Modeling the effect of glucagon on endogenous glucose production in healthy individuals under meal-like conditions

Defective postprandial glucagon suppression contributes to chronic hyperglycemia in type 2 diabetes. Although insulin action and secretion have been extensively and quantitatively studied in the literature, less effort has been made to quantify the glucagon stimulatory effect on endogenous glucose production (EGP). This study aims to model the glucagon effect on EGP in healthy humans, capturing the decline of its action following sustained hyperglucagonemia. We analyzed data from 54 nondiabetic individuals studied on two occasions, where they received a glucose, labeled with [3-3H]-glucose, and an insulin infusion, mimicking systemic appearance after an oral glucose challenge, whereas endogenous hormone secretion was suppressed by somatostatin. Glucagon was infused at a rate of 0.65 ng/kg/min starting at 0 min (nonsuppressed occasion) or 120 min to mimic postprandial glucagon suppression (suppressed occasion). Plasma glucose, insulin, and glucagon concentrations were frequently measured for 300 min, and model-independent estimates of EGP were obtained from tracer specific activity. Several physiological models describing the EGP time course as a function of plasma glucose, insulin, and glucagon concentrations were developed and compared, each implementing a different hypothesis for the evanescence of glucagon effect. The best model successfully described EGP using the glucagon-to-insulin ratio and over-basal glucose to account for the waning glucagon effect. The model precisely estimated hepatic glucagon and insulin sensitivities. However, the glucose effect was excessively delayed, likely reflecting a cascade of other biological signals rather than the direct effect of hyperglycemia on the liver.NEW & NOTEWORTHY The model can be used to quantify hepatic glucagon and insulin sensitivity, accounting also for glucagon evanescence over time. The ability to quantify glucagon effects on postprandial glucose metabolism will further our understanding of its role in the onset and progression of type 2 diabetes. These findings can also be used in the design of novel glucagon-based therapies where accurate modeling of glucagon action is required to meet efficacy and safety standards.