Insulin sensitivity predictions in individuals with obesity and type II diabetes mellitus using mathematical model of the insulin signal transduction pathway

Abstract

Mathematical modeling approaches have been commonly used in complex signaling pathway studies such as the insulin signal transduction pathway. Our expanded mathematical model of the insulin signal transduction pathway was previously shown to effectively predict glucose clearance rates using mRNA levels of key components of the pathway in a mouse model. In this study, we re-optimized and applied our expanded model to study insulin sensitivity in other species and tissues (human skeletal muscle) with altered protein activities of insulin signal transduction pathway components. The model has now been optimized to predict the effect of short term exercise on insulin sensitivity for human test subjects with obesity or type II diabetes mellitus. A comparison between our extended model and the original model showed that our model better simulates the GLUT4 translocation events of the insulin signal transduction pathway and glucose uptake as a clinically relevant model output. Results from our extended model correlate with O'Gorman's published in-vivo results. This study demonstrates the ability to adapt this model to study insulin sensitivity to many biological systems (human skeletal muscle and mouse liver) with minimal changes in the model parameters.

Keywords: Insulin sensitivity; Insulin signal transduction pathway; Mathematical modeling.