A molecular phenomics approach to complex multisystemic diseases
File(s)
Author(s)
Begum, Sofina
Type
Thesis
Abstract
The age of -omics has set a precedent for precision medicine, yet one of the most prevalent challenges is multi-omics data integration, with no platform yet that can efficiently integrate clinical and multi-omic data. This thesis uses several integrative data strategies to deconvolute complex multisystemic disease states, utilising clinical, cytokine profiling, metagenomic and metabonomic data to gain greater depth and understanding. High-throughput metabolic profiling methods have been employed for in-depth systemic analysis of SARS-CoV-2 infection, Primary Biliary Cholangitis and paediatric burn injury. Correlation analysis and derived clustering methods were utilised for data integration, following multivariate analyses and reveal disease state specific signatures. Similarly, different biofluids (plasma, urine, faeces) contributed specific complementary information. Several systemic biomarkers were identified for each disease, each with hallmarks of organ dysfunction. This work highlights the value of data integration in heavily confounded data and disease.
Version
Open Access
Date Issued
2021-05
Date Awarded
2021-08
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Holmes, Elaine
Nicholson, Jeremy
Garcia-Perez, Isabel
Sponsor
Medical Research Council (Great Britain)
Publisher Department
Department of Metabolism, Digestion and Reproduction
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)