Abstract

Several models for the long-term development of T2DM already exist, focusing on the dynamics of the interaction between glycemia, insulinemia and β-cell mass. Current models consider representative (fasting or daily average) glycemia and insulinemia as characterizing the compensation state of the subject at some instant in slow time. This implies that only these representative levels can be followed through time and that the role of fast glycemic oscillations is neglected. An improved model (DPM15) for the long-term progression of T2DM is proposed, introducing separate peripheral and hepatic (liver and kidney) insulin actions. The DPM15 model no longer uses near-equilibrium approximation to separate fast and slow time scales, but rather describes, at each step in slow time, a complete day in the life of the virtual subject in fast time. The model can thus represent both fasting and postprandial glycemic levels and describe the effect of interventions acting on insulin-enhanced tissue glucose disposal or on insulin-inhibited hepatic glucose output, as well as on insulin secretion and β-cell replicating ability. The model can simulate long-term variations of commonly used clinical indices (HOMA-B, HOMA-IR, insulinogenic index) as well as of Oral Glucose Tolerance or Euglycemic Hyperinsulinemic Clamp test results. The model has been calibrated against observational data from the Diabetes Prevention Program study: it shows good adaptation to observations as a function of very plausible values of the parameters describing the effect of such interventions as Placebo, Intensive LifeStyle and Metformin administration.

Highlights

  • We previously introduced a mathematical model of Type 2 Diabetes Mellitus (T2DM) [10], which was able to replicate acceptably well the observed time courses of fasting glycemia and diabetes incidence [18], when compared quantitatively with the results of the non-intervention group in a large study of individuals at-risk for T2DM [the Diabetes Prevention Program (DPP) study [19,20,21]]

  • The goal of the present work is to detail the assumptions underlying the functional form of the new model, named DPM15; to justify the numerical values assigned to its parameters; and to show model forecasts corresponding to all of the endpoints that were recorded in the DPP study

  • The model to be described is named DPM15 since it is the 15th version of Diabetes Progression Model we built in the ongoing effort to capture the relevant features of the development of this disease

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Summary

Introduction

Mathematical modelling is being increasingly used in diabetology, in order to help explain the mechanisms of normal and diseased control of the glucose-insulin system, both in short-term dynamical perturbation experiments and in the long-term development of the disease [1,2,3,4,5,6]. A novel fast-slow model of diabetes progression able to access the data in the same manner as the authors. Interested researchers can replicate the study findings exactly and in their entirety by implementing the equations constituting the model described in the Methods section; populating the implementation with the parameter values reported in the Tables; and plotting the resulting model predictions together with the averages of the DPP study data at each time point

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