68 Rare alleles in genetic predisposition to coronary artery disease: insights from the novel analysis of gene-centric array. (9th June 2011)

• Record Type: Journal Article
• Authors: Christofidou, P; Debiec, R; Nelson, C P; Braund, P S; Bloomer, L D S; Ball, S G; Balmforth, A J; Hall, A S; Tomaszewski, M; Samani, N J
• Is Part Of: Heart. Volume 97(2011)Supplement 1
• Page Start: A41
• Page End: A42
• Publication Date: 2011-06-09
• Subjects: Coronary artery disease -- rare variants -- 50k chip; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2011-300198.68
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Background: Genome-wide association studies have been successful in identifying association between several common variants and coronary artery disease (CAD). However, collectively these variants explain only a small proportion of CAD heritability. It is becoming increasingly clear that the remainder of the "missing CAD heritability" could be explained by low frequency/rare alleles. Because of the small number of observations for any given rare allele, the power to detect its association with a phenotype is a major limiting factor in genetic analysis. In this study we have undertaken a novel statistical approach that combines information from all low frequency (MAF<5%) SNPs at one locus in gene-centric analysis of CAD. We hypothesised that patients with CAD will show over-representation of rare alleles compared to controls. Methods: To examine associations between rare alleles and CAD, we have used data from 2119 CAD cases and 2440 healthy controls recruited to the Welcome Trust Case-Control Consortium (WTCCC) Study. DNA from each subject was genotyped for approximately 45 000 SNPs in more than 2000 genes/loci using 50K IBC array (version 1). Association analysis was based on the CCRaVAT (Case-Control Rare Variant Analysis Tool) algorithm that maximises statistical power by combining all rare alleles within defined regions into a single "super locus". Differences in the proportion of cases and controls carrying rare "super loci" were tested by Pearson's or Fisher's exact test. Empirical p values were generated by permuting case-control status a predefined number of times and repeating the analysis for each replicate. Results: 5 candidate regions (MMP23B, VEGFA, DVL1, RIPK1, LPAL2) showed an over-accumulation of rare alleles in patients with CAD when compared to controls (FDR<50%). The number of analysed rare alleles at each of these loci ranged from 4 to 42. The most significant over-representation of rare variants were identified at MMP23B (matrix metallopeptidase 23B gene; p=1.3/10 4 ), a gene previously unsuspected to play a major role in CAD and VEGFA (vascular endothelial growth factor A; p=2.6×10 −4 ). Only one of the identified genes (LPAL2; p=1.7×10 −3 ) lies within the locus that was previously shown to harbour rare variants associated with susceptibility to CAD. Conclusions: Rare alleles are associated with predisposition to CAD and this gene-centric analysis combining information from low-frequency variants of the same locus has a potential to uncover, at least a proportion of, the "missing heritability" of CAD.