Anthony L. McCall

Resolving the Conundrum of Islet Transplantation by Linking Metabolic Dysregulation, Inflammation, and Immune Regulation

Although type 1 diabetes cannot be prevented or reversed, replacement of insulin production by transplantation of the pancreas or pancreatic islets represents a definitive solution. At present, transplantation can restore euglycemia, but this restoration is short-lived, requires islets from multiple donors, and necessitates lifelong immunosuppression. An emerging paradigm in transplantation and autoimmunity indicates that systemic inflammation contributes to tissue injury while disrupting immune tolerance. We identify multiple barriers to successful islet transplantation, each of which either contributes to the inflammatory state or is augmented by it. To optimize islet transplantation for diabetes reversal, we suggest that targeting these interacting barriers and the accompanying inflammation may represent an improved approach to achieve successful clinical islet transplantation by enhancing islet survival, regeneration or neogenesis potential, and tolerance induction. Overall, we consider the proinflammatory effects of important technical, immunological, and metabolic barriers including: 1) islet isolation and transplantation, including selection of implantation site; 2) recurrent autoimmunity, alloimmune rejection, and unique features of the autoimmune-prone immune system; and 3) the deranged metabolism of the islet transplant recipient. Consideration of these themes reveals that each is interrelated to and exacerbated by the other and that this connection is mediated by a systemic inflammatory state. This inflammatory state may form the central barrier to successful islet transplantation. Overall, there remains substantial promise in islet transplantation with several avenues of ongoing promising research. This review focuses on interactions between the technical, immunological, and metabolic barriers that must be overcome to optimize the success of this important therapeutic approach.

Insulin Therapy and Hypoglycemia

Hypoglycemia is the most important and common side effect of insulin therapy. It is also the rate limiting factor in safely achieving excellent glycemic control. A three-fold increased risk of severe hypoglycemia occurs in both type 1 and type 2 diabetes with tight glucose control. This dictates a need to individualize therapy and glycemia goals to minimize this risk. Several ways to reduce hypoglycemia risk are recognized and discussed. They include frequent monitoring of blood sugars with home blood glucose tests and sometimes continuous glucose monitoring (CGM) in order to identify hypoglycemia particularly in hypoglycemia unawareness. Considerations include prompt measured hypoglycemia treatment, attempts to reduce glycemic variability, balancing basal and meal insulin therapy, a pattern therapy approach and use of a physiological mimicry with insulin analogues in a flexible manner. Methods to achieve adequate control while focusing on minimizing the risk of hypoglycemia are delineated in this article.

Reduced Daily Risk of Glycemic Variability: Comparison of Exenatide with Insulin Glargine

BACKGROUNDnConventional methods describing daily glycemic variability (i.e., standard deviation and coefficient of variation) do not express risk. Low and High Blood Glucose Indices (LBGI and HBGI, respectively) and Average Daily Risk Range (ADRR) are parameters derived from self-monitored blood glucose (SMBG) data that quantify risk of glycemic excursions and temporal aspects of variability. In the present study, variability parameters were used to assess effects of exenatide and insulin glargine on risk of acute blood glucose extremes.nnnMETHODSnNew (LBGI, HBGI, and ADRR) and conventional variability analyses were applied retrospectively to SMBG data from patients with type 2 diabetes suboptimally controlled with metformin and a sulfonylurea plus exenatide or insulin glargine as a next therapeutic step. Exenatide- (n = 282) and insulin glargine-treated (n = 267) patients were well matched.nnnRESULTSnExenatide treatment reduced ADRR overall (exenatide, mean +/- SEM, 16.33 +/- 0.45; insulin glargine, 18.54 +/- 0.49; P = 0.001). Seventy-seven percent of exenatide-treated patients were at low risk for glucose variability compared with 62% of glargine-treated patients (P = 0.00023). LBGI for exenatide remained minimal for all categories and significantly lower than glargine for all comparisons, and HBGI for exenatide remained low or moderate for all categories and significantly lower than glargine after the morning and evening meals. Reduced variability in exenatide-treated patients was shown by conventional methods but provided no indications of risk.nnnCONCLUSIONSnAverage glycemic control was similar for both treatment groups. However, exenatide treatment minimized risk for glycemic variability and extremes to a greater degree than insulin glargine treatment.

The Median Is Not the Only Message: A Clinician's Perspective on Mathematical Analysis of Glycemic Variability and Modeling in Diabetes Mellitus

Hemoglobin A1c (HbA1c), a long-term, integrated average of tissue exposure to hyperglycemia, is the best reflection of average glucose concentrations and the best proven predictor of microvascular complications of diabetes mellitus. However, HbA1c fails to capture glycemic variability and the risks associated with extremes of hypoglycemia and hyperglycemia. These risks are the primary barrier to achieving the level of average glucose control that will minimize both the microvascular and the long-term macrovascular complications of type 1 diabetes. High blood glucose levels largely due to prandial excursions produce oxidative and inflammatory stress with potential acceleration of preexisting atherosclerosis and increased cardiovascular risk. Moreover, some temporal aspects of glycemic variation, including the rates of rise and fall of glucose, are associated with adverse cognitive and mood symptoms in those with diabetes. Methods to quantify the risk of glycemic extremes, both high and low, and the variability including its temporal aspects are now more precise than ever. These important endpoints should be included for use in clinical trials as useful metrics and recognized by regulatory agencies, which has not been the case in the past. Precise evaluation of glycemic variability and its attendant risks are essential in the design of optimal therapies; for these reasons, inclusion of these metrics and the pulsatile hormone patterns in mathematical models may be essential. For the clinician, the incursion of mathematical models that simulate normal and pathophysiological mechanisms of glycemic control is a reality and should be also gradually incorporated into clinical practice.

Diabetes mellitus and the central nervous system

Publisher Summary Diabetes mellitus (DM) disturbs central nervous system (CNS) function and may injure the brain. An emerging body of literature has shown that there are manifold biological effects of diabetes on the brain. Insulin action on the brain influences neurotransmission. Diabetes increases the risk of stroke and exacerbates stroke damage and mortality. Stroke damage is worsened potentially both through the effects of hyperglycemia and lack of insulin upon brain biochemistry in the presence of ischemia. The major treatment side effect of diabetes, which is hypoglycemia, may acutely impair brain function and, when severe and prolonged, may permanently injure the brain largely through excitotoxic mechanisms or cause death. The physiological adaptations of blood-brain barrier (BBB) function, brain metabolism, cerebral blood flow, and microvascular function may occur with either hyper- or hypoglycemia. Future research directions should delineate new areas and mechanisms of abnormalities in brain function in diabetes. Future research should also explore the basis for CNS functional alterations in acute and chronic hyper- and hypoglycemia. It would be desirable to initiate clinical trials to limit the adverse CNS effects of diabetes on stroke. A better understanding of how hyper- and hypoglycemia impair brain function may help spare the brain from the harm of altered metabolism in diabetes. This chapter focuses on clinically relevant pathophysiology. It deals with the studies that relate altered insulin and glucose concentrations to both short- and long-term adverse consequences to the brain.

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.

IDDM, Counterregulation, and the Brain

Does the brain of a person with IDDM respond to hypoglycemia differently than the brain of someone without diabetes? This is one of several questions raised by the provocative article by George et al. (1) in this issue. Recognition of hypoglycemia and the counterregulatory defenses against hypoglycemia are thought to be mediated primarily through discrete brain regions (2,3)If this thinking is correct, might the observation by George and colleagues be explained as an effect of IDDM on the brain signaling? Importantly, experimental studies in animals and humans suggest that both diabetes (2) and hypoglycemia (3) may exert potentially deleterious effects on the brain. The study by George et al. (1) concludes that those with IDDM recover awareness of hypoglycemia more rapidly than do those without diabetes. In this study, moderate hyperglycemia was maintained between hypoglycemic challenges. Two days after a brief period of hypoglycemia, eight subjects with uncomplicated diabetes showed normal responses (except for the peak and threshold norepinephrine response) to being rechallenged with hypoglycemia. This recovery is more rapid than the recovery the authors previously found in nondiabetic subjects. To begin addressing the questions raised by this study, we must understand its clinical background. We also need to review the pathophysiology of how both diabetes and hypoglycemia affect the brain. The important clinical backdrop for this study relates to the good news/bad news conundrum raised by the data from the Diabetes Control and Complications Trial (DCCT) (4) and other similar studies, such as the Stockholm Diabetes Intervention Study (5). The good news, of course, is that substantial and clinically relevant reductions in risk for all of the major chronic metabolic complications of IDDM are achieved with intensive insulin therapy that attains close to normal levels of HbAk (~7%) when compared to less closely regulated glycemia (~9% HbAlc). The less welcome observation is that a threefold increase in the risk of serious hypoglycemia occurs in those with intensive treatment. Serious hypoglycemia in IDDM subjects commonly occurs at night or without typical sympathoadrenal warning symptoms (hypoglycemia unawareness) that permit patients to rectify glucose levels by taking dextrose or other remedies. These observations have led Cryer (6) to assert that hypoglycemia is the limiting factor in control of IDDM, a judgment now widely accepted. The hypothesis that excess glucose or some factor closely allied with it is toxic is now much better defended than ever; the concern about hypoglycemia is, however, heightened.

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.

Pramlintide Reduces the Risks Associated with Glucose Variability in Type 1 Diabetes

BACKGROUNDnThis study was designed to determine whether pramlintide added to insulin therapy reduced the risks associated with extreme blood glucose (BG) fluctuations in patients with type 1 diabetes.nnnMETHODSnSelf-monitored BG (SMBG) records were retrospectively analyzed from a randomized, double-blind, placebo-controlled study of the effects of pramlintide on intensively treated patients with type 1 diabetes. Two groups--pramlintide (n=119), 30/60 microg administered subcutaneously at each meal, or placebo (n=129)--were matched by age, gender, and baseline hemoglobin A1C. Using SMBG, daily BG profiles, BG rate of change, and low and high BG indices (LBGI and HBGI, respectively) measuring the risk for hypoglycemia and hyperglycemia were calculated.nnnRESULTSnCompared with placebo, pramlintide significantly attenuated the pre- to postprandial BG rate of change (F=83.8, P<0.0001). Consequently, in pramlintide-treated patients, the average post-meal BG (8.4 vs. 9.7 mmol/L [151.2 vs. 174.6 mg/dL]) and postprandial HBGI were significantly lower than placebo (both P<0.0001). Substantial daily BG variation was observed in placebo-treated patients, with most significant hyperglycemia occurring after breakfast and during the night; post-meal BG did not vary significantly throughout the day in pramlintide-treated patients. The reduction in postprandial hyperglycemia in pramlintide-treated patients occurred without increased risk for preprandial hypoglycemia as quantified by the LBGI.nnnCONCLUSIONSnRisk analysis of the effect of pramlintide treatment demonstrated risk-reduction effects independent of changes in average glycemia, most notably reduced rate and magnitude of postprandial BG fluctuations. These effects were not accompanied by an increased risk of hypoglycemia.

PANCREATIC NETWORK CONTROL OF GLUCAGON SECRETION AND COUNTERREGULATION

Glucagon counterregulation (GCR) is a key protection against hypoglycemia compromised in insulinopenic diabetes by an unknown mechanism. In this work, we present an interdisciplinary approach to the analysis of the GCR control mechanisms. Our results indicate that a pancreatic network which unifies a few explicit interactions between the major islet peptides and blood glucose (BG) can replicate the normal GCR axis and explain its impairment in diabetes. A key and novel component of this network is an alpha-cell auto-feedback, which drives glucagon pulsatility and mediates triggering of pulsatile GCR by hypoglycemia via a switch-off of the beta-cell suppression of the alpha-cells. We have performed simulations based on our models of the endocrine pancreas which explain the in vivo GCR response to hypoglycemia of the normal pancreas and the enhancement of defective pulsatile GCR in beta-cell deficiency by switch-off of intrapancreatic alpha-cell suppressing signals. The models also predicted that reduced insulin secretion decreases and delays the GCR. In conclusion, based on experimental data we have developed and validated a model of the normal GCR control mechanisms and their dysregulation in insulin deficient diabetes. One advantage of this construct is that all model components are clinically measurable, thereby permitting its transfer, validation, and application to the study of the GCR abnormalities of the human endocrine pancreas in vivo.