Nonlinear Mixed Effects Modeling of Glucagon Kinetics Assessed Using [¹³C¹⁵N]-Glucagon in Individuals With and...

To date, few studies have quantified glucagon kinetics in humans with and without diabetes, with results often varying due to differences in experimental designs and glucagon assay methodologies. This has limited the ability to study glucagon secretion in vivo using methods such as deconvolution. To overcome these limitations, a novel stable glucagon tracer, [¹³C¹⁵N]-glucagon, along with high-resolution mass spectrometry, has been used to study glucagon kinetics and turnover in humans.In this work, we present a nonlinear mixed effects modeling approach to describe glucagon kinetics in healthy subjects and individuals with type 1 diabetes (T1D). To do so, data from a novel stable isotope-labeled glucagon tracer ([¹³C¹⁵N]-glucagon), collected in 9 healthy controls (HC) and 12 individuals with T1D following an intravenous bolus injection under basal steady-state, post-absorptive conditions, were used. Models of increasing complexity were developed and tested against the data, with model selection guided by standard criteria such as the ability of the model to describe the data, precision and physiological plausibility of parameter estimates and parsimony.A one-compartment model effectively describes typical population kinetics (TPK) of glucagon, along with the between-subject variability (BSV) and inter-occasion variability (IOV), linking individual differences to easily accessible subject characteristics. In particular, model-predicted outcome highlights that variability in glucagon kinetics is predominantly explained by individual-specific factors, like age and body weight, rather than by group-specific factors, like HC vs. T1D.Future work will focus on integrating this model into simulation platforms to enable the evaluation of advanced artificial pancreas systems, further enhancing diabetes care.Clinical Relevance- This model is crucial for assessing glucagon turnover in the post-absorptive state and represents a significant step toward the quantification of glucagon secretion in humans.