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The CVDi, led by Patrick Ellinor, aims to reduce the burden of cardiovascular disease and sudden cardiac death through four goals:

1. Fully define and make widely known the genetic causes of CVD and its metabolic risk factors.
2. Deeply investigate the biology underlying the most promising novel mechanisms.
3. Develop assays to identify therapeutics for the most promising targets.
4. Target interventions to people at high risk of premature CVD using genetic or non-genetic biomarkers.

The successful execution of this vision over the next decade will lead to a deep biological understanding of new mechanisms underlying CVD and its risk factors, which will help scientists and physicians effectively identify high-risk individuals appropriate for preventive interventions and advance new medicines that reduce the burden of these diseases. This work has centered on Ó³»­´«Ã½-led studies to identify and interpret genetic variants associated with cardiovascular diseases such as heart attack, atrial fibrillation, and stroke. Other work by the initiative aims to uncover biological insight from the genomic findings by connecting the variants to causal genes and mechanisms through studies in cellular, animal, and human model systems.

Members of the CVDi work closely with Ó³»­´«Ã½'s Data Sciences Platform (DSP), in particular DSP's Machine Learning for Health (ML4H) effort; Genomics Platform, Program in Medical and Population Genetics, and other scientists and programs studying related chronic diseases. Members of the CVDi also aim to translate genomic and biological findings into clinical interventions, such as new treatments. This work is done in close collaboration with Ó³»­´«Ã½'s Center for the Development of Therapeutics (CDoT) and partners in academia and industry.