Models of Glucagon Secretion, Their Application to the Analysis of the Defects in Glucagon Counterregulation and Potential Extension to Approximate Glucagon Action

Abstract

Abbreviations: (BG) blood glucose, (GABA) γ-aminobutyric acid, (GCR) glucagon counterregulation, (GLP-1) glucagon-like peptide-1, (HGO) hepatic glucose output, (ID 50 AbstractThis review analyzes an interdisciplinary approach to the pancreatic endocrine network-like relationships that control glucagon secretion and glucagon counterregulation (GCR). Using in silico studies, we show that a pancreatic feedback network that brings together several explicit interactions between islet peptides and blood glucose reproduces the normal GCR axis and explains its impairment in diabetes. An α-cell auto-feedback loop drives glucagon pulsatility and mediates triggering of GCR by hypoglycemia by a rapid switch-off of β-cell signals. The auto-feedback explains the enhancement of defective GCR in β-cell deficiency by a switch-off of signals in the pancreas that suppress α cells. Our models also predict that reduced β-cell activity decreases and delays the GCR. A key application of our models is the in silico simulation and testing of possible scenarios to repair defective GCR in β-cell deficiency. In particular, we predict that partial suppression of hyperglucagonemia may repair the impaired GCR. We also outline how the models can be extended and tested using human data to become a part of a larger construct including the regulation of the hepatic glucose output by the pancreas, circulating glucose, and incretins. In conclusion, a model of the normal GCR control mechanisms and their dysregulation in insulin-deficient diabetes is proposed and partially validated. The model components are clinically measurable, which permits its application to the study of the abnormalities of the human endocrine pancreas and their role in the progression of many diseases, including diabetes, metabolic syndrome, polycystic ovary syndrome, and others. It may also be used to examine therapeutic responses.

Optimizing reduction in basal hyperglucagonaemia to repair defective glucagon counterregulation in insulin deficiency

“…We have also shown that the MCN could account for the observed in vivo pulsatile GCR response to hypoglycaemia triggered by switch‐off signals in insulin deficiency as detailed in figure 2 in Ref. [27] (see also Ref. [21]).…”

“…Using our MCN model we simulated the response to hypoglycaemia assuming different strategies of glucagon reduction: gradual suppression of AFI or AFR glucagon, or both. Reduction in AFI glucagon improved (figure 4[27], top curve), while reduction in AFR secretion reduced the GCR (figure 4[27], lower curve). However, if inhibition of both AFI and AFR glucagon is assumed (as expected during an ACI infusion) the model predicts initial GCR enhancement followed by GCR gradual decline (figure 4[27], middle curve).…”

Insulin Therapy and Hypoglycemia

“…There are promising animal data, but as yet no convincing proof in humans that this may occur. 73,74 …”

Mathematical models for insulin secretion in pancreatic β-cells

“…[112][113][114][115][116] Their complex behaviors, however, may not obviously be addressed by probing α-, β-and δ-cells separately. Even if they are not physically connected with each other, they communicate with each other via paracrine interactions which are mediated by hormones [117][118][119][120] or neurotransmitters.…”

“…On the other hand, the role of δ-cells is not fully known although there are reports that somatostatin secreted from δ-cells inhibits both α and β-cells. [127][128][129][130] In conclusion, despite both theoretical and experimental efforts as to the questions over the past 30 y, [112][113][114][115][116]127,128,131 there still lacks concrete understanding of the roles of the paracrine interactions among islet cells in glucose homeostasis. A variety of complicated interactions in an islet makes it difficult to recognize their roles, and existing experiments have focused mostly on static responses of the endocrine cells.…”