Assessment of multi-trait analysis of GWAS (MTAG) for discovery of novel genetic variants and mechanistic insight in common cardiovascular diseases

Abstract Background Variability in cardiovascular conditions is partly explained by common genomic variation identifiable by genome-wide association studies (GWAS). Genetic substrate may overlap in certain entities, this being quantified by genetic correlation. We aimed to leverage multi-trait analysis of GWAS (MTAG), (1) which boosts statistical power by joint analysis of genetically correlated traits, to improve genetic loci discovery in 3 common cardiovascular diseases: atrial fibrillation (AF), coronary artery disease (CAD), and heart failure (HF). Methods and Results Cardiovascular phenotypes with available GWAS summary statistics most correlated with the disease of interest were analysed jointly by MTAG (workflow depicted in Figure 1). These included body mass index and HF for AF (2); HF, LDL-cholesterol, and systolic blood pressure for CAD (3); and AF, CAD, and dilated cardiomyopathy for HF (4). MTAG increased statistical power for all 3 disease GWAS and allowed the identification of 19 new genomic loci for AF, 89 for CAD and 52 for HF (at a GWAS significance level P<5x10-8) (Figure 2). New loci were defined as not previously identified in the single trait original GWAS. Consistently, 19/19, 85/89 and 48/52 of new loci reached nominal significance (P<0.05) in the original studies; and 37%, 44% and 36% of new loci have been associated with AF, CAD and HF in GWAS and phenome wide association studies (PheWAS) in independent cohorts. MTAG summary statistics annotation and functional analysis integrated the distance to the canonical transcriptional start site, chromatin interaction experiments, quantitative molecular phenotype trait experiments and in silico functional prediction through OpenTargets Genetics. MAGMA gene-set functional analysis of the new MTAG results showed 87, 27 and 24 significant associated pathways to AF, CAD and HF respectively. Among the top associations, cardiac depolarization, repolarization, and muscle contraction in AF; macromolecular complex remodeling, triglyceride, chylomicron and LDL metabolism in CAD; and muscle structure, tissue development and RNA transcription initiation in HF. Among novel relevant genes in AF, SRR on chromosome 16 is involved in central nervous system development through regulation of NMDA receptors. This locus has been previously associated with QRS in another GWAS and SRR is related to reduction in heart rate variability and AF enhancement in rats. In CAD, RSPO3 and JAG1 genes, on chromosomes 6 and 20 respectively, have a relevant role in angiogenesis, where RSPO3 is a crucial regulator of coronary artery formation in the developing heart. Conclusions MTAG allows the discovery of new trait-specific loci involved in the pathogenesis of AF, CAD, and HF congruent with the mechanisms of each disease and consistent with independent external cohort PheWAS and GWAS. Thus, MTAG is an interesting tool to unravel relevant mechanisms and potential therapeutic targets in common cardiovascular diseases.