Abstract 179: Computational Modelling Of Early Atherosclerotic Plaque Structure Reveals The Role Of The Rate Of Lipid Deposition On Plaque Structure And Growth Rate

Abstract

Much current research on inflammation in atherosclerosis focuses on specific cellular and biochemical processes as isolated phenomena. There is scope, therefore, for an integrated approach that examines the interactions between the various mechanisms involved in early plaque growth. An in silico modelling approach is promising in this regard as multiple biological processes can easily be incorporated into the model and used to simulate early plaque growth under a variety of conditions. We present a computational model to simulate early plaque growth and test the hypothesis that higher rates of lipid deposition in the artery wall will cause accelerated plaque growth and influence the plaque’s morphology and composition. We formulate a mathematical model based on the observed interactions between macrophages, pro-atherogenic extracellular lipid, lipid accumulated by macrophages, and apoptotic cells/cellular debris. This basic model incorporates several key processes including monocyte recruitment, phagocytosis, proliferation, apoptosis, lipid cytotoxicity, and cell migration. The model is used to computationally simulate how the early development of the plaque is influenced by its physiological environment, focusing in particular on the rate of lipid influx into the artery wall. Individual simulations yield a profile of how cells and lipids are spatially distributed over the plaque, and how this distribution and the total plaque size evolve in time. The model qualitatively suggests that the rate of lipid deposition has a key influence on early plaque morphology and behaviour. Specifically, increasing the rate of lipid deposition (simulating higher fat diets) accelerates the rate of plaque growth. The ratio of apoptotic cells to active macrophages also increases with distance from the endothelium, with the ratio becoming more pronounced in older plaques. The computational model provides a novel methodology with which to capture the dynamics and structure of early atherosclerotic plaques, and provides a foundation on which to build models that can account for further aspects of the relevant biology, including plaque regression and necrotic core formation.