SPINA Carb: a simple mathematical model supporting fast in-vivo estimation of insulin sensitivity and beta cell function

Sci Rep. 2022 Oct 21;12(1):17659. doi: 10.1038/s41598-022-22531-3.

Abstract

Modelling insulin-glucose homeostasis may provide novel functional insights. In particular, simple models are clinically useful if they yield diagnostic methods. Examples include the homeostasis model assessment (HOMA) and the quantitative insulin sensitivity check index (QUICKI). However, limitations of these approaches have been criticised. Moreover, recent advances in physiological and biochemical research prompt further refinement in this area. We have developed a nonlinear model based on fundamental physiological motifs, including saturation kinetics, non-competitive inhibition, and pharmacokinetics. This model explains the evolution of insulin and glucose concentrations from perturbation to steady-state. Additionally, it lays the foundation of a structure parameter inference approach (SPINA), providing novel biomarkers of carbohydrate homeostasis, namely the secretory capacity of beta-cells (SPINA-GBeta) and insulin receptor gain (SPINA-GR). These markers correlate with central parameters of glucose metabolism, including average glucose infusion rate in hyperinsulinemic glucose clamp studies, response to oral glucose tolerance testing and HbA1c. Moreover, they mirror multiple measures of body composition. Compared to normal controls, SPINA-GR is significantly reduced in subjects with diabetes and prediabetes. The new model explains important physiological phenomena of insulin-glucose homeostasis. Clinical validation suggests that it may provide an efficient biomarker panel for screening purposes and clinical research.

MeSH terms

  • Biomarkers
  • Blood Glucose / metabolism
  • Glycated Hemoglobin A
  • Humans
  • Insulin / pharmacology
  • Insulin Resistance* / physiology
  • Models, Theoretical
  • Receptor, Insulin

Substances

  • Receptor, Insulin
  • Blood Glucose
  • Glycated Hemoglobin A
  • Insulin
  • Biomarkers