Personalized metabolic profile estimations using oral glucose tolerance tests

Oral glucose tolerance tests (OGTTs) are used commonly to diagnose diabetes mellitus (DM). However, blood glucose data and the changes in insulin induced by OGTTs contain information regarding intestinal absorption, hepatic control of glucose and insulin, pancreatic insulin secretion and peripheral tissue glucose and insulin control. Therefore, an appropriate dynamic model could reveal the above information from OGTT data. We developed an OGTT model containing five compartments for insulin dynamics and two compartments for glucose dynamics based on previous reports. Anthropometric data of individuals were used to assume the cardiac output. Simplex and Levenberg–Marquardt algorithms were then used to fit the data obtained from 42 normal subjects (24 males and 20 females) and eight subjects with DM. We found clear gender differences in the intestinal glucose absorption kinetics, glucose sensitivity in the pancreas, maximal insulin production capacity and endogenous glucose production. There were also differences between normal and DM subjects. For example, pancreatic and liver dysfunctions were evident in DM cases. The differences between normal and DM subjects in glucose and insulin dynamics in the pancreas, liver and peripheral tissues, such as insulin resistance, insulin secretion and the relative roles of glucose disposal in each organ, were demonstrated clearly and quantitatively in a time-dependent manner. This study revealed the quantitative dynamic interaction between glucose and insulin using OGTT data and revealed organ function during the OGTT. Using this approach, we identified the dysfunctional organs for glucose and insulin regulation. Data produced using this model will allow a personalized and targeted approach for health issues related to glucose and insulin.