UC San Diego

The two most common forms of diabetes are type 1 diabetes (T1D) which is an autoimmune disorder and type 2 diabetes (T2D) which is a metabolic disorder. Large-scale genome-wide association studies (GWAS) have identified hundreds of loci associated with disease risk, but determining the molecular mechanisms of these loci is not trivial. One major challenge in interpreting GWAS loci is that there is extensive linkage disequilibrium in the human genome where many variants will show association through linkage with the causal variant but not be causal themselves. A second challenge is that most GWAS loci map to non-coding regions of the genome and have no immediately obvious function or affected gene. Together these challenges motivate research to fine-map causal variants at diabetes risk loci and leverage epigenomic and functional genomic data to determine the mechanisms of fine-mapped variants.

In my work I developed strategies and created resources for fine-mapping diabetes risk signals identified in GWAS and determining their molecular mechanisms. In the first chapter, we identify genetic risk shared by T1D and T2D. We then fine-map causal variants at specific shared loci and perform molecular characterization of candidate causal variants at the shared risk loci GLIS3 and CTRB1/2 in pancreatic islets. In the second chapter, we use ATAC-seq and RNA-seq on dexamethasone-treated and untreated pancreatic islets to generate a map of glucocorticoid- responsive islet chromatin sites and gene expression, as well as genetic variants that interact with glucocorticoid signaling to affect islet regulation. We identify enrichment of T2D-associated variants in glucocorticoid-responsive islet chromatin and characterize a fine-mapped T2D risk variant with glucocorticoid-dependent effects on islet accessible chromatin and SIX2/3 expression. Finally, in the third chapter we develop a novel framework for allelic imbalance mapping using ChIP-seq and ATAC-seq data. We quantify the allelic effects of variants on epigenomic sequencing data in islets and liver cells and demonstrate that these effects can help predict likely causal variants for expression QTLs and T2D risk loci. At the HMG20A locus, we identify a fine-mapped T2D risk variant with allelic imbalance in pancreatic islet accessible chromatin and validate allelic effects on pancreatic islets.