AI Discovers Rare Genetic Variants Linked to Coronary Heart Disease

Researchers at the Icahn School of Medicine at Mount Sinai have leveraged advanced artificial intelligence (AI) tools to identify rare coding variants across 17 genes, shedding light on the genetic foundations of coronary artery disease (CAD). Their study, published in Nature Genetics, emphasizes the genetic factors contributing to heart disease, paving the way for targeted, personalized cardiovascular treatments.

The team developed a Coronary Artery Disease Score (ISCAD) to facilitate a thorough analysis of CAD. This score consolidates hundreds of clinical characteristics from electronic health records, including vital signs, laboratory results, medications, symptoms, and diagnoses. To create this AI scoring system, they utilized electronic health records from 604,914 individuals in partnerships with the UK Biobank, the All of Us Research Program, and the BioMe Biobank.

After establishing the scoring system, the researchers analyzed the correlation between the ISCAD score and rare or ultra-rare coding variants present in the exome sequences of these individuals. They further investigated how these identified genes relate to CAD risk factors, clinical manifestations, and overall CAD status.

Ultimately, the AI tool successfully pinpointed coding variants in 17 genes, enhancing the understanding of their association with coronary artery disease. Although these rare coding variants are found in only a small percentage of individuals, they can significantly impact disease risk and susceptibility. Additionally, studying these variants offers potential insights into the physiological mechanisms of heart disease and may lead to the discovery of novel genetic targets for treatment.