PROJECT SUMMARY/ ABSTRACT Cardiovascular disease is the leading cause of morbidity and mortality for patients with type 2 diabetes (T2DM). Determining cardiovascular effects of T2DM therapies is of clinical importance. Human genetics may be a strategy to provide insights to long-term effects of T2DM therapies and mechanisms linking T2DM and cardiovascular risk. Dipeptidyl peptidase 4 (DPP4) inhibitors are used for the treatment of T2DM and decrease degradation of substrates with possible metabolic or cardiovascular effects such as glucagon like peptide-1 (GLP-1), neuropeptides, CXCL12, brain natriuretic peptide, and substance P. Although they have the benefit of improving glucose dynamics through GLP-1 effects, DPP4 inhibitors are also associated with increased risk of hospitalization for heart failure (such as during saxagliptin), potentially related to negative effects of neuropeptides, CXCL12, and substance P. Long-term data on cardiovascular effects of DPP4 inhibition remain limited as the longest cardiovascular outcomes trial of DPP4 inhibitors was only three years. Our preliminary data in among individuals in the Penn Medicine Biobank show that on gene burden analysis for rare loss of function variants, DPP4 loss of function was significantly associated with heart failure. Phenotyping individuals with DPP4 loss of function will provide further insights as to the possible mechanism for this finding and long- term effects of decreased DPP4 activity and antigen in humans. We hypothesize that genetic DPP4 loss of function will be associated with improved metabolic parameters but also with heart failure and related biomarkers/ imaging. We will identify individuals in the Penn Medicine Biobank with DPP4 loss of function variants and their matched controls and recruit them for a phenotyping study. We will also enroll participants in a pilot clinical trial to assess the response of individuals heterozygous for DPP4 loss of function to pharmacologic DPP4 inhibition. The candidate has a strong multi-disciplinary mentoring team with experts in patient oriented research, genetics, endocrinology, cardiology (advanced heart failure), mathematical modeling/ biostatistics, and metabolomics/ proteomics. The candidate will gain necessary skills and expertise during the award period in the areas of: genetics, a genetic-based approach to clinical trials recruitment, mathematical modeling of insulin sensitivity and insulin secretion, advanced biostatistics, and leadership skills. This will facilitate the candidate achieving necessary milestones to become an independent academic physician-scientist specializing in the use of genetics and clinical trials approaches to answer questions in T2DM and metabolism, cardiovascular risk, and related therapies.