Poster

Mathematical Modeling Postprandial Lipoprotein Metabolism and Investigating the Effects of the Bariatric Surgery

eSMB2020 eSMB2020 Follow 2:30 - 3:30pm EDT, Monday - Wednesday
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Vehpi Yildirim

Erzurum Technical University
"Mathematical Modeling Postprandial Lipoprotein Metabolism and Investigating the Effects of the Bariatric Surgery"
Obesity has become one of the most serious public health issues over the past decades. Dyslipidemia, which is characterized by elevated plasma triglyceride-rich lipoprotein levels and disrupted plasma cholesterol profiles, is a major health risk associated with obesity. Bariatric surgery is one of the most effective methods for treating obesity. In addition to a significant weight loss, surgery induces remarkable improvements in plasma lipid profiles and insulin sensitivity indices. Even though the improving effects of bariatric surgery on the plasma lipid profiles and lipoprotein metabolism are well recognized, due to the complex nature of metabolism, the underlying mechanism is not fully understood. Lipoproteins are complex biochemical assemblies of lipids and apoproteins that transport water-insoluble triglycerides and cholesterol from the liver and intestines to the peripheral tissues. Studies show that lipoprotein metabolism is regulated by insulin and different lipoprotein species compete for the same clearance pathways in the circulation. The complexity induced by these regulatory mechanisms, interactions and feedbacks make computational models very effective for investigating lipoprotein metabolism. In this study, we introduce a physiologically based multicompartmental model of hepatic and intestinal lipoprotein metabolisms. The model is designed to utilize stable isotopic enrichment and biochemical concentration data that has been collected during a mixed meal test. Hence, unlike several other models in the literature, the current model enables estimating metabolic parameters under non-steady-state conditions. An insulin module has been incorporated into the model to explore insulin-mediated regulations by utilizing available insulin data. The gastrointestinal module is designed to simulate the anatomical changes induced by gastric bypass surgery. This way, the model can comparatively analyze pre and post-surgery data to better understand the improvements induced at each metabolic pathway following the surgery. Finally, we test our model with pre- and post-surgery clinical data that has been collected from patients that went through Roux-en-y gastric bypass surgery. Our results indicate that, after the surgery, postprandial plasma lipoprotein clearance is significantly increased. Another key finding is that insulin-mediated stimulation of lipoprotein clearance is ameliorated. Furthermore, measured insulin responsiveness indices are significantly correlated with model estimates. Work done with
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Virtual conference of the Society for Mathematical Biology, 2020.