Using Mathematical Modelling and Electrochemical Analysis to Investigate Age‐Associated Disease
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AbstractPeople are living longer. With this rise in life expectancy, a concomitant rise in morbidity in later life is observed; with conditions including cardiovascular disease (CVD), and cancer. However, ageing and the pathogenesis of age related disease, can be difficult to study, as the ageing process is a complex process, which affects multiple systems and mechanisms. The aim of this research was two‐fold. The first aim was to use mathematical modelling to investigate the mechanisms underpinning cholesterol metabolism, as aberrations to this system are associated with an increased risk for CVD. To better understand cholesterol from a mechanistic perspective, a curated kinetic model of whole body cholesterol metabolism, from the BioModels database, was expanded in COPASI, to produce a model with a broader range of mechanisms which underpin cholesterol metabolism. A range of time course data, and local and global parameter scans were utilised to examine the effect of cholesterol feeding, saturated fat feeding, ageing, and cholesterol ester transfer protein (CETP) genotype. These investigations revealed: the model behaved as a hypo‐responder to cholesterol feeding, the robustness of the cholesterol biosynthesis pathway, and the impact CETP can have on healthy ageing. The second aim of this work was to use electrochemical techniques to detect DNA methylation within the engrailed homeobox 1 (EN1) gene promoter, which has been implicated in cancer. Hypermethylation of this gene promoter is often observed in a diseased state. Synthetic DNA, designed to represent methylated and unmethylated variants, were adsorbed onto a gold rotating disk electrode for electrochemical analysis by 1) electrochemical impedance spectroscopy (EIS), 2) cyclic voltammetry (CV) and 3) differential pulse voltammetry (DPV). The technique was then applied to bisulphite modified and asymmetrically amplified DNA from the breast cancer cell line MCF‐7. Results indicated that electrochemical techniques could detect DNA methylation in both synthetic and cancer derived DNA, with EIS producing superiorresults. These non‐traditional techniques ofstudying age related disease were effective for the investigation of cholesterol metabolism and DNA methylation, and this work highlights how these techniques could be used to elucidate mechanisms or diagnose/monitor disease pathogenesis, to reduce morbidity in older people
CitationMorgan, A. E. (2019). Using Mathematical Modelling and Electrochemical Analysis to Investigate Age‐Associated Disease. (Doctoral dissertation). University of Chester, United Kingdom.
PublisherUniversity of Chester
TypeThesis or dissertation
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