Genome-Wide Pleiotropy Analysis Identifies Shared and Opposing Pathways Influencing Coronary Artery Disease and Cancer.

Abstract

Background: Coronary artery disease (CAD) and cancer are 2 leading global causes of mortality, with shared modifiable risk factors, yet the genetic and molecular mechanisms underlying their comorbidity remain poorly understood.

Methods: We performed a genome-wide pleiotropy analysis to identify shared genetic mechanisms across CAD and 4 common cancers that share modifiable risk factors with CAD (breast, colorectal, lung, prostate).

Results: Using genome-wide pleiotropy and colocalization analysis, we identified 60 colocalized susceptibility loci shared by CAD and site-specific cancer, of which 43 are novel, including loci at TERT, MYO9B, and SREBF1. For 35 loci, the lead SNP (single-nucleotide polymorphism) exhibited opposing effects on CAD and cancer risk. Gene-set enrichment analysis revealed distinct enrichment patterns of same-direction and opposing-direction pleiotropic loci, including differential associations with blood pressure-related traits, blood cell traits, and waist circumference. By integrating transcriptomic and proteomic data in multitrait colocalization, 13 pleiotropic loci influenced CAD and cancer risk via differential gene or protein expression of neighboring genes, including CALCRL, ANGPTL4, and LAMC1, targets of approved or investigational medications. Phenome-wide association analysis in the UK Biobank identified 1955 associations (false discovery rate [FDR] P<0.05) of lead SNPs at multitrait colocalized loci with serum biomarkers and clinical measures, with apoA, HDL (high-density lipoprotein) cholesterol, and creatinine being associated with the largest number of lead SNPs.

Conclusions: Our findings highlight shared and opposing genetic loci between CAD and cancer and provide insight into molecular intermediates mediating joint disease risk. Importantly, they indicate potential drug repurposing opportunities for dual CAD and cancer prevention while highlighting possible adverse and divergent effects of existing medications across both conditions.