Analysis of Large-Scale Human Genetic Datasets to Identify Novel Risk Factors and Therapeutic Targets for Cardiometabolic Disease
Emdin, Connor A.
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CitationEmdin, Connor A. 2020. Analysis of Large-Scale Human Genetic Datasets to Identify Novel Risk Factors and Therapeutic Targets for Cardiometabolic Disease. Doctoral dissertation, Harvard Medical School.
AbstractThrough the analysis of large-scale human genetic datasets, I identify five therapeutic targets and risk factors for cardiometabolic disease. First, using Mendelian randomization, I demonstrate that body fat distribution is a causal risk factor for coronary artery disease and type 2 diabetes, with a similar magnitude of effect on disease risk as body mass index. Second, exploiting the genetic association between body fat distribution and type 2 diabetes, I identify a series of damaging variants in the receptor ALK7 that reduce abdominal adiposity and protect against type 2 diabetes. These findings suggest that pharmacologic ALK7 antagonism may be useful in the treatment of type 2 diabetes. Third, I show that genetic nitric oxide signaling protects against cardiovascular disease and improves renal function, suggesting that nitric oxide signaling agents such as PDE5A inhibitors could be repurposed for the treatment of cardiovascular and renal disease. Fourth, through the analysis of rare predicted loss-of-function variants in UK Biobank, I identify that deficiency in GPR151, a G-protein coupled receptor, and PDE3B, an intracellular enzyme, protects against obesity and coronary artery disease, respectively. These findings suggest that pharmacologic GPR151 inhibition may be a novel therapeutic approach to weight loss. Finally, I show that healthy lifestyle can mitigate inherited genetic predisposition to risk of cardiovascular disease, identifying a non-pharmacologic method of reducing genetic risk for coronary artery disease.
Citable link to this pagehttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365220