Abstract
Technological advances in the digital age mean that researchers can now produce vastquantities 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.
Keywords: systems biology, bioinformatics, degeneration, Alzheimer’s disease,
Parkinson’s disease, lipodystrophy, muscle regeneration
| Date of Award | 1 Mar 2023 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Supervisor | affiliated academic (Supervisor) & Adil Mardinoglu (Supervisor) |