Abstract MP16: Multi-trait Gwas Of Atherosclerosis Detects Novel Loci And Potential Therapeutic Targets

Abstract

Atherosclerosis, which is the narrowing of the arterial walls via accumulation of cholesterol-rich arterial plaques, is the leading cause of vascular disease worldwide, including myocardial infarction and ischemic stroke. Although atherosclerosis affects arteries throughout the body, previous genome-wide association studies (GWAS) have been performed on specific atherosclerotic phenotypes such as coronary artery disease (CAD) and peripheral artery disease (PAD). There is substantial evidence to suggest that these more specific atherosclerosis phenotypes share a common genetic etiology. We performed a series of multi-trait GWAS using combinations of two atherosclerosis traits and seven atherosclerosis risk factor traits and detected 31 novel pleiotropic loci. We performed these multi-trait GWAS using the N-GWAMA multi-trait GWAS method and summary statistics for CAD (van der Harst et al. 2018), PAD (Klarin et al. 2019), body mass index (Pulit et al. 2019), type II diabetes (Vujkovic et al. 2020), smoking initiation (Wootton et al. 2020), and lipid traits (Klarin et al. 2019). We identified candidate causal genes for 14 of these loci through colocalization analysis with GTEx expression quantitative trait locus (eQTL) data. VDAC2 and PCSK6 are two candidate causal genes that our results and previous literature suggest are potential therapeutic targets. VDAC2 eQTLs in aorta and tibial artery colocalized with a multi-trait GWAS signal detected in the CAD PAD multi-trait GWAS. Previous work has shown that VDAC2 regulates apoptosis, and our results suggest increased VDAC2 expression in smooth muscle cells could increase smooth muscle cell accumulation in atherosclerotic plaques. A sQTL (splicing QTL) for PCSK6 in liver colocalized with a multi-trait GWAS signal between PAD and LDL. Further analysis of the sQTL signal suggested that the effect allele correlates with a more active isoform of PCSK6 , which could increase lipid fractions and risk of atherosclerosis. These results show that joint analysis of atherosclerotic disease traits and their risk factors allows for identification of unified biology that may offer the opportunity for therapeutic manipulation.