Coronary artery disease (CAD) is a heritable disorder with a complex genetic architecture that represents a major global health burden. A recent study by Petrazzini et al. leveraged exome sequencing data and a novel machine learning-based marker to identify rare coding variants (minor allele frequency (MAF) ≤ 0.01) and ultra-rare coding variants (MAF ≤ 0.0001) associated with the disease.

The team performed a rare variant association analysis using exome sequencing data of 604,915 individuals from independent study groups: the UK Biobank, All of Us and BioMe. By analysing 5,187,073 rare and ultra-rare coding variants, the authors identified 17 genes that had significant associations with ISCAD. These genes were implicated through both single-variant analyses and gene-level aggregation tests. Of note, 14 genes had moderate to strong prior genetic, biological or clinical evidence linking them to CAD. For example, the study highlighted the genes APOB, APOC3 and LDLR, which have known roles in lipid metabolism and CAD risk.