INTEGRATIVE OMICS REVEALS INSIGHTS INTO HUMAN LIVER DEVELOPMENT, DISEASE ETIOLOGY, AND PRECISION MEDICINE
Transcriptomic regulation of human liver is a tightly controlled and highly dynamic process. Genetic and environmental exposures to this process play pivotal roles in the development of multiple liver disorders. Despite accumulating knowledge have gained through large-scale genomics studies in the developed adult livers, the contributing factors to the interindividual variability in the pediatric livers remain largely uninvestigated. In the first two chapters of the present study, we addressed this question through an integrative analysis of both genetic variations and transcriptome-wide RNA expression profiles in a pediatric human liver cohort with different developmental stages ranging from embryonic to adulthood. Our systematic analysis revealed a transcriptome-wide transition from stem-cell-like to liver-specific profiles during the course of human liver development. Moreover, for the first time, we observed different genetic control of hepatic gene expression in different developmental stages. Motivated by the critical roles of genetics variations and development in regulating hepatic gene expression, we constructed robust predictive models to impute the virtual liver gene expression using easily available genotype and demographic information. Our model is promising in improving both PK/PD modeling and disease diagnosis for pediatric patients. In the last two chapters of the study, we analyzed the genomics data in a more liver disease- related context. Specifically, in the third chapter, we identified Macrophage migration inhibitory factor (MIF) and its related pathways as potential targets underlying human liver fibrosis through an integrative omics analysis. In the last chapter, utilizing the largest-to-date publicly available GWAS summary data, we dissected the causal relationships among three important and clinically related metabolic diseases: non-alcoholic fatty liver disease (NAFLD), type 2 diabetes (T2D), and obesity. Our analysis suggested new subtypes and provided insights into the precision treatment or prevention for the three complex diseases. Taken together, through integrative analysis of multiple levels of genomics information, we improved the current understanding of human liver development, the pathogenesis of liver disorders, and provided implications to precision medicine.