Applied Chemical Engineering

A computational model for the dietary control of insulin, glucose, fatty acid metabolism and type 2 diabetes

Baozhu Guo

Department of Public Health, International College, Krirk University , Bang Khen, Bangkok, 10220, Thailand

Shih-Pin Lee

Department of Public Health, International College, Krirk University , Bang Khen, Bangkok, 10220, Thailand

DOI: https://doi.org/10.59429/ace.v7i3.5563

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Abstract

Non-alcoholic fatty liver disease (NAFLD) is a significant global public health issue, closely related to poor dietary habits and excessive energy intake. Type 2 diabetes（T2DM） is closely related to NAFLD. Due to the complex regulation of dietary factors on the interaction between insulin, glucose, and free fatty acids (FFA), existing metabolic models have limitations in characterizing the dynamic response of this system. This paper uses an improved mathematical model to simulate the dynamic effects of different dietary compositions on insulin, glucose, and FFA, the study adopts a delayed feedback mechanism to construct a system of differential equations, which describes the relationship between postprandial insulin secretion and the fluctuations of glucose and FFA. The results show that the model can effectively simulate the fluctuating behavior of metabolic parameters under postprandial conditions, verifying its predictive potential in the study of NAFLD and dietary interventions.

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References

[1]. Targher G, Corey KE, Byrne CD, Roden M. The complex link between NAFLD and type 2 diabetes mellitus—mechanisms and treatments. Nature reviews Gastroenterology & hepatology. 2021;18(9):599-612.

[2]. Cernea S, Raz I. NAFLD in type 2 diabetes mellitus: Still many challenging questions. Diabetes/Metabolism Research and Reviews. 2021;37(2):e3386.

[3]. Valenti L, Bugianesi E, Pajvani U, Targher G. Nonalcoholic fatty liver disease: cause or consequence of type 2 diabetes? Liver International. 2016;36(11):1563-79.

[4]. Tilg H, Moschen AR. Evolution of inflammation in nonalcoholic fatty liver disease: the multiple parallel hits hypothesis. Hepatology. 2010;52(5):1836-46.

[5]. Perry RJ, Peng L, Barry NA, Cline GW, Zhang D, Cardone RL, et al. Acetate mediates a microbiome-brain-beta-cell axis to promote metabolic syndrome. Nature. 2016;534(7606):213-7.

[6]. Deng M, Wen Y, Yan J, Fan Y, Wang Z, Zhang R, et al. Comparative effectiveness of multiple different treatment regimens for nonalcoholic fatty liver disease with type 2 diabetes mellitus: a systematic review and Bayesian network meta-analysis of randomised controlled trials. BMC medicine. 2023;21(1):447.

[7]. Mu W, Cheng X-f, Liu Y, Lv Q-z, Liu G-l, Zhang J-g, et al. Potential nexus of non-alcoholic fatty liver disease and type 2 diabetes mellitus: insulin resistance between hepatic and peripheral tissues. Frontiers in pharmacology. 2019;9:1566.

[8]. Sturis J, Polonsky KS, Mosekilde E, Van Cauter E. Computer model for mechanisms underlying ultradian oscillations of insulin and glucose. American Journal of Physiology-Endocrinology And Metabolism. 1991;260(5):E801-E9.

[9]. Tolić IM, Mosekilde E, Sturis J. Modeling the insulin–glucose feedback system: the significance of pulsatile insulin secretion. Journal of theoretical biology. 2000;207(3):361-75.

[10]. König M, Bulik S, Holzhütter HG. Quantifying the contribution of the liver to glucose homeostasis: a detailed kinetic model of human hepatic glucose metabolism. PLoS computational biology. 2012;8(6):e1002577.

[11]. Dalla Man C, Rizza RA, Cobelli C. Meal simulation model of the glucose-insulin system. IEEE Trans Biomed Eng. 2007;54(10):1740-9.

[12]. Pratt AC, Wattis JA, Salter AM. Mathematical modelling of hepatic lipid metabolism. Math Biosci. 2015;262:167-81.

[13]. Kosic M, Benkovic M, Jurina T, Valinger D, Gajdos Kljusuric J, Tusek AJ. Analysis of Hepatic Lipid Metabolism Model: Simulation and Non-Stationary Global Sensitivity Analysis. Nutrients. 2022;14(23).

[14]. Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics. 2003;19(4):524-31.

[15]. Wilkinson DJ. Stochastic modelling for systems biology: Chapman and Hall/CRC; 2018.

[16]. Funahashi A, Matsuoka Y, Jouraku A, Morohashi M, Kikuchi N, Kitano H. CellDesigner 3.5: a versatile modeling tool for biochemical networks. Proceedings of the IEEE. 2008;96(8):1254-65.

[17]. Novère NL, Hucka M, Mi H, Moodie S, Schreiber F, Sorokin A, et al. The systems biology graphical notation. Nature biotechnology. 2009;27(8):735-41.

[18]. Finck BN. Targeting metabolism, insulin resistance, and diabetes to treat nonalcoholic steatohepatitis. Diabetes. 2018;67(12):2485-93.

[19]. Stefanovski D, Punjabi NM, Boston RC, Watanabe RM. Insulin Action, Glucose Homeostasis and Free Fatty Acid Metabolism: Insights From a Novel Model. Frontiers in endocrinology. 2021;12:625701.

[20]. Li Y, Chow CC, Courville AB, Sumner AE, Periwal V. Modeling glucose and free fatty acid kinetics in glucose and meal tolerance test. Theor Biol Med Model. 2016;13:8.

[21]. Roy A, Parker RS. Dynamic modeling of free fatty acid, glucose, and insulin: An extended" minimal model". Diabetes technology & therapeutics. 2006;8(6):617-26.

[22]. Petäjä EM, Yki-Järvinen H. Definitions of normal liver fat and the association of insulin sensitivity with acquired and genetic NAFLD—a systematic review. International journal of molecular sciences. 2016;17(5):633.

[23]. Topp B, Promislow K, deVries G, Miura RM, Finegood DT. A model of beta-cell mass, insulin, and glucose kinetics: pathways to diabetes. J Theor Biol. 2000;206(4):605-19.

[24]. Topp BG, Atkinson LL, Finegood DT. Dynamics of insulin sensitivity, -cell function, and -cell mass during the development of diabetes in fa/fa rats. Am J Physiol Endocrinol Metab. 2007;293(6):E1730-5.

[25]. Ribbing J, Hamren B, Svensson MK, Karlsson MO. A model for glucose, insulin, and beta-cell dynamics in subjects with insulin resistance and patients with type 2 diabetes. J Clin Pharmacol. 2010;50(8):861-72.

[26]. Bridgewater A, Huard B, Angelova M. Amplitude and frequency variation in nonlinear glucose dynamics with multiple delays via periodic perturbation. Journal of Nonlinear Science. 2020;30(3):737-66.

[27]. Sedaghat AR, Sherman A, Quon MJ. A mathematical model of metabolic insulin signaling pathways. American Journal of Physiology-Endocrinology and Metabolism. 2002;283(5):E1084-E101.

[28]. Mason IC, Qian J, Adler GK, Scheer F. Impact of circadian disruption on glucose metabolism: implications for type 2 diabetes. Diabetologia. 2020;63(3):462-72.

[29]. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444(7121):840-6.

[30]. Forbes JM, Cooper ME. Mechanisms of diabetic complications. Physiological reviews. 2013;93(1):137-88.

[31]. Bloomgarden ZT. Developments in diabetes and insulin resistance. Diabetes Care. 2006;29(1):161-7.

[32]. Efendić S, Wajngot A, Cerasi E, Luft R. Insulin release, insulin sensitivity, and glucose intolerance. Proceedings of the National Academy of Sciences. 1980;77(12):7425-9.

[33]. Smith GI, Shankaran M, Yoshino M, Schweitzer GG, Chondronikola M, Beals JW, et al. Insulin resistance drives hepatic de novo lipogenesis in nonalcoholic fatty liver disease. The Journal of clinical investigation. 2020;130(3):1453-60.

[34]. Alves-Bezerra M, Cohen DE. Triglyceride Metabolism in the Liver. Compr Physiol. 2017;8(1):1-8.

[35]. Gad AI, Ibrahim NF, Almadani N, Mahfouz R, Nofal HA, El-Rafey DS, et al. Therapeutic Effects of Semaglutide on Nonalcoholic Fatty Liver Disease with Type 2 Diabetes Mellitus and Obesity: An Open-Label Controlled Trial.Diseases. 2024;12(8):186.