69 Genome wide methylation analysis in coronary artery disease

Abstract

<h3>Background</h3> Using genome-wide association studies several genes have been identified that affect the risk of CAD. However, these genes only explain part of the heritability. There is increasing evidence of the role of epigenetic regulation in complex diseases that may explain part of the missing heritability. DNA methylation is an important epigenetic change that regulates gene expression. Any role of methylation in CAD is poorly understood. Therefore we undertook an exploratory genome-wide screen to identify genes differentially methylated in CAD cases and controls. <h3>Methods</h3> We characterised DNA methylation in 24 CAD patients with a documented history of MI and 24 matched controls from the Cardiogenics case-control cohort. All subjects were male, ranging in age from 40 to 57 years. For each subject, genomic DNA, isolated from whole blood, was bisulphite converted and run on Illumina HumanMethylation27 bead chips. The HumanMethylation27 chips interrogate 27 578 CpG sites spanning 14 495 genes with an average of 2 CpG sites per gene. <h3>Results</h3> Global DNA methylation level was significantly higher in cases compared to controls (p=9.0×10⁻⁴). Furthermore, 686 individual CpG sites, spanning 633 genes showed statistically significant differences in methylation levels between cases and controls. Significant signals after Bonferroni correction for multiple comparisons included GNAS (p=7.94×10⁻⁵), which is involved in receptor-mediated signal transduction, PCMT1 (p=7.94×10⁻⁵), ACD (p=3.48×10⁻⁴ part of the telosome/shelterin complex), ATXN2 and APOA1 (p=5.6×10⁻³ and p=0.01). To explore the potential functional importance of differences in methylation level in cases and controls for individual genes, we examined the relationship of methylation level to transcript level in monocytes and macrophages on a gene by gene basis and identified several genes including GNAS and PCMT1 that showed significant correlations between gene expression and methylation. Pathway enrichment analysis of the differentially methylated genes using the DAVID bioinformatics resource identified a number of pathways that showed significant enrichment including the calcium signalling pathway (p=3.85×10⁻⁷). <h3>Conclusions</h3> This pilot study has shown several significant differences in gene methylation patterns between CAD cases and controls. We also found a correlation between methylation level and gene expression for a number of these genes. Genes differentially methylated in CAD are significantly enriched for a number of pathways including the calcium signalling pathway. While these findings require further validation they suggest that epigenetic changes may play an important role in the pathogenesis of CAD.