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Cardiovascular disease is a critical global health challenge, and early detection of at-risk individuals can enable early treatment and prevention of disease. In the CVDi, we leverage genomics, bioinformatics, machine learning, clinical data, and mobile health technology to advance the practice of preventive cardiology. Using existing clinical datasets we then validate the clinical utility of these models in diverse settings and populations.

• We use genetics to generate genetic predictors (polygenic risk scores) of atherosclerosis and coronary artery disease across diverse populations which can then be used clinically to identify at-risk individuals and guide clinical care.
• We have launched  for eight cardiovascular conditions (coronary artery disease, atrial fibrillation, diabetes mellitus type 2, hypertension, hypercholesterolemia, elevated lipoprotein(a), thoracic aortic aneurysm, and venous thromboembolic disease).
• Our landmark  are testing a polygenic risk-based detection strategy for subclinical coronary atherosclerosis to improve cardiovascular health and treat coronary plaque.
• We also participate in  for innovative catheter-based coronary interventions and drugs for atherosclerosis.