Leveraging Multi-Omics data to Understand Genetic and Biological Mechanisms underlying Fatty Acid Metabolism and Coronary Artery Disease

Polyunsaturated fatty acids (PUFAs) and their metabolites play critical roles in various aspects of human physiology and health and coronary artery disease (CAD) is a leading cause of mortality worldwide. In my dissertation work, I leveraged multi-omics data to understand genetic and biological mechanisms underlying Fatty Acid metabolism and coronary artery disease using multiple statistical approaches. In the first chapter, I described the different types of molecular ‘omics data, the available analytical techniques, and the backgrounds of PUFAs and CAD. In the second chapter, I estimated the global proportional of Amerind ancestry in 1102 Hispanic Americans from the Multi-Ethnic Study of Atherosclerosis (MESA), and demonstrated strong negative associations between Amerind genetic ancestry and PUFA levels. In the third chapter, I performed a meta-analysis of Genome-wide association study (GWAS) of PUFAs in Hispanic Americans and African Americans to identify multiple novel signals spanning a > 9 Mb region on chromosome 11 (57.5 Mb ~ 67.1 Mb) and demonstrated that multiple associations are unique to Hispanic Americans. In the fourth chapter, I applied colocalization analysis and correlation network analysis to prioritize seven potential causal genes of coronary artery diseases and subclinical atherosclerosis using MESA multi-omics data. In the last chapter, I summarized my research work and discussed the future direction of leveraging the molecular ‘omics data to provide a comprehensive insight of the biological mechanism of the complex human diseases.