Population Assessments of Aggregate Genetic Risk for Dilated Cardiomyopathy

PROJECT SUMMARY

Candidate. Krishna G. Aragam, MD MS is a board-certified physician in internal medicine and cardiology at

Massachusetts General Hospital (MGH), an Instructor in Medicine at Harvard Medical School (HMS), and an

affiliated researcher at the Broad Institute of Harvard/MIT. He has a track record of scientific commitment and

productivity, and seeks to expand upon previous training in clinical medicine, epidemiology, and genetics to

catalyze a career focused on cardiovascular genomic medicine. Mentorship, Training Activities, and

Environment. Dr. Aragam will perform the proposed work at the MGH and the Broad Institute under the

primary mentorship of Dr. Patrick Ellinor, a physician scientist and international leader in complex trait genetics

with an outstanding track record of mentorship. Co-primary mentor Dr. Steven Lubitz will provide additional

guidance with investigations in cardiovascular genetics, and complementary expertise in clinical and

epidemiological analyses leveraging the electronic health record. The mentorship team will include a highly

committed and accomplished Advisory Committee of Drs. Kathryn Lunetta, Xihong Lin, Christopher O’Donnell,

and Jacob Joseph. Formal coursework will enhance a multi-disciplinary experiential learning effort to gain

requisite skills in clinical informatics, advanced statistical genetics, computational biology, next-generation

sequencing (NGS) analyses, trans-omics, and responsible research conduct. Research. Dilated

cardiomyopathy (DCM) is a heritable cause of heart failure and the leading indication for heart transplantation

worldwide. While studies regarding the genetic causes of DCM have focused on rare, large-effect

(“monogenic”) mutations, these account for < 40% of DCM cases referred for genetic testing. The PI will

leverage multiple large databases (Total N > 1,000,000) with robust phenotypic and genotypic data to identify

common, small-effect genetic variants associated with DCM which, in aggregate, contribute to a “polygenic”

susceptibility to disease. First, the PI will conduct EHR-based phenotyping to permit a common variant

association study and meta-analysis of DCM, and then derive a DCM polygenic risk score. Second, he will

assess the longitudinal risk associated with established, monogenic DCM mutations in a population-based

cohort, and perform rare variant association analyses with clinical and subclinical DCM. Third, he will

determine how rare, monogenic mutations interact with polygenic risk, and non-genetic factors (including

clinical, lifestyle and environmental factors) to influence disease penetrance. Successful completion of the

proposed studies will yield a comprehensive assessment of the polygenic basis of DCM and the relative,

population-wide contributions of monogenic and polygenic risk to disease pathogenesis. Finally, completion of

this proposal will allow the PI to acquire new skills in several important domains (clinical informatics, advanced

statistical genetics, NGS analyses, computational biology, cloud computing, and trans-omics investigation) that

will facilitate his transition to a role as an independent physician-scientist.