Modeling cholesterol metabolism and atherosclerosis.

Area of Science:

• Cardiovascular Diseases
• Systems Biology
• Computational Biology

Background:

• Atherosclerotic cardiovascular disease (ASCVD) is a major cause of death, with elevated low-density lipoprotein cholesterol (LDL-C) as a primary risk factor.
• Cholesterol metabolism and atherogenesis involve complex, multifaceted regulatory mechanisms.
• Investigating these intricate processes presents significant challenges.

Purpose of the Study:

• To provide an overview of cholesterol metabolism and atherosclerosis.
• To introduce mathematical modeling approaches in this field.
• To critically discuss existing models and identify future research directions.

Main Methods:

• Review of scientific literature on cholesterol metabolism, atherosclerosis, and mathematical modeling.
• Analysis of systems biology approaches applied to cardiovascular research.
• Critical evaluation of computational models relevant to ASCVD.

Main Results:

• Mathematical modeling is pivotal in deciphering the dynamics of cholesterol metabolism and atherogenesis.
• Models have provided novel insights into the key drivers of ASCVD.
• The review synthesizes current understanding and highlights modeling's potential.

Conclusions:

• Mathematical modeling offers a powerful framework for understanding complex biological systems like cholesterol metabolism and ASCVD.
• Further development and application of computational models are crucial for advancing ASCVD research.
• This review serves as a guide for utilizing mathematical approaches in cardiovascular disease studies.