Prediction of Causal Candidate Genes in Coronary Artery Disease Loci

Abstract

Objective Genome-wide association studies (GWAS) have so far identified 159 significant and suggestive loci for coronary artery disease (CAD). We now report comprehensive bioinformatics analyses of sequence variation in these loci to predict candidate causal genes. Approach and Results All annotated genes in the loci were evaluated with respect to protein coding SNPs and gene expression parameters. The latter included expression quantitative trait loci, tissue specificity, and miRNA binding. High priority candidate genes were further identified based on literature searches and our experimental data. We conclude that the great majority of causal variations affecting CAD risk occur in non-coding regions, with 41 % affecting gene expression robustly versus 6% leading to amino acid changes. Many of these genes differed from the traditionally annotated genes, which was usually based on proximity to the lead SNP. Indeed, we obtained evidence that genetic variants at CAD loci affect 98 genes which had not been linked to CAD previously. Conclusions Our results substantially revise the list of likely candidates for CAD and suggest that GWAS efforts in other diseases may benefit from similar bioinformatics analyses.

The impact of genome‐wide association studies on the pathophysiology and therapy of cardiovascular disease

“…annot., bioinformatics annotation according to Braenne et al (2015) or others (Musunuru et al , 2010; Salvi et al , 2013); no data, no eQTL data or non‐coding variant; NA, not analysed.…”

“…Indeed, annotation of the risk alleles revealed that the majority are located in chromosomal regions relevant for gene regulation. The identification of the underlying pathophysiological mechanism(s) thus requires annotation of the affected gene(s), which may be challenging (Braenne et al , 2015). The chromosome 9p21 locus is a prominent example: whereas initial studies focused on the two genes situated at the locus, CDKN2A and CDKN2B, current studies rather point to radically new disease mechanisms.…”

“…The variant rs3184504 tagging the SH2B3 gene is associated with CAD (Gudbjartsson et al , 2009; CARDIoGRAMplusC4D Consortium, 2013). The interpretation of this association is complicated by the fact that this particular variant also represents an eSNP for a neighbour gene, ATXN2 (Braenne et al , 2015). Nevertheless, the SH2B3 gene, which encodes an adaptor protein expressed, for example, in leucocytes and platelets, revealed in a knock‐out mouse model ( Lnk −/− ) increased platelet counts, but reduced thrombus stability (Takizawa et al , 2010).…”

Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits

“…1,2 The genetic analysis of gene expression by identification of expression quantitative trait loci (eQTLs) in relevant tissues has proven useful to predict candidate genes at GWAS loci and biological pathways that are perturbed in affected individuals. [3][4][5][6] Subcutaneous adipose tissue serves as a buffering system for lipid energy balance, particularly fatty acids, 7,8 and might play a protective role in metabolic and cardiovascular disease risk. 9 Subcutaneous adipose eQTL studies have implicated genes involved in obesity and metabolic traits.…”

Recent Advances in the Genetics of Atherothrombotic Disease and Its Determinants

“…Using network centrality analysis, they identified several novel gene candidates involved in CAD pathways. In a second CAD study, Braenne et al 18 performed a comprehensive bioinformatics analysis of sequence variation in known CAD loci to predict candidate causal genes. This led to a revised list of gene candidates for CAD and the expansion of the CAD genetic landscape.…”