TY - JOUR
T1 - Modeling the dynamics of glucose, insulin, and free fatty acids with time delay
T2 - The impact of bariatric surgery on type 2 diabetes mellitus
AU - Murillo, Anarina L.
AU - Li, Jiaxu
AU - Castillo-Chavez, Carlos
N1 - Funding Information:
The authors would like to acknowledge Dr. Sherry Towers for her help and suggestions on the technical and statistical aspects of our final manuscript. This project has been partially supported by grants from the Alfred P. Sloan Foundation, the Graduate Assistance in Areas of National Need (GAANN), the National Science Foundation (DMS 1263374), the National Security Agency (H98230-15-1-0021), the Office of the President of ASU, and the Office of the Provost at ASU. ALM would like to acknowledge funding by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) grant number T32HL072757. This research is partially supported by the
Funding Information:
The authors would like to acknowledge Dr. Sherry Towers for her help and suggestions on the technical and statistical aspects of our final manuscript. This project has been partially supported by grants from the Alfred P. Sloan Foundation, the Graduate Assistance in Areas of National Need (GAANN), the National Science Foundation (DMS 1263374), the National Security Agency (H98230-15-1-0021), the Office of the President of ASU, and the Office of the Provost at ASU. ALM would like to acknowledge funding by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) grant number T32HL072757. This research is partially supported by the Brown University Data Science Initiative.
Publisher Copyright:
© 2019 the Author(s), licensee AIMS Press.
PY - 2019
Y1 - 2019
N2 - The role of free fatty acids (FFA) on Type 2 diabetes mellitus (T2DM) progression has been studied extensively with prior studies suggesting that individuals with shared familial genetic predisposition to metabolic-related diseases may be vulnerable to dysfunctional plasma FFA regulation. A harmful cycle arises when FFA are not properly regulated by insulin contributing to the development of insulin resistance, a key indicator for T2DM, since prolonged insulin resistance may lead to hyperglycemia. We introduce a hypothesis-driven dynamical model and use it to evaluate the role of FFA on insulin resistance progression that is mathematically constructed within the context of individuals that have genetic predisposition to dysfunctional plasma FFA. The dynamics of the nonlinear interactions that involve glucose, insulin, and FFA are modeled by incorporating a fixed-time delay with the corresponding delay-differential equations being studied numerically. The results of computational studies, that is, extensive simulations, are compared to the known minimal ordinary differential equations model. Parameter estimation and model validation are carried out using clinical data of patients who underwent bariatric surgery. These estimates provide a quantitative measure that is used to evaluate the regulation of lipolysis by insulin action measured by insulin sensitivity, within a metabolically heterogeneous population (non-diabetic to diabetic). Results show that key metabolic factors improve after surgery, such as the effect of insulin inhibition of FFA on insulin and glucose regulation, results that do match prior clinical studies. These findings indicate that the reduction in weight or body mass due to surgery improve insulin action for the regulation of glucose, FFA, and insulin levels. This reinforces what we know, namely, that insulin action is essential for regulating FFA and glucose levels and is a robust effect that can be observed not only in the long-term, but also in the short-term; thereby preventing the manifestation of T2DM.
AB - The role of free fatty acids (FFA) on Type 2 diabetes mellitus (T2DM) progression has been studied extensively with prior studies suggesting that individuals with shared familial genetic predisposition to metabolic-related diseases may be vulnerable to dysfunctional plasma FFA regulation. A harmful cycle arises when FFA are not properly regulated by insulin contributing to the development of insulin resistance, a key indicator for T2DM, since prolonged insulin resistance may lead to hyperglycemia. We introduce a hypothesis-driven dynamical model and use it to evaluate the role of FFA on insulin resistance progression that is mathematically constructed within the context of individuals that have genetic predisposition to dysfunctional plasma FFA. The dynamics of the nonlinear interactions that involve glucose, insulin, and FFA are modeled by incorporating a fixed-time delay with the corresponding delay-differential equations being studied numerically. The results of computational studies, that is, extensive simulations, are compared to the known minimal ordinary differential equations model. Parameter estimation and model validation are carried out using clinical data of patients who underwent bariatric surgery. These estimates provide a quantitative measure that is used to evaluate the regulation of lipolysis by insulin action measured by insulin sensitivity, within a metabolically heterogeneous population (non-diabetic to diabetic). Results show that key metabolic factors improve after surgery, such as the effect of insulin inhibition of FFA on insulin and glucose regulation, results that do match prior clinical studies. These findings indicate that the reduction in weight or body mass due to surgery improve insulin action for the regulation of glucose, FFA, and insulin levels. This reinforces what we know, namely, that insulin action is essential for regulating FFA and glucose levels and is a robust effect that can be observed not only in the long-term, but also in the short-term; thereby preventing the manifestation of T2DM.
KW - Free fatty acids
KW - Mathematical model
KW - Type 2 diabetes
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U2 - 10.3934/mbe.2019288
DO - 10.3934/mbe.2019288
M3 - Article
C2 - 31499737
AN - SCOPUS:85070509627
SN - 1547-1063
VL - 16
SP - 5765
EP - 5787
JO - Mathematical Biosciences and Engineering
JF - Mathematical Biosciences and Engineering
IS - 5
ER -