Researchers have developed an integrated genomic model for coronary artery disease that combines germline and somatic data. This model may improve the prediction of cardiovascular disease risk and related conditions, such as atrial fibrillation and type 2 diabetes. The integration of various data types, including polygenic risk scores and questionnaire-based risk factors, appears to enhance the understanding of the molecular mechanisms underlying these diseases.