Leveraging human genetics and functional genomics to investigate insulin resistance related disorders
- DeForest, Natalie
- Advisor(s): Majithia, Amit
Abstract
Insulin resistance plays a central role in the development of multiple epidemic metabolic disorders such as type 2 diabetes (T2D) and cardiovascular disease. In this dissertation, I leverage human genetics and functional genomics to unravel the molecular mechanisms underlying insulin resistance and its related disorders, as well as identify novel key effector genes for potential therapeutic applications. The work is divided into four chapters:Chapter 1 provides an overview of the recent large-scale T2D genetic studies with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discusses recent work on the use and limitations of genetic risk scores for T2D risk prediction. Chapter 2 describes deep mutational scanning of 11,970 protein-coding HNF1A variants in human hepatocytes and clinical correlation with 553,246 exome- sequenced individuals which identifies gain-of-function mutations in HNF1A which exert pleiotropic effects, conferring protection against diabetes while increasing the hepatic secretion of atherogenic lipoproteins. Chapter 3 utilizes genetic determinants of circulating protein levels to perform proteome-wide Mendelian Randomization which identifies RSPO3 as a critical mediator of non-alcoholic steatohepatitis (NASH) pathogenesis. Chapter 4 presents a genome-wide association study for the serum triglyceride to HDL-cholesterol ratio and subsequent integrative genomics which systematically prioritizes novel insulin resistance effector genes with insights into tissues of action and directional effects on metabolic disease. Collectively, this dissertation demonstrates the power of integrating large-scale human genetics with functional genomics in elucidating the intricate mechanisms contributing to insulin resistance-related disorders. These findings contribute to the growing body of knowledge in the field, offering novel insights into the pathogenesis of insulin resistance and its related disorders and identifying potential candidate genes for further investigation and therapeutic targeting.