User:Johnsy/Lipoprotein Modelling

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Modeling Lipoprotein Metabolism and the Action of Statins

Figure 1 A Lipoprotein

BEng Final Year Individual Project 2007/2008

John Sy
Department of Bioengineering, Imperial College London

Supervisor: Dr. M Barahona


The field of systems biology is an expanding field which seeks to help understand biological phenomena using the language of mathematics and engineering. With statistics showing that a larger population of the West is becoming clinically obese and the incidence of cardiovascular diseases dramatically increasing in the past decade, it is imperative that we take a step towards understanding the mechanism behind disease and how to correct it. This project aims to tackle the problem of hypercholesterolemia and extend current mathematical models of lipoprotein production, delivery, and metabolism. Furthermore, the project seeks to develop a mathematical understanding of how statins affect the de novo synthesis of cholesterol within both hepatic and extrahepatic cells.

Introduction and Motivation

Mathematical models have helped shape our current understanding of the way most of our world works, especially in the physical and macromolecular world where classical physics and Newtonian mechanics has dominated for several centuries. However, there is a strong drive to seek mathematical models to explain biological phenomena. Well established engineering fields such as electrical engineering or mechanical engineering have relied on mathematical models, but due to the dynamic nature of biological systems, modeling them is more difficult.

The health care industry has grown over the past decade, and the US alone spends over $2 trillion per annum and is expected to double by 2015. With an increasing population, advancements in health care, and under changing health care consumer demands, the medical industry can no long afford to wait for serendipitous events to occur such as the discovery of the small pox vaccine or the discovery of penicillin. By creating and building on simple mathematical models to reflect the physiology of the human body, we hope to eliminate the need for in vivo testing on animals in the future and more precisely understand drug interactions through the use of technology. Although the gold standard of mathematical biology and systems biology is to create a complete model of all the pathways in the human body and be able to input molecular structures of drugs, we are far from achieving this. In the meantime, we can create models to simulate certain pathways and hopefully gain a more complete understanding of the effects of perturbations in the system.

Lipoprotein metabolism is of significance and should be studied because of its strong link to atherosclerosis and coronary heart disease (CHD), now the number one cause of death in the United States. Existing models of lipoprotein metabolism have focused on the macromolecular physiology of lipoproteins, mainly the production, delivery, and degradation of these particles and how intracellular cholesterol levels are affected by this pathway. However, low density lipoproteins (LDL) and intermediate density lipoproteins (IDL) are not the only source of cholesterol and the importance of this pathway varies with diet and plasma cholesterol levels. (Meddings, 1986) The other important pathway which contributes to intracellular cholesterol levels is the de novo pathway where cholesterol is synthesized from the precursor acetyl-CoA through a series of enzyme-dependent steps in the mevalonate pathway. Statins, drugs which have been clinically shown to decrease the plasma cholesterol concentrations significantly, affect this de novo pathway by inhibiting the rate-determining enzyme, HMG-CoA reductase. The biochemistry and structure of the enzyme is further discussed in the Biology and Biochemical Background section.

Analysis of our model through stability and bifurcation analysis will hopefully give us insight into which parameters have the greatest effect on both intracellular cholesterol levels and plasma cholesterol levels. With these results in mind, pharmaceutical companies, nutritionists, and medical practitioners will be able to target specific intermediates in cholesterol transport and production depending on which parameters affect cholesterol levels the greatest.


Part 1: Background

  • Understand the mechanism by which cholesterol is produced in cells (cholesterol biosynthesis) beginning from Acetyl-CoA and which enzymes limit the rate at which cholesterol and its derivatives are produced.
  • Understand the pathways for maintaining cholesterol homeostasis in the human body and various diseased states resulting in a level of blood cholesterol away from homeostasis.
  • Develop an understanding of the structure and function of lipoproteins and how they are transported into and out of the cells in the human body, especially the liver and intestinal cells.
  • Reserach and understand current models of lipoprotein transport and metabolism.

Part 2: Model Extension & Development

  • Adapt and develop the current models of lipoprotein metabolism to more accurately reflect the biochemistry of the process.
  • Adapt and develop the current models to fit specific cell types, such as hepatocytes, and account for the variation in function of those different cell types.

Part 3: Model Testing & Limits

  • Understand the mechanism by which statins affect HMG-CoA reductase and test input parameters of the mathematical models developed to account for its actions.
  • Understand the importance of lipoproteins, especially LDL, to the generation of atherosclerosis.
  • Test the model with various physiological parameters in an attempt to better understand the effects of diseases such as familial hypercholesterolemia (FH)

Project Sections

  1. Cholesterol Biosynthesis
  2. Cholesterol Homeostasis
  3. Lipoprotein Structure & Function
  4. Current Models of Lipoprotein Metabolism
  5. Biochemical Modelling
  6. Lipoprotein Model Development
  7. Final Lipoprotein Model Development
  8. De Novo Cholesterol Synthesis Modelling
  9. Bile Acid Biosynthesis
  10. Compartmental Modelling
  11. Model Analysis
  12. References

Project Reports