Pancreatic network control of glucagon secretion and counterregulation

A novel pulse-modulated closed-loop artificial pancreas based on intravenous administration of insulin and glucagon

Current attempts to implement and apply automated control systems for the management of glucose homeostasis in individuals with diabetes are partly successful. In most semi and closed loop control systems to mimic the action of a normal pancreas in diabetes patients, insulin is administered subcutaneously. However, the parameters for insulin diffusion and transport time constants are relatively large and have wide individual variations. Therefore, deviation from a normal meal can result in suboptimal euglycemic control. Stable and reliable closed loop feedback control using continuous glucose monitoring under these conditions is difficult and needs regular interventions from the user. This article describes the translation of the endocrine physiology of a normal pancreas to an electronic equivalent. With this translation, the complex effects of a direct intravenous pulsatile method of insulin and glucagon administration can be simulated in accordance with physiological observations in a healthy subject and has been built with standard electronic components. This device is applicable for any individual and under any condition to automatically maintain the desired optimal euglycemic condition. The insulin and glucagon response control is presented in the same physiological pulsatile manner as is observed in healthy individuals.

Changes in Pancreatic Endocrine Function and Morphology After Pancreaticoduodenectomy: A Comparison Between Pancreatic Head Cancer and Other Pathologies

OBJECTIVES

It is unclear whether the improved glucose metabolism in pancreas head cancer (PHC) patients after pancreaticoduodenectomy is due to the anatomical change or the relief of pancreatic duct obstruction.

METHODS

We divided 170 patients into the PHC group (n = 54, 31.8%) and other pathology (non-PHC) group (n = 116, 68.2%). Glucose metabolic function was evaluated using the glucose tolerance index (GTI), and the pancreatic duct obstruction and dilatation was measured using the pancreatic atrophic index (PAI).

RESULTS

The preoperative GTI was significantly higher in the PHC group (mean [standard deviation {SD}], 0.84 [1.16]) than in the non-PHC group (0.41 [SD, 0.59], P = 0.000). The postoperative GTI decreased significantly in the PHC group but remained unchanged in the non-PHC group. Similarly, the preoperative PAI was higher in the PHC group (0.32 [SD, 0.19]) than in the non-PHC group (0.13 [SD, 0.09], P = 0.000). The postoperative PAI decreased significantly in the PHC group, but not in the non-PHC group.

CONCLUSIONS

The impaired glucose metabolism in PHC can be caused by pancreatic duct obstruction. After pancreaticoduodenectomy, glucose metabolism is improved by the relief of pancreatic duct obstruction, and not by the anatomical change. The patients should be counseled accordingly.

Functional and morphological evolution of remnant pancreas after resection for pancreatic adenocarcinoma

Functional and morphological evolution of remnant pancreas after resection for pancreatic adenocarcinoma is investigated.The medical records of 45 patients who had undergone radical resection for pancreatic adenocarcinoma from March 2010 to September 2013 were reviewed retrospectively. There were 34 patients in the pancreaticoduodenectomy (PD) group and 10 patients in the distal pancreatectomy (DP) group. One patient received total pancreatectomy. The endocrine function was measured using the glucose tolerance index (GTI), which was derived by dividing daily maximum serum glucose fluctuation by daily minimum glucose. Remnant pancreas volume (RPV) was estimated by considering pancreas body and tail as a column, and head as an ellipsoid, respectively. The pancreatic atrophic index (PAI) was defined as the ratio of pancreatic duct width to total pancreas width. Representative indices of each patient were compared before and after resection up to 2 years postoperatively.The area under receiver operating characteristic curve of GTI for diagnosing DM was 0.823 (95% confidence interval, 0.699-0.948, P < .001). Overall, GTI increased on postoperative day 1 (POD#1, mean ± standard deviation, 1.79 ± 1.40 vs preoperative, 1.02 ± 1.41; P = .001), and then decreased by day 7 (0.89 ± 1.16 vs POD#1, P < .001). In the PD group, the GTI on POD#14 became lower than preoperative (0.51 ± 0.38 vs 0.96 ± 1.37; P = .03). PAI in the PD group was significantly lower at 1 month postoperatively (0.22 ± 0.12 vs preoperative, 0.38 ± 0.18; P < .001). In the PD group, RPV was significantly lower at 1 month postoperatively (25.3 ± 18.3 cm vs preoperative, 32.4 ± 20.1 cm; P = .02), due to the resolution of pancreatic duct dilatation. RPV of the DP group showed no significant change. GTI was negatively related to RPV preoperatively (r = -0.317, P = .04), but this correlation disappeared postoperatively (r = -0.044, P = .62).Pancreatic endocrine functional deterioration in pancreatic adenocarcinoma patients may in part be due to pancreatic duct obstruction and dilatation caused by the tumor. After resection, this proportion of endocrine insufficiency is corrected.

Paracrine regulation of glucagon secretion: the β/α/δ model

The regulation of glucagon secretion in the pancreatic α-cell is not well understood. It has been proposed that glucose suppresses glucagon secretion either directly through an intrinsic mechanism within the α-cell or indirectly through an extrinsic mechanism. Previously, we described a mathematical model for isolated pancreatic α-cells and used it to investigate possible intrinsic mechanisms of regulating glucagon secretion. We demonstrated that glucose can suppress glucagon secretion through both ATP-dependent potassium channels (K_ATP) and a store-operated current (SOC). We have now developed an islet model that combines previously published mathematical models of α- and β-cells with a new model of δ-cells and use it to explore the effects of insulin and somatostatin on glucagon secretion. We show that the model can reproduce experimental observations that the inhibitory effect of glucose remains even when paracrine modulators are no longer acting on the α-cell. We demonstrate how paracrine interactions can either synchronize α- and δ-cells to produce pulsatile oscillations in glucagon and somatostatin secretion or fail to do so. The model can also account for the paradoxical observation that glucagon can be out of phase with insulin, whereas α-cell calcium is in phase with insulin. We conclude that both paracrine interactions and the α-cell's intrinsic mechanisms are needed to explain the response of glucagon secretion to glucose.

The impact of mathematical modeling on the understanding of diabetes and related complications

Diabetes is a chronic and complex multifactorial disease caused by persistent hyperglycemia and for which underlying pathogenesis is still not completely understood. The mathematical modeling of glucose homeostasis, diabetic condition, and its associated complications is rapidly growing and provides new insights into the underlying mechanisms involved. Here, we discuss contributions to the diabetes modeling field over the past five decades, highlighting the areas where more focused research is required.

Mathematical models for insulin secretion in pancreatic β-cells

Insulin secretion is one of the most characteristic features of β-cell physiology. As it plays a central role in glucose regulation, a number of experimental and theoretical studies have been performed since the discovery of the pancreatic β-cell. This review article aims to give an overview of the mathematical approaches to insulin secretion. Beginning with the bursting electrical activity in pancreatic β-cells, we describe effects of the gap-junction coupling between β-cells on the dynamics of insulin secretion. Then, implications of paracrine interactions among such islet cells as α-, β-, and δ-cells are discussed. Finally, we present mathematical models which incorporate effects of glycolysis and mitochondrial glucose metabolism on the control of insulin secretion.

Association of Basal hyperglucagonemia with impaired glucagon counterregulation in type 1 diabetes

Glucagon counterregulation (GCR) protects against hypoglycemia, but is impaired in type 1 diabetes (T1DM). A model-based analysis of in vivo animal data predicts that the GCR defects are linked to basal hyperglucagonemia. To test this hypothesis we studied the relationship between basal glucagon (BasG) and the GCR response to hypoglycemia in 29 hyperinsulinemic clamps in T1DM patients. Glucose levels were stabilized in euglycemia and then steadily lowered to 50 mg/dL. Glucagon was measured before induction of hypoglycemia and at 10 min intervals after glucose reached levels below 70 mg/dL. GCR was assessed by CumG, the cumulative glucagon levels above basal; MaxG, the maximum glucagon response; and RIG, the relative increase in glucagon over basal. Analysis of the results was performed with our mathematical model of GCR. The model describes interactions between islet peptides and glucose, reproduces the normal GCR axis and its impairment in diabetes. It was used to identify a control mechanism consistent with the observed link between BasG and GCR. Analysis of the clinical data showed that higher BasG was associated with lower GCR response. In particular, CumG and RIG correlated negatively with BasG (r = −0.46, p = 0.012 and r = −0.74, p < 0.0001 respectively) and MaxG increased linearly with BasG at a rate less than unity (p < 0.001). Consistent with these results was a model of GCR in which the secretion of glucagon has two components. The first is under (auto) feedback control and drives a pulsatile GCR and the second is feedback independent (basal secretion) and its increase suppresses the GCR. Our simulations showed that this model explains the observed relationships between BasG and GCR during a three-fold simulated increase in BasG. Our findings support the hypothesis that basal hyperglucagonemia contributes to the GCR impairment in T1DM and show that the predictive power of our GCR animal model applies to human pathophysiology in T1DM.

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

In health, the pancreatic islet cells work as a network with highly co-ordinated signals over time to balance glycaemia within a narrow range. In type 1 diabetes (T1DM), with autoimmune destruction of the β-cells, lack of insulin is considered the primary abnormality and is the primary therapy target. However, replacing insulin alone does not achieve adequate glucose control and recent studies have focused on controlling the endogenous glucagon release as well. In T1DM, glucagon secretion is disordered but not absolutely deficient; it may be excessive postprandially yet it is characteristically insufficient and delayed in response to hypoglycaemia. We review our system-level analysis of the pancreatic endocrine network mechanisms of glucagon counterregulation (GCR) and their dysregulation in T1DM and focus on possible use of α-cell inhibitors (ACIs) to manipulate the glucagon axis to repair the defective GCR. Our results indicate that the GCR abnormalities are of 'network origin'. The lack of β-cell signalling is the primary deficiency that contributes to two separate network abnormalities: (i) absence of a β-cell switch-off trigger and (ii) increased intraislet basal glucagon. A strategy to repair these abnormalities with ACI is proposed, which could achieve better control of glycaemia with reduced hypoglycaemia risk.

Models of glucagon secretion, their application to the analysis of the defects in glucagon counterregulation and potential extension to approximate glucagon action

This 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.