A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data

Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the model's delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction. Author summary The adipose tissue is no longer considered a metabolically quiescent tissue. Disturbances in non-esterified fatty acid (NEFA) metabolism leading to ectopic fat deposition have been associated with the development of insulin resistance. In recent years, the use of stable isotope tracers coupled with arteriovenous sampling across tissue depots has greatly improved our knowledge of postprandial NEFA dynamics. In this study, we make use of arteriovenous measurements collected across the abdominal subcutaneous adipose tissue in humans during a high fat mixed meal to evaluate three existing computational models of adipose tissue metabolism. As the three models included in this study were not capable of fully describing the measured adipose tissue fluxes, we present a new model of human in vivo adipose tissue metabolism, introducing novel terms such as the postprandial uptake of glycerol. We then utilised our refined model to quantify the effect of caloric restriction on adipose tissue metabolism by fitting the model to mixed meal challenge test data collected before and after a weight-loss intervention. Parameter estimates indicate an increase in the rates of glycerol and NEFA release coupled with a decrease in the delay of insulin signalling for all reactions, suggesting improved insulin sensitivity following caloric restriction.