Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Abstract

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention

“…The CAD PRS was based on all 241 conditionally independent genome-wide significant SNVs identified in the most recent CAD GWAS from the Coronary Artery Disease Genome-Wide Replication and Meta-analysis (CARDIoGRAM) plus the Coronary Artery Disease (C4D) Genetics (CARDIoGRAMplusC4D) Consortium. 3 A complete list of these SNVs is included in eTable 1 in the Supplement. Using PLINK, version 2.0 (Christopher Chang), the GRS was calculated for each participant by multiplying the imputed allelic dosage with the variant-specific weight (β coefficient for the association between the SNV and CAD) based on CARDIoGRAMplusC4D and then summed across all variants.…”

“…A recent genomewide association study (GWAS) including over 1 million participants has identified 241 conditionally independent genomewide significant single-nucleotide variants (SNVs), representing an approximately 33% increase from the prior CAD GWAS. 3 Compared with prior scores, this updated score resulted in stronger risk prediction for incident CAD, increasing the hazard ratio (HR) per 1 SD of the PRS from 1.49 to 1.61. Although larger sample sizes will continue to identify more variants, the incremental risk prediction will likely be progressively more modest.…”

Genome-wide association analysis of plasma lipidome identifies 495 genetic associations

“…Of the 236 conditionally independent coronary artery disease ( CAD) GWS variants at 196 loci [43], 11 reach the BFS threshold P < 7.35e-10 for univariate analysis and 1 additional variant reaches the BFS threshold P < 4.55e-9 for multivariate analyses (Figure 5). The most widely-associated variant is near ZNF259 , located in the BUD13 - ZNF259 - APOA5 - APOA1 - SIK3 gene-cluster, which increases the levels of DAGs, PCs, PE 18:0;0_18:2;0, PIs, and TAGs and decreases the level of PC O-16:1;0/18:1;0.…”

“…We assessed associations of the coronary artery disease (CAD) variants identified by a recent study [43] with lipid species and clusters of lipid species in our study. Of the 241 conditionally independent GWS associations with CAD at 198 loci, 236 variants at 196 loci were either included in our GWAS, or their LD-proxies were found in our GWAS (LD proxies were defined using the same approach as with the lead variants).…”

Polygenic score informed by genome-wide association studies of multiple ancestries and related traits improves risk prediction for coronary artery disease

“…7,8 Polygenic scores integrate data from genome-wide association studies into a single quantitative and predictive metric of inherited risk. [9][10][11][12] . Several studies to date have stratified individuals into substantial gradients of CAD risk based on their polygenic score beyond their clinical risk factor profiles.…”