significant associations. Disequilibrium coefficients for all SNPs from HapMap CEU data (from persons of Northern and Western European ancestry) across chromosome 9, generated with the use of Haploview software, are shown (V). In IV and V, the strength of the linkage disequilibrium between SNPs increases from white to blue to red (white: disequilibrium coefficient <1 and LOD score <2; blue: disequilibrium coefficient=1 and LOD score <2; pink or light red: disequilibrium coefficient <1 and LOD score ≥2; and bright red: disequilibrium coefficient=1 and LOD score ≥2). References relevant to II, III, and IV are given in the Supplementary Appendix.