Glucagon Kinetics Research Articles

Glucagon kinetics assessed by mathematical modelling during oral glucose administration in people spanning from normal glucose tolerance to type 2 diabetes.

Glucagon is important in the maintenance of glucose homeostasis, with also effects on lipids. In this study, we aimed to apply a recently developed model of glucagon kinetics to determine the sensitivity of glucagon variations (especially, glucagon inhibition) to insulin levels ("alpha-cell insulin sensitivity"), during oral glucose administration. We studied 50 participants (spanning from normal glucose tolerance to type 2 diabetes) undergoing frequently sampled 5-hr oral glucose tolerance test (OGTT). The alpha-cell insulin sensitivity and the glucagon kinetics were assessed by a mathematical model that we developed previously. The alpha-cell insulin sensitivity parameter (named SGLUCA; "GLUCA": "glucagon") was remarkably variable among participants (CV=221%). SGLUCA was found inversely correlated with the mean glycemic values, as well as with 2-hr glycemia of the OGTT. When stratifying participants into two groups (normal glucose tolerance, NGT, N=28, and impaired glucose regulation/type 2 diabetes, IGR_T2D, N=22), we found that SGLUCA was lower in the latter (1.50 ± 0.50·10-2 vs. 0.26 ± 0.14·10-2 ng·L-1 GLUCA/pmol·L-1 INS, in NGT and IGR_T2D, respectively, p=0.009; "INS": "insulin"). The alpha-cell insulin sensitivity is highly variable among subjects, and it is different in groups at different glucose tolerance. This may be relevant for defining personalized treatment schemes, in terms of dietary prescriptions but also for treatments with glucagon-related agents.

A Quantitative Systems Pharmacology Model of the Incretin Hormones GIP and GLP1, Glucagon, Glucose, Insulin, and the Small Molecule DPP-4 Inhibitor, Linagliptin

In the current study, we established a comprehensive quantitative systems pharmacology (QSP) model using linagliptin as the model drug, where drug disposition, drug intervention on dipeptidyl peptidase-4 (DPP-4), glucose-dependent insulinotropic peptide (GIP), Glucagon-like peptide-1 (GLP-1), glucagon, glucose, and insulin are integrated together with the cross talk and feedback loops incorporated among the whole glycemic control system. In the final linagliptin QSP model, the complicated disposition of linagliptin was characterized by a 2-compartment pharmacokinetic (PK) model with an enterohepatic cycling (EHC) component as well as target-mediated drug disposition (TMDD) processes occurring in both tissues and plasma, and the inhibitory effect of linagliptin on DPP-4 was determined by the linagliptin-DPP-4 complex in the central compartment based on target occupancy principle. The integrated GIP-GLP1-glucagon-glucose-insulin system contains five indirect response models as the “skeleton” structure with 12 feedback loops incorporated within the glucose control system. Our model adequately characterized the substantial nonlinear PK of linagliptin, time course of DPP-4 inhibition, as well as the kinetics of GIP, GLP-1, glucagon, and glucose simultaneously in humans. Our model provided valuable insights on linagliptin pharmacokinetics/pharmacodynamics and complicated glucose homeostasis. Since the glucose regulation modeling framework within the QSP model is “drug-independent”, our model can be easily adopted by others to evaluate the effect of other DPP-4 inhibitors on the glucose control system. In addition, our QSP model, which contains more components than other reported glucose regulation models, can potentially be used to evaluate the effect of combination antidiabetic therapy targeting different components of glucose control system.

Nonlinear Mixed Effects Modeling of Glucagon Kinetics in Healthy Subjects.

To date, the lack of a model of glucagon kinetics precluded the possibility of estimating and studying glucagon secretion in vivo, e.g., using deconvolution, as done for other hormones like insulin and C-peptide. Here, we used a nonlinear mixed effects technique to develop a robust population model of glucagon kinetics, able to describe both the typical population kinetics (TPK) and the between-subject variability (BSV), and relate this last to easily measurable subject characteristics. Thirty-four models of increasing complexity (variably including covariates and correlations among random effects) were identified on glucagon profiles obtained from 53 healthy subjects, who received a constant infusion of somatostatin to suppress endogenous glucagon production, followed by a continuous infusion of glucagon (65 ng/kg/min). Model selection was performed based on its ability to fit the data, provide precise parameter estimates, and parsimony criteria. A two-compartment model was the most parsimonious. The model was able to accurately describe both the TPK and the BSV of model parameters as function of body mass and body surface area. Parameters were precisely estimated, with central volume of distribution V1 = 5.46 L and peripheral volume of distribution V2 = 5.51 L. The introduction of covariates resulted in a significant shrinkage of the unexplained BSV and considerably improved the model fit. We developed a robust population model of glucagon kinetics. This model provides a deeper understanding of glucagon kinetics and is usable to estimate glucagon secretion in vivo by deconvolution of plasma glucagon concentration data.

13C15N: glucagon-based novel isotope dilution mass spectrometry method for measurement of glucagon metabolism in humans

BackgroundGlucagon serves as an important regulatory hormone for regulating blood glucose concentration with tight feedback control exerted by insulin and glucose. There are critical gaps in our understanding of glucagon kinetics, pancreatic α cell function and intra-islet feedback network that are disrupted in type 1 diabetes. This is important for translational research applications of evolving dual-hormone (insulin + glucagon) closed-loop artificial pancreas algorithms and their usage in type 1 diabetes. Thus, it is important to accurately measure glucagon kinetics in vivo and to develop robust models of glucose-insulin-glucagon interplay that could inform next generation of artificial pancreas algorithms.MethodsHere, we describe the administration of novel 13C15N heavy isotope-containing glucagon tracers—FF glucagon [(Phe 6 13C9,15N; Phe 22 13C9,15N)] and FFLA glucagon [(Phe 6 13C9,15N; Phe 22 13C9,15N; Leu 14 13C6,15N; Ala 19 13C3)] followed by anti-glucagon antibody-based enrichment and LC–MS/MS based-targeted assays using high-resolution mass spectrometry to determine levels of infused glucagon in plasma samples. The optimized assay results were applied for measurement of glucagon turnover in subjects with and without type 1 diabetes infused with isotopically labeled glucagon tracers.ResultsThe limit of quantitation was found to be 1.56 pg/ml using stable isotope-labeled glucagon as an internal standard. Intra and inter-assay variability was < 6% and < 16%, respectively, for FF glucagon while it was < 5% and < 23%, respectively, for FFLA glucagon. Further, we carried out a novel isotope dilution technique using glucagon tracers for studying glucagon kinetics in type 1 diabetes.ConclusionsThe methods described in this study for simultaneous detection and quantitation of glucagon tracers have clinical utility for investigating glucagon kinetics in vivo in humans.

Glucagon Clearance is Preserved in Type 2 Diabetes.

Hyperglucagonemia is a common observation in both obesity and type 2 diabetes, and the etiology is primarily thought to be hypersecretion of glucagon. We investigated whether altered elimination kinetics of glucagon could contribute to the hyperglucagonemia in type 2 diabetes and obesity. Individuals with type 2 diabetes and preserved kidney function (8 with and 8 without obesity) and matched control individuals (8 with and 8 without obesity) were recruited. Each participant underwent a 1-hour glucagon infusion (4 ng/kg/min), achieving steady-state plasma glucagon concentrations, followed by a 1-hour wash-out period. Plasma levels, the metabolic clearance rate (MCR), half-life (T½) and volume of distribution of glucagon were evaluated and a pharmacokinetic model was constructed. Glucagon MCR and volume of distribution were significantly higher in the type 2 diabetes group compared to the control group, while no significant differences between the groups were found in glucagon T½ Individuals with obesity had neither a significantly decreased MCR, T½, nor volume of distribution of glucagon. In our pharmacokinetic model, glucagon MCR associated positively with fasting plasma glucose and negatively with body weight. In conclusion, our results suggest that impaired glucagon clearance is not a fundamental part of the hyperglucagonemia observed in obesity and type 2 diabetes.

264-OR: Glucagon Kinetics: Model from First-in-Humans with 13C15N Glucagon

We recently developed a novel stable glucagon tracer, [13C15N]-glucagon, to study glucagon kinetics and turnover in humans. Here, [13C15N]-glucagon was used to model glucagon kinetics during steady-state conditions in 5 nondiabetic subjects with complete data thus far (age 27±7 y; BMI 25.3±2.4 kg/m2, Mean±SD) who underwent two separate protocols: bolus injection (1497±564 pg/kg) and stop-from-constant infusion (138±33 pg/kg/min) of [13C15N]-glucagon. Arterialized blood was frequently sampled to measure the decay of [13C15N]-glucagon concentrations using tandem mass spectrometry. A linear, single compartment model was necessary and sufficient to reliably describe [13C15N]-glucagon kinetics and estimate both glucagon volume of distribution and clearance rate. The model well predicted the data (Fig. 1) and model parameters were estimated with precision (CV = 6±3 %). Volume of glucagon distribution was 37±9 mL/kg while clearance rate was 8.1±1.5 mL/kg/min. Results suggest that glucagon distributes in a single compartment with a volume of distribution approximately equal to the plasma volume. Additional nondiabetic and subjects with type 1 diabetes are currently under study. This model will be key to study postprandial glucagon turnover. Disclosure M. Schiavon: None. F. Ruchi: None. Y. R. Yadav: None. R. Basu: None. C. Cobelli: None. C. Dalla man: Research Support; Self; Becton, Dickinson and Company, Sanofi-Aventis Deutschland GmbH. A. Basu: None. Funding National Institutes of Health (DK085516 to A.B.), (DK029953 to R.B.); Italian Ministry of Education, University and Research (Law 232/2016 to M.S. and C.D.M.)

Mathematical Model of Glucagon Kinetics for the Assessment of Insulin-Mediated Glucagon Inhibition During an Oral Glucose Tolerance Test.

Glucagon is secreted from the pancreatic alpha cells and plays an important role in the maintenance of glucose homeostasis, by interacting with insulin. The plasma glucose levels determine whether glucagon secretion or insulin secretion is activated or inhibited. Despite its relevance, some aspects of glucagon secretion and kinetics remain unclear. To gain insight into this, we aimed to develop a mathematical model of the glucagon kinetics during an oral glucose tolerance test, which is sufficiently simple to be used in the clinical practice. The proposed model included two first-order differential equations -one describing glucagon and the other describing C-peptide in a compartment remote from plasma - and yielded a parameter of possible clinical relevance (i.e., SGLUCA(t), glucagon-inhibition sensitivity to glucose-induced insulin secretion). Model was validated on mean glucagon data derived from the scientific literature, yielding values for SGLUCA(t) ranging from -15.03 to 2.75 (ng of glucagon·nmol of C-peptide-1). A further validation on a total of 100 virtual subjects provided reliable results (mean residuals between -1.5 and 1.5 ng·L-1) and a negative significant linear correlation (r = -0.74, p < 0.0001, 95% CI: -0.82 – -0.64) between SGLUCA(t) and the ratio between the areas under the curve of suprabasal remote C-peptide and glucagon. Model reliability was also proven by the ability to capture different patterns in glucagon kinetics. In conclusion, the proposed model reliably reproduces glucagon kinetics and is characterized by sufficient simplicity to be possibly used in the clinical practice, for the estimation in the single individual of some glucagon-related parameters.

Assessment of individual and standardized glucagon kinetics in healthy humans.

Impaired glucose tolerance arises out of impaired postprandial insulin secretion and delayed suppression of glucagon. These defects occur early and independently in the pathogenesis of prediabetes. Quantification of the contribution of α-cell dysfunction to glucose tolerance has been lacking because knowledge of glucagon kinetics in humans is limited. Therefore, in a series of experiments examining the interaction of glucagon suppression with insulin secretion we studied 51 nondiabetic subjects (age = 54 ± 13 yr, BMI = 28 ± 4 kg/m2). Glucose was infused to mimic the systemic appearance of an oral challenge. Somatostatin was used to inhibit endogenous hormone secretion. 120 min after the start of the experiment, glucagon was infused at 0.65 ng/kg/min. The rise in glucagon concentrations was used to estimate its kinetic parameters [volume of distribution (Vd), half-life (t1/2), and clearance rate (CL)]. A single-exponential model provided the best fit for the data, and individualized kinetic parameters were estimated: Vd = 8.2 ± 2.7 L, t1/2 = 4 ± 1.1 min, CL = 1.4 ± 0.33 L/min. Stepwise linear regression was used to correlate Vd with BMI and sex (R2adj = 0.44), whereas CL similarly correlated with lean body mass or BSA (both R2 = 0.28). This enabled the development of a population-based model using anthropometric characteristics to predict Vd and CL. These data demonstrate that it is feasible to derive glucagon kinetic parameters from anthropometric characteristics, thereby enabling quantitation of the rate of glucagon appearance in the systemic circulation in large populations.NEW & NOTEWORTHY State-of-the-art measurement of insulin secretion in humans is accomplished by deconvolution of peripheral C-peptide concentrations using population-derived parameters of C-peptide kinetics. In contrast, knowledge of the kinetic parameters of glucagon in humans is lacking so that measurement of glucagon secretion to date is largely qualitative. This series of experiments enabled measurement of glucagon kinetics in 51 subjects, and subsequently, stepwise linear regression was used to correlate these parameters with anthropometric characteristics. This enabled the development of a population-based model using anthropometric characteristics to predict the volume of distribution and the rate of clearance. This is a necessary first step in the development of a model to quantitate of glucagon secretion and action (and its contribution to glucose tolerance) in large populations.

Insulin Action in the Hypothalamus Increases Second-Phase Insulin Secretion in Humans

Background: Animal studies and initial correlative data in humans indicate that insulin action in the brain may affect pancreatic insulin secretion. An important brain region for this process is the hypothalamus, an area that can develop insulin resistance. Methods: Fifteen young, healthy men (27 ± 3 years) with a wide BMI spectrum (20–30 kg/m²) underwent 2 hyperglycemic clamps (target blood glucose: 10 mmol/L). In this double-blind study, subjects received 160 U of insulin or placebo as a nasal spray on 2 days in randomized order. On another day, insulin sensitivity of the hypothalamus was determined by functional magnetic resonance imaging. Results: Glucose levels were comparable on both study days. In the whole group, C-peptide levels were not significantly different between conditions. Though, there was a significant interaction between insulin sensitivity of the hypothalamus × nasal spray × time on C-peptide levels (p = 10^–6). The group was therefore divided according to median hypothalamic insulin sensitivity. C-peptide concentrations were higher after intranasal insulin compared to placebo spray in the group with a strong hypothalamic insulin response (p < 0.0001, β = 6.00 ± 1.24) and lower in the brain insulin-resistant group (p = 0.005, β = –2.68 ± 0.95). Neither somatostatin nor glucagon kinetics was altered by the nasal spray. Conclusions: In participants with high hypothalamic insulin sensitivity, insulin action in the brain enhanced second-phase insulin secretion from pancreatic beta cells. This reaction could, for example, contribute to late postprandial glucose regulation by suppressing hepatic glucose production by portal venous insulin.

A statistical virtual patient population for the glucoregulatory system in type 1 diabetes with integrated exercise model.

PurposeWe introduce two validated single (SH) and dual hormone (DH) mathematical models that represent an in-silico virtual patient population (VPP) for type 1 diabetes (T1D). The VPP can be used to evaluate automated insulin and glucagon delivery algorithms, so-called artificial pancreas (AP) algorithms that are currently being used to help people with T1D better manage their glucose levels. We present validation results comparing these virtual patients with true clinical patients undergoing AP control and demonstrate that the virtual patients behave similarly to people with T1D.MethodsA single hormone virtual patient population (SH-VPP) was created that is comprised of eight differential equations that describe insulin kinetics, insulin dynamics and carbohydrate absorption. The parameters in this model that represent insulin sensitivity were statistically sampled from a normal distribution to create a population of virtual patients with different levels of insulin sensitivity. A dual hormone virtual patient population (DH-VPP) extended this SH-VPP by incorporating additional equations to represent glucagon kinetics and glucagon dynamics. The DH-VPP is comprised of thirteen differential equations and a parameter representing glucagon sensitivity, which was statistically sampled from a normal distribution to create virtual patients with different levels of glucagon sensitivity. We evaluated the SH-VPP and DH-VPP on a clinical data set of 20 people with T1D who participated in a 3.5-day outpatient AP study. Twenty virtual patients were matched with the 20 clinical patients by total daily insulin requirements and body weight. The identical meals given during the AP study were given to the virtual patients and the identical AP control algorithm that was used to control the glucose of the virtual patients was used on the clinical patients. We compared percent time in target range (70–180 mg/dL), time in hypoglycemia (<70 mg/dL) and time in hyperglycemia (>180 mg/dL) for both the virtual patients and the actual patients.ResultsThe subjects in the SH-VPP performed similarly vs. the actual patients (time in range: 78.1 ± 5.1% vs. 74.3 ± 8.1%, p = 0.11; time in hypoglycemia: 3.4 ± 1.3% vs. 2.8 ± 1.7%, p = 0.23). The subjects in the DH-VPP also performed similarly vs. the actual patients (time in range: 75.6 ± 5.5% vs. 71.9 ± 10.9%, p = 0.13; time in hypoglycemia: 0.9 ± 0.8% vs. 1.3 ± 1%, p = 0.19). While the VPPs tended to over-estimate the time in range relative to actual patients, the difference was not statistically significant.ConclusionsWe have verified that a SH-VPP and a DH-VPP performed comparably with actual patients undergoing AP control using an identical control algorithm. The SH-VPP and DH-VPP may be used as a simulator for pre-evaluation of T1D control algorithms.

1836-P: Derivation of Glucagon Kinetics to Reconstruct Glucagon Secretion in Nondiabetic Humans

Impaired glucose tolerance arises out delayed and decreased postprandial insulin secretion together with impaired postprandial suppression of glucagon. Recent studies have demonstrated that β-cell and α-cell dysfunction can occur independently in prediabetes. The effect of diabetes-associated variation in TCF7L2 on α-cell function also suggests a direct role in the pathogenesis of type 2 diabetes (T2DM). Quantification of the relative contribution of α-cell and β-cell function to glucose tolerance has been lacking because of a dearth of information regarding glucagon kinetics in humans. This information is necessary to deconvolute glucagon secretion from peripheral glucose concentrations. Therefore, as part of a series of experiments examining the interaction between a lack of glucagon suppression with intact, mildly or moderately impaired insulin secretion we studied 22 nondiabetic subjects (age = 46 ± 3 years, BMI = 29 ± 1 Kg/M2). An intravenous glucose infusion mimicking the systemic appearance of 50g oral glucose was administered in the presence of a pancreatic clamp over 300 minutes. Glucagon was infused at a rate of 0.65ng/kg/min, starting 120 minutes after initiation of the experiment (and suppression of endogenous glucagon secretion by somatostatin). The observed glucagon appearance rates were used to calculate the kinetic parameters of glucagon. Volume of distribution (Vd) was estimated at 14 ± 2 Litres or 0.16 ± 0.02 L/Kg body weight. Half-life was estimated at 6.1 ± 0.5 minutes with a clearance rate (CL) of 1.6 ± 0.1 L/min. Body surface area and height predicted Vd and CL. The individual parameters were then used to calculate glucagon secretion rates from peripheral glucagon concentrations for each participant. Fasting glucagon secretion rates (101 ± 11 ng/min) decreased (p &amp;lt; 0.01) in the presence of somatostatin (57 ± 5 ng/min). These data demonstrate the application of deconvolution to the quantification of glucagon secretion and its contribution to glucose tolerance. Disclosure M.C. Laurenti: Employee; Self; GlySens Incorporated. C. Dalla Man: None. J. Adams: None. A.M. Egan: None. C. Cobelli: None. A. Vella: Advisory Panel; Self; vTv Therapeutics. Research Support; Self; Novo Nordisk Inc. Funding National Institutes of Health

Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments.

Type-1 diabetes (T1D) treatment requires exogenous insulin administrations finely tuned based on glucose monitoring to avoid hyper/hypoglycemia. The safety and effectiveness of insulin treatments is commonly assessed in clinical trials, which are time demanding and expensive. These limitations can be overtaken by in silico clinical trials (ISCT) that require realistic patient and treatment models. The aim is to develop a T1D patient decision simulator usable to perform reliable ISCT. The T1D patient decision simulator was developed by connecting the UVA/Padova T1D model, which describes glucose, insulin, and glucagon kinetics, with modules describing glucose monitoring devices, like self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM), the patient's behavior in making treatment decisions, and insulin administration. The reliability of the simulator was assessed by comparing its predictions with data collected in 44 T1D subjects using the Dexcom G5 Mobile CGM sensor as an adjunct to the Bayer Contour Next USB SMBG device. Metrics like time spent in eu/hypo/hyperglycemia of simulated data well match those observed in subjects. In particular, mean time in euglycemia, mean time in hyperglycemia, and median time in hypoglycemia are 61.75% versus 63.60% (p-value = 0.4825), 33.38% versus 33.40% (p -value = 0.9950), and 3.17% versus 2.14% (p-value = 0.1134), respectively, in real versus simulated data. The proposed simulator can be used to perform credible ISCT in realistic insulin treatment scenarios. The T1D patient decision simulator can be used to reliably assess novel insulin treatments, e.g., based on use of CGM only, in a realistic multiple-day scenario.

Changes in Levels of Biomarkers Associated with Adipocyte Function and Insulin and Glucagon Kinetics During Treatment with Dapagliflozin Among Obese Type 2 Diabetes Mellitus Patients.

ObjectivesThis study aimed to investigate changes in levels of biomarkers associated with adipocyte function and insulin and glucagon kinetics after a meal tolerance test (MTT) during treatment with dapagliflozin among obese type 2 diabetes mellitus (T2DM) patients.MethodsT2DM patients with hemoglobin A1c (HbA1c) levels >6.5 % and body mass index (BMI) >25 kg/m2 were treated with dapagliflozin 5 mg/day for at least 12 weeks. HbA1c, body weight, ketone bodies, adiponectin, plasminogen activator inhibitor-1 (PAI-1), and C-reactive protein (CRP) were measured before and after treatment with dapagliflozin. A subset of patients underwent an MTT.ResultsOf 27 participating patients (mean age 47.9 years; 17 males), five were drug-naive and 22 were treated with other antidiabetic agents, including insulin and glucagon-like peptide-1 (GLP-1) receptor agonists. Following treatment with dapagliflozin, HbA1c levels significantly improved (7.44 ± 0.56 to 6.70 ± 0.0.57 %; p < 0.01), body weight significantly decreased (90.9 ± 16.5 to 87.1 ± 15.9 kg; p < 0.01), ketone bodies increased, adiponectin significantly increased, and high-sensitivity CRP tended to decrease. During the MTT, blood glucose ΔAUC2 significantly decreased, glucagon ΔAUC2 increased, and immunoreactive insulin (IRI) did not change in 11 of 27 patients.ConclusionAlthough ketone bodies increased significantly, adiponectin increased and high-sensivity CRP decreased significantly. These findings suggest that sodium-glucose cotransporter-2 (SGLT2) inhibitors may potentially improve adipocyte function in treating obese T2DM patients.

Postprandial lipemia induces pancreatic α cell dysfunction characteristic of type 2 diabetes: studies in healthy subjects, mouse pancreatic islets, and cultured pancreatic α cells

Type 2 diabetes is associated with pancreatic α cell dysfunction, characterized by elevated fasting plasma glucagon concentrations and inadequate postprandial glucose- and insulin-induced suppression of glucagon secretion. The cause and the underlying mechanisms of α cell dysfunction are unknown. Because Western dietary habits cause postprandial lipemia for a major part of a day and, moreover, increase the risk of developing type 2 diabetes, we tested the hypothesis that postprandial lipemia with its characteristic elevation of triglyceride-rich lipoproteins (TGRLs) might cause pancreatic α cell dysfunction. In a crossover study with 7 healthy volunteers, 2 experiments using 2 fat-enriched meals were performed on each volunteer; meal 1 was designed to increase plasma concentrations of both TGRLs and nonesterified fatty acids and meal 2 to increase TGRLs only. Intravenous glucose boli were injected at 0800 after an overnight fast and postprandially at 1300, 3 h after ingestion of a fat-enriched meal. Glucagon concentrations were measured throughout the days of the experiments. In addition to the study in humans, in vitro experiments were performed with mouse pancreatic islets and cultured pancreatic alpha TC 1 clone 9 (αTC1c9) cells, which were incubated with highly purified TGRLs. In humans, postprandial lipemia increased plasma glucagon concentrations and led to an inadequate glucose- and insulin-induced suppression of glucagon. There was no difference between the 2 meal types. In mouse pancreatic islets and cultured pancreatic αTC1c9 cells, purified postprandial TGRLs induced abnormalities in glucagon kinetics comparable with those observed in humans. The TGRL-induced α cell dysfunction was due to reduced γ-aminobutyric acid A receptor activation in pancreatic α cells. We concluded that postprandial lipemia induces pancreatic α cell dysfunction characteristic of type 2 diabetes and, therefore, propose that pancreatic α cell dysfunction could be viewed, at least partly, as a postprandial phenomenon.

The UVA/PADOVA Type 1 Diabetes Simulator: New Features.

Recent studies have provided new insights into nonlinearities of insulin action in the hypoglycemic range and into glucagon kinetics as it relates to response to hypoglycemia. Based on these data, we developed a new version of the UVA/PADOVA Type 1 Diabetes Simulator, which was submitted to FDA in 2013 (S2013). The model of glucose kinetics in hypoglycemia has been improved, implementing the notion that insulin-dependent utilization increases nonlinearly when glucose decreases below a certain threshold. In addition, glucagon kinetics and secretion and action models have been incorporated into the simulator: glucagon kinetics is a single compartment; glucagon secretion is controlled by plasma insulin, plasma glucose below a certain threshold, and glucose rate of change; and plasma glucagon stimulates with some delay endogenous glucose production. A refined statistical strategy for virtual patient generation has been adopted as well. Finally, new rules for determining insulin to carbs ratio (CR) and correction factor (CF) of the virtual patients have been implemented to better comply with clinical definitions. S2013 shows a better performance in describing hypoglycemic events. In addition, the new virtual subjects span well the real type 1 diabetes mellitus population as demonstrated by good agreement between real and simulated distribution of patient-specific parameters, such as CR and CF. S2013 provides a more reliable framework for in silico trials, for testing glucose sensors and insulin augmented pump prediction methods, and for closed-loop single/dual hormone controller design, testing, and validation.

Glucagon clearance is regulated by nutritional state: evidence from experimental studies in mice

Given the importance of glucagon in the development of type 2 diabetes and as a potential therapeutic agent, the aim of this study was to characterise glucagon kinetics in mice and its regulation by the nutritional state. Anaesthetised C57BL/6 mice fed normal or high-fat diets, or fasted, were injected intravenously with glucagon (0.1, 0.3, 1.0, 10.0 or 20 μg/kg); blood samples were withdrawn before injection and 1, 3, 5, 10, 20 min thereafter for glucagon assay by RIA. Glucagon kinetics were described by two-compartment models using a population analysis. The population mean and between-animal SD of glucagon clearance in the fed mice was 6.03 ± 2.58 ml/min, with a rapid elimination half-life of 2.92 ± 1.21 min. Fasted mice showed a slower glucagon clearance. The kinetics of glucagon in the fed and fasted group was linear across this large dose range. The mice fed a high-fat diet, however, showed non-linear kinetics with a faster terminal clearance of 20.4 ± 5.45 ml/min (p < 0.001) and a shorter elimination half-life of 1.59 ± 0.606 (p < 0.001) min relative to normal mice. This first systematic dose-ranging study of glucagon kinetics produced several findings: (1) a linear two-compartment model describes glucagon in normal C57BL/6 mice; (2) fasting reduces the clearance of glucagon and (3) high-fat diet enhances the clearance of glucagon. These results may direct future studies on glucagon physiology and indicate that there are other mechanisms, not included in the current model, needed to fully explain glucagon's kinetics.

Glucose Generates Coincident Insulin and Somatostatin Pulses and Antisynchronous Glucagon Pulses from Human Pancreatic Islets

The kinetics of insulin, glucagon and somatostatin release was studied in human pancreatic islets. Batches of 10-15 islets were perifused and the hormones measured with RIA in 30-sec fractions. Increase of glucose from 3 to 20 mm resulted in a brief pulse of glucagon coinciding with suppression of basal insulin and somatostatin release. There was a subsequent drop of glucagon release concomitant with the appearance of a pronounced pulse of insulin and a slightly delayed pulse of somatostatin. Continued exposure to 20 mm glucose generated pulsatile release of the three hormones with 7- to 8-min periods accounting for 60-70% of the secreted amounts. Glucose caused pronounced stimulation of average insulin and somatostatin release. However, the nadirs between the glucagon pulses were lower than the secretion at 3 mm glucose, resulting in 18% suppression of average release. The repetitive glucagon pulses were antisynchronous to coincident pulses of insulin and somatostatin. The resulting greater than 20-fold variations of the insulin to glucagon ratio might be essential for minute-to-minute regulation of the hepatic glucose production.

Changes in glucagon kinetics and processing in patients with acute pancreatitis

The kinetics of the pancreatic hormone glucagon in patients with acute pancreatitis have not been investigated as carefully as those of insulin, in spite of its crucial influence on energy metabolism. In the present study, we studied the kinetics of glucagon and glucagon-related peptides assessed by radioimmunoassay. Furthermore, the molecular forms of these peptides were examined using gel filtration chromatography, and the glucagon processes in the pancreas and intestine in the early stage in patients with acute pancreatitis were investigated. Fourteen patients with acute pancreatitis were enrolled in this study. Eight had severe pancreatitis (group S) and six had mild pancreatitis (group M). Ten healthy volunteers were also enrolled as the normal control (group C). Serum levels of glucagon and glucagon-related peptides were assessed on the second admission day in groups S and M, and in an early morning fasting state in group C, using glucagon non-specific N-terminal (glucagon-like immunoreactivity: GLI) and specific C-terminal (immunoreactive glucagon: IRG) radioimmunoassays. The molecular forms of these peptides were also estimated using gel filtration chromatography. We then discuss the glucagon processes based on these findings. Serum GLI and IRG in groups S and M were significantly higher than those of group C (P < 0.01), while those in group S were also significantly higher than those in group M (P < 0.05). In all patients in groups S and M, except for only three in group S, a peculiar glicentin-like peptide (GLLP: MW about 8000) other than pancreatic glucagon was observed in IRG gel filtration chromatography, which was clearly absent from group C. The kinetics and processing of glucagon in patients with acute pancreatitis were quite different from those of healthy subjects. In patients with acute pancreatitis, the peculiar processing of glucagon proceeded in the intestine quite differently from ordinary glucagon processing either in the pancreas or in the intestine, generating a peculiar GLLP.

Varying the protein source in mixed meal modifies glucose, insulin and glucagon kinetics in healthy men, has weak effects on subjective satiety and fails to affect food intake.

To evaluate the influence of three dietary protein types (casein, gelatin, soy protein) on satiety and food intake, at two levels of loading (total energy of test meals: 3.6 or 1.8 MJ). The study employed a repeated measures design. Test meals were controlled for energy, macronutrients, fiber and palatability, and contained about 23% energy as protein (of which about 65% was experimentally manipulated). Postprandial subjective satiety and hunger, plasma glucose, insulin and glucagon were assessed for 8 h, and energy and macronutrient intakes were monitored for 24 h. Nine healthy normal-weight men. No effect of the type of protein on 24 h energy and macronutrient intakes was observed despite a significant effect of protein source on the kinetics of peripheral metabolic responses (but only after 3.6 MJ lunches), and inconsistent effects on subjective hunger and satiety responses A casein-enriched lunch delayed glucose and insulin responses for 1.5 h, compared with soy protein, probably due to a lag in gastric emptying. Varying the protein source in a mixed meal modifies glucose, insulin and glucagon kinetics in healthy men, but these variations in satiety-implicated factors have inconsistent effects on subjective satiety and fail to affect food intake. Eridania Béghin-Say, Vilvoorde, Belgium and Association Nationale de la Recherche Technique, France (Convention CIFRE no 537/94).

Splanchnic glucagon kinetics in exercising alloxan-diabetic dogs.

The purpose of this study was to define the relationship between arterial immunoreactive glucagon (IRG) and IRG that perfuses the liver via the portal vein during exercise in the diabetic state. Dogs underwent surgery >16 days before the experiment, at which time flow probes were implanted in the portal vein and the hepatic artery, and Silastic catheters were inserted in the carotid artery, portal vein, and hepatic vein for sampling. Dogs were made diabetic with alloxan injected intravenously approximately 3 wk before study (AD) or were studied in the nondiabetic state (ND). Each study consisted of a 30-min basal period and a 150-min moderate-exercise period on a treadmill. The findings from these studies indicate that the exercise-induced increment in portal vein IRG can be substantially greater in AD compared with ND, even when arterial and hepatic vein increments are not different. The larger IRG gradient from the portal vein to the systemic circulation in AD dogs is a function of a twofold greater increase in nonhepatic splanchnic IRG release and a fivefold greater hepatic fractional IRG extraction during exercise. In conclusion, during exercise, arterial IRG concentrations greatly underestimate the IRG levels to which the liver is exposed in ND, and this underestimation is considerably greater in dogs with poorly controlled diabetes.