Myocardial infarction (MI) is the leading cause of death in the United States and is heritable. Large studies focusing on common genetic variation have now identified over 30 loci associated with risk for MI. Despite this success, these common variants explain only a small proportion of the genetic basis of MI. Population genetics and candidate gene studies support the hypothesis that less common genetic variation plays a significant role in complex disorders such as MI. In this proposal, we outline several methods to explore the role of rare genetic variation in risk for MI. Using a set of rare (minor allele frequecy <5%) coding variants identified through whole exome sequencing (i.e. all protein coding regions of the genome), we will test the hypotheses that rare variants contribute to MI risk both individually and collectively and further that this knowledge can improve population-based risk stratification. To test these hypotheses, we propose the following specific aims:
in Aim 1, we will genotype exome variants in a well-powered case/control study to identify rare variants that individually contribute to risk of MI;
in Aim 2, we will develop novel computational methods for rare variant analysis to identify rare variants collectively associated with MI;and in Aim 3, we will develop a rare variant method for population-based MI risk stratification. In addition to elucidating the role of rare coding variation in risk for MI, this five-year proposal outlines a comprehensive strategy for the principal investigator's career development in academic cardiovascular medicine. This strategy logically builds on the principal investigator's previous research experience and clinical training. After obtaining a Ph.D. in Bioinformatics, the principal investigator completed residency training in Internal Medicine and is currently finishing fellowship training in Cardiovascular Disease. This proposal now focuses on expanding his scientific skills by attaining additional knowledge and practical research experience in human genetics and genomics, statistical genetics, and risk modeling. The career development goals will be achieved through a multi-faceted approach involving mentoring by Dr. Sekar Kathiresan (human genetics and genomics) and Dr. Shamil Sunyaev (statistical genetics, risk modeling), didactic coursework, scientific investigation, and training in scientific communication and research ethics. This work will take place in a unique training environment comprised of complementary experiences at Massachusetts General Hospital, Brigham and Women's Hospital, and the Broad Institute. Successful completion of this career development award will result in a better understanding of the genetic basis for MI, result in the principal investigator'transition to an independent physician-scientist, and provide a solid foundation from which he will apply for RO1-level funding.

Public Health Relevance

Heart attack is the leading cause of death in the United States and although it is heritable, its genetic basis is incompletely characterized. This proposal outlines several methods aimed at understanding the role of rare genetic variation in risk for heart attack. Success has the potential to identify new mechanisms of disease and novel strategies for prevention.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Clinical Investigator Award (CIA) (K08)
Project #
Application #
Study Section
Special Emphasis Panel (ZHL1-CSR-K (M2))
Program Officer
Carlson, Drew E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Washington University
Internal Medicine/Medicine
Schools of Medicine
Saint Louis
United States
Zip Code
Lin, Chien-Jung; Lin, Chieh-Yu; Stitziel, Nathan O (2018) Genetics of the extracellular matrix in aortic aneurysmal diseases. Matrix Biol 71-72:128-143
Emdin, Connor A; Khera, Amit V; Klarin, Derek et al. (2018) Phenotypic Consequences of a Genetic Predisposition to Enhanced Nitric Oxide Signaling. Circulation 137:222-232
Natarajan, Pradeep; Young, Robin; Stitziel, Nathan O et al. (2017) Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting. Circulation 135:2091-2101
Stitziel, Nathan O; Khera, Amit V; Wang, Xiao et al. (2017) ANGPTL3 Deficiency and Protection Against Coronary Artery Disease. J Am Coll Cardiol 69:2054-2063
Stitziel, Nathan O (2017) Human genetic insights into lipoproteins and risk of cardiometabolic disease. Curr Opin Lipidol 28:113-119
Auer, Paul L; Stitziel, Nathan O (2017) Genetic association studies in cardiovascular diseases: Do we have enough power? Trends Cardiovasc Med 27:397-404
Webb, Thomas R; Erdmann, Jeanette; Stirrups, Kathleen E et al. (2017) Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease. J Am Coll Cardiol 69:823-836
Khera, Amit V; Won, Hong-Hee; Peloso, Gina M et al. (2017) Association of Rare and Common Variation in the Lipoprotein Lipase Gene With Coronary Artery Disease. JAMA 317:937-946
Stitziel, Nathan O; Kathiresan, Sekar (2017) Leveraging human genetics to guide drug target discovery. Trends Cardiovasc Med 27:352-359
Emdin, Connor A; Khera, Amit V; Natarajan, Pradeep et al. (2016) Phenotypic Characterization of Genetically Lowered Human Lipoprotein(a) Levels. J Am Coll Cardiol 68:2761-2772

Showing the most recent 10 out of 24 publications