A Population Kinetic Analysis of Prehepatic Insulin Secretion

Introduction

Quantitative estimation of pancreatic insulin release is necessary for the understanding of the pathogenesis of type 2 diabetes (T2D), which is characterized by a progressive loss of beta-cell function. However, direct measurement of insulin secretion rate (ISR) from beta-cells in a human is not feasible because of the need for prehepatic blood sampling. The plasma insulin concentration is accessible in vivo, but that only provides information about the posthepatic insulin delivery because insulin released from the beta-cells is partly extracted by the liver before entering the circulation. However, the ISR can be quantified indirectly using plasma C-peptide (CP) data based on the fact that CP and insulin are secreted at an equal molar ratio. The deconvolution technique can reconstruct ISR from the time course of CP and its disposition kinetics. The required CP kinetics can be acquired in a separate experiment in the same subjects or, alternatively, by using parameter values from population analysis. Another choice is the “combined model” that combines insulin and CP data in a single experiment analysis. The advantage of the combined model approach is the combined use of insulin and CP kinetics and does not require a prior knowledge of the CP kinetic parameter. However, the combined model does not accurately estimate the second-phase of insulin secretion and does not evaluate the effect of glucose on insulin secretion. The minimal model of insulin secretion can quantify both the ISR and the glucose effect on ISR. However, the minimal model describes insulin and CP kinetics separately and does capture the insulin concentration profiles well under oral glucose load.

Abstract

Quantification of insulin secretion from beta-cells is important for the understanding of the development of type 2 diabetes (T2D).

OBJECTIVES

The aim of this work is to perform a population kinetic covariate analysis of the prehepatic insulin secretion in T2D in response to an oral glucose tolerance test (OGTT) by combined use of insulin, glucose, and C-peptide (CP) data from different population groups.

METHODS

Data were collected from 149 with normal glucose tolerance (NGT), 29 with impaired glucose tolerance (IGT), and 43 T2D subjects who all underwent an OGTT. A population analysis with nonlinear mixed-effects was performed to identify significant covariates influencing the prehepatic insulin secretion.

RESULTS

Obese subjects have higher basal insulin (PB.0001) and CP level (PB.0001) than subjects with normal weight. Obesity leads to a higher insulin production (PB.0005), secretion (PB.05) from the beta-cell and lower clearance from the plasma (PB.05) than a normal weight subject. Gender, glucose tolerance, and obesity have no effects on the average hepatic insulin extraction during OGTT. The insulin clearance is the same in subjects with various glucose tolerances. Compared to the NGT subjects with normal weight, obesity leads to a 25% increase in insulin production rate, while T2D and IGT reduce the insulin production rate by 62% and 22%, respectively. The T2D has significant impact on the kinetic parameters (PB.05) that control the insulin release, resulting in a delayed and depressed insulin secretion. The differences in insulin concentration between the subject groups are mainly caused by insulin secretion.

CONCLUSION

The study shows that by a population kinetic analysis that simultaneously makes use of plasma insulin and CP data from OGTT it is possible to estimate the prehepatic insulin secretion and liver extraction and identify important population covariates.

Keywords

insulin secretion, insulin extraction, oral glucose tolerance test, insulin modeling, glucose tolerance, population analysis