Genomic analysis of the metabolic and microbial basis of human disease

Abstract

Genetics influences the phenotype and behavior of living organism. Human genetic variants have been widely linked to diseases, while the biological pathways through which genetic variants affect the physiology remain unclear. Genetic associations with molecular traits, for example levels of plasma metabolites, may aid the interpretation of genetic associations on higher-order phenotypes. The human body is a symbiont with a large number of microbial organisms, which have a close relationship with human health. In particular, the gut microbiota can influence various organs of human host through the synthesis of bioactive metabolites. Understanding the microbial organisms living in the human body holds great promise for increasing our understanding of human health and disease.

This thesis focuses on genetic aspects of metabolic and microbial traits and has four general aims: 1. To identify genetic determinants of human plasma metabolite levels and prioritize metabolites with putative causality on complex diseases. 2. To identify genetic associations on gut microbiota and determine how these are relevant to host-microbe interactions. 3. To identify causal associations between gut microbes and plasma metabolites and characterize how these relate to diseases. 4. To identify novel genetic determinants of drug resistance in Mycobacterium tuberculosis and characterize the lineage-specific profiles of drug-resistant mutations.

Through this research, I uncovered novel insights into communicable and non-communicable diseases in humans. In addition to identifying novel genetic loci associated with metabolism, my work prioritized plasma metabolites with putative causal effects on complex diseases. The robust genetic associations with gut microbiota expand our understanding of host-microbe interactions and may facilitate precision intervention of the gut microbiota. Causal relationships between gut microbes and plasma metabolites suggest that plasma metabolites may be involved in the microbial effects on human diseases. In infectious diseases, distinct lineage-specific profiles on drug-resistant associated mutations may guide public health decisions on tuberculosis control and treatment.

In summary, this thesis demonstrates how genomic information can be leveraged to generate hypotheses, prioritize biomarkers, and uncover disease causality. The results expand our understanding of the human body as a complex symbiont.