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A Mathematical Model of Atherosclerosis with Reverse Cholesterol Transport and Associated Risk Factors

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Abstract

Atherosclerosis, the leading cause of death in the US, is a disease in which a plaque builds up inside the arteries. The low density lipoprotein (LDL) and high density lipoprotein (HDL) concentrations in the blood are commonly used to predict the risk factor for plaque growth. In a recent paper (Hao and Friedman in Plos One e90497, 2014), we have developed a mathematical model of plaque growth which includes the (LDL, HDL) concentrations. In the present paper, we have refined that model by including the effect of reverse cholesterol transport. By exploration-by-examples of regression of a plaque in mice, our model simulations suggest that such drugs as used for mice may also slow plaque growth in humans. We next proceeded to explore the effects of oxidative stress or antioxidant deficiency, high blood pressure and cigarette smoking as risk factors. We suggest for an individual in one of these three risk categories and with specified (LDL, HDL) concentration, how to reduce or eliminate the risk of atherosclerosis.

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Acknowledgments

This research has been supported by the Mathematical Biosciences Institute and the National Science Foundation under Grant DMS 0931642. We would like to express our thanks to Drs. Sanjay Rajagopalan and Andrei Maiseyeu at University of Maryland, Baltimore for helpful discussions.

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Authors and Affiliations

  1. Department of Mathematics, Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA

    Avner Friedman

  2. Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA

    Wenrui Hao

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  1. Avner Friedman
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Correspondence to Wenrui Hao.

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Friedman, A., Hao, W. A Mathematical Model of Atherosclerosis with Reverse Cholesterol Transport and Associated Risk Factors. Bull Math Biol 77, 758–781 (2015). https://doi.org/10.1007/s11538-014-0010-3

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