Cholesterol Metabolism Pathways Disturbances in Atherosclerosis—Analyses Using Stochastic Petri Net-Based Model

Abstract

Atherosclerosis is a multifactorial disease that affects large arteries and causes much morbidity and mortality worldwide. Despite ongoing research for several decades, it is still a global health problem that cannot be stopped and cured completely. Furthermore, the development of this disease is contributed to by various processes, primarily disturbances in cholesterol metabolism, local low-grade inflammation, and oxidative stress, resulting in the formation of atherosclerotic plaques. In this work, a stochastic Petri net model was constructed and subsequently analyzed to examine the impact of these factors on the development and progression of atherosclerosis. The use of knockout- and simulation-based analysis allowed for a comprehensive investigation of the studied phenomena. Our research has demonstrated that while cholesterol is a contributing factor in atherosclerosis, blocking its impact alone is insufficient in halting the progression of this disorder. Inhibition of oxidative stress is also important when blocking the impact of phosphoprotein phosphatase inhibitor-1 (PPI-1), microsomal triglyceride transfer protein (MTTP), and 3-hydroxy-3-methyl-glutaryl coenzyme A reductase (HMGCR), as our model shows that this action reduces the number of foam cells underlying atherosclerosis. The results obtained further support the previous observations that the combined treatment is significantly effective in enhancing therapeutic efficacy against atherosclerosis.