Computationally Modelling Cholesterol Metabolism and Atherosclerosis

Davies, Callum and Morgan, Amy E and Mc Auley, Mark T (2023) Computationally Modelling Cholesterol Metabolism and Atherosclerosis. Biology, 12 (8). ISSN 2079-7737

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Abstract

Cardiovascular disease (CVD) is the leading cause of death globally. The underlying pathological driver of CVD is atherosclerosis. The primary risk factor for atherosclerosis is elevated low-density lipoprotein cholesterol (LDL-C). Dysregulation of cholesterol metabolism is synonymous
with a rise in LDL-C. Due to the complexity of cholesterol metabolism and atherosclerosis mathematical models are routinely used to explore their non-trivial dynamics. Mathematical modelling has generated a wealth of useful biological insights, which have deepened our understanding of these processes. To date however, no model has been developed which fully captures how whole-body cholesterol metabolism intersects with atherosclerosis. The main reason for this is one of scale. Whole body cholesterol metabolism is defined by macroscale physiological processes, while atherosclerosis operates mainly at a microscale. This work describes how a model of cholesterol metabolism was combined with a model of atherosclerotic plaque formation. This new model is capable of reproducing the output from its parent models. Using the new model, we demonstrate how this system can be utilized to identify interventions that lower LDL-C and abrogate plaque formation.

Item Type:	Article
Faculty / Department:	Faculty of Human and Digital Sciences > School of Health and Sport Sciences
Depositing User:	Amy Morgan
Date Deposited:	31 Oct 2023 16:04
Last Modified:	31 Oct 2023 16:04
URI:	https://hira.hope.ac.uk/id/eprint/4053

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