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More reliable and personalized ways to predict cardiovascular events could improve outcomes and quality of life for the hundreds of people worldwide with stable coronary artery disease (CAD). Contemporary risk stratification in CAD assesses clinical risk factors and tests for inducible myocardial ischemia and coronary atherosclerosis, but does not yet include molecular markers for processes at the root of cardiovascular events in CAD. If we could use molecular assays to better identify these high-risk patients, we could better target resource-intensive therapies to the right patient at the right time.

Our multidisciplinary group of cardiologists, clinical trialists, bioinformaticians, statisticians, and molecular scientists studies clinical applications of precision medicine to treat and prevent CAD, as well as investigates the role of environmental exposures, such as air pollution, and lifestyle in CAD development and prognosis. We are currently working to understand the following three fundamental questions in clinical trials and other groups of people with and without known CAD.

Can known and unbiased/discovery biomarkers reported to predict myocardial infarction and death in coronary artery disease improve prediction of these events when added to usual clinical testing?

Can we discover or use unbiased techniques to identify or guide treatment for patients with CAD and other clinical characteristics, such as type 2 diabetes, that increase risk of cardiovascular events?

How do environmental exposures, such as fossil fuel combustion, increase risk of heart disease, and can we test novel interventions to reduce this risk?

We have found that untargeted molecular approaches can reveal novel pathways associated with heart disease events for patients with CAD, and that we can align gene expression for high- and low-risk patients with CAD. We have also shown that whole-blood gene expression can improve prediction of cardiovascular events in patients with peripheral artery disease, and may improve risk stratification for cardiovascular events in CAD patients.

Our aim for the future is to validate additional biomarkers of risk in CAD, describe how these molecular markers can improve or replace existing clinical testing, and use these markers to guide treatment decisions for high-risk patients.