PROJECT SUMMARY/ABSTRACT Type 1 diabetes (T1D) is a highly prevalent disorder affecting over 8 million individuals worldwide. T1D causes significant morbidity and mortality, including acute complications such as diabetic ketoacidosis as well as chronic complications such as nephropathy, neuropathy, retinopathy, and cardiovascular disease. Developing a deeper understanding of T1D risk factors is critical to reduce diabetes-related complications, to identify individuals at high risk for T1D, and potentially to delay or to prevent the onset of T1D. Because T1D is characterized by autoimmune destruction of insulin-producing beta cells, T1D risk is strongly influenced by genetic variants related to immune function. Genetic risk for T1D can be quantified with a polygenic score, which integrates the disease risk of causal variants from across the genome. Current polygenic scores have demonstrated excellent predictive power to identify those individuals most likely to develop T1D. However, most existing scores were developed and validated in individuals with European genetic ancestry, and their predictive power declines when applied to other populations. In this proposal, we will develop a multi-ancestry T1D polygenic score that integrates genetic variants from diverse ancestral populations. We will apply this score to predict risk for T1D as well as for certain atypical immune-mediated forms of diabetes, which may share genetic risk factors with T1D. Additionally, we will apply computational methods that analyze T1D genetic risk factors to identify genetic subtypes of T1D. The proposed project will provide advanced training in computational biology and statistical genetics. The research setting represents an ideal environment for junior investigators, combining the world-class clinical expertise of Massachusetts General Hospital with the innovative computational resources of the Broad Institute. This project will provide a foundation for the candidate to apply for independent research funding and ultimately to establish a career as a physician scientist.