부산대학교 도서관

Technological advances in the digital age mean that researchers can now produce vast quantities of data. These data have the potential to shape the way that human health and disease are viewed. Mathematical and statistical analysis of high-dimensional biological molecular data, or omics data, reveals a paradigm shift that human disease is a product of faulty metabolism, be it caused by genetics or the environment. It therefore follows that metabolic modulation should be able to act as a treatment for such diseases, and metabolic considerations should be factored into prophylactic and curative medicines. In this doctoral thesis incorporating papers, I describe the role of systems biology in the analysis of omics data and how it is used to drive discovery of treatments for human degenerative diseases. The current investigation describes a full journey around the cycle of data-driven biomarker identification, use of animal models of metabolism, and human clinical trials. This work introduces a focus shift away from single toxic species and towards reporter metabolites whose modulation is more tangible and have the potential to reverse the degenerative phenotype. I illustrate this with work focusing on Alzheimer's disease, Parkinson's disease, congenital generalised lipodystrophy, and muscle stem cells.