Towards a mechanistic explanation of insulin resistance, which incorporates mTOR, autophagy, and mitochondrial dysfunction

Type 2 diabetes is a global disease which affects an increasing number of people every year. At the heart of the disease lies insulin resistance in the target tissues, primarily fat and muscle. The insulin resistance is caused by the failure of a complex signalling network, and several mechanistic hypotheses for this failure have been proposed. Herein, we evaluate a hypothesis that revolves around the protein mammalian target of rapamycin (mTOR) and its feedback signals to insulin receptor substrate-1 (IRS1). In particular, we have re-examined this hypothesis and relevant biological data using a mathematical modelling approach. During the course of modelling we gained several important insights. For instance, the model was unable to reproduce the relation between the EC50-values in the dose-response curves for IRS1 and its serine residue 312 (Ser-312). This implies that the presented hypothesis, where the phosphorylation of Ser-312 lies downstream of the tyrosine phosphorylation of IRS1, is inconsistent with the provided data, and that the hypothesis or the data might be incorrect. Similarly, we also realized that in order to fully account for the information in the dose-response data, time curves needed to be incorporated into the model. A preliminary model is presented, which explains most of the data-sets, but still is unable to describe all the details in the data. The originally proposed hypothesis as an explanation to the given data has been revised, and our analysis serves to exemplify that an evaluation of a mechanistic hypothesis by mere biochemical reasoning often misses out on important details, and/or leads to incorrect conclusions. A model-based approach, on the other hand, can efficiently pin-point such weaknesses, and if combined with a comprehensive understanding of biological variation and generation of experimental data, mathematical modelling can prove to be a method of great potential in the search for mechanistic explanations to the cause of insulin resistance in type 2 diabetics.