PROJECT SUMMARY Type 2 diabetes (T2D) is a major cause of morbidity and mortality in the USA and worldwide. Identification of genes increasing susceptibility to T2D would substantially improve public health by providing biological and clinical data about development and treatment of T2D and by advising lifestyle changes in at-risk individuals. Our overall goal is to identify the functional variants, target genes, and mechanisms responsible for T2D and diabetes-related quantitative trait (QT) association signals. Previously, we have identified hundreds of novel loci for T2D and QTs by leading and contributing to genome-wide association study (GWAS) analyses and meta- analyses. To examine loci, we identified candidate genes and developed and applied methods to predict regulatory variants. We used experimental manipulation, including regulatory variant assays and genome editing, to identify mechanisms by which variant alleles bind transcriptional regulators and increase or decrease expression of specific target genes and alter traits such as insulin secretion. In this proposal, we seek to extend these successes to additional T2D and QT loci. We will study the two key and complementary aspects of T2D pathogenesis, insulin resistance and insulin secretion, by focusing on association signals that (1) affect gene regulation in the liver, or (2) act through insulin processing in pancreatic islets. Specifically, we will map liver transcriptional regulatory elements using chromatin accessibility data in hundreds of samples, identify chromatin accessibility quantitative trait loci (caQTL), perform multi-omic integration to identify variants and genes that affect T2D risk and QT variability, and assess the function of variants and genes using high throughput transcriptional reporter assays, genome editing, and assays of liver gene function. We will identify genetic variants and target genes that alter insulin processing and secretion by integration of known and new proinsulin GWAS loci with pancreatic islet multi-omic data, characterize mechanistic pathways, and assess the function of candidate variants and genes using regulatory assays, genome editing, and assays of insulin and proinsulin secretion. To accelerate advances in T2D genetics including cross-tissue analyses, we will share data via T2D web portals. Successful completion of this work will translate T2D association signals into biological insights and potential therapeutic targets. We will identify risk variants, the mechanisms by which they affect gene function, and their pathological effects on disease processes, guiding studies that evaluate novel therapies and intervene in at-risk individuals to prevent disease.