Hyperglycemia suppresses Lactate Clearance during Exercise in Type 1 Diabetes.

CONTEXT: Circulating lactate concentration is an important determinant of exercise tolerance. OBJECTIVE: To determine the role of hyperglycemia on lactate metabolism during exercise in type 1 diabetes (T1D). DESIGN: Protocol involved compared T1D participants and participants without diabetes (ND) at euglycemia [5.5mM] or hyperglycemia [9.2mM] in random order in T1D and at euglycemia in ND. SETTING: Clinical Research Unit, University of Virginia, Charlottesville, VA. PARTICIPANTS: 7 T1D and 7 ND. INTERVENTION: [1-13C] lactate infusion, exercise at 65% VO2max, euglycemia and hyperglycemia visits. MAIN OUTCOME MEASURE: Lactate turnover before, during and after 60 min of exercise at 65% VO2max. RESULTS: A two-compartment model with loss only from the peripheral compartment described lactate kinetics. Volume of distribution of the accessible compartment was similar between T1D and ND (p=0.76) and concordant to plasma volume (∼40ml/kg). Circulating lactate concentrations were higher (p<0.001) in T1D participants during exercise at hyperglycemia than euglycemia. Exercise induced lactate appearance did not differ (p=0.13) between hyperglycemia and euglycemia. However, lactate clearance was lower (p=0.03) during hyperglycemia than euglycemia in T1D. There were no differences in any of the above parameters between T1D and ND during euglycemia. CONCLUSIONS: Hyperglycemia modulates lactate metabolism during exercise by lowering lactate clearance leading to higher circulating lactate concentrations in T1D. This novel observation implies that exercise during hyperglycemia can lead to higher circulating lactate concentrations thus increasing the likelihood of reaching the lactate threshold sooner in T1D, and has high translational relevance for both providers and recreationally active people with Type 1 diabetes.

A New Index of Insulin Sensitivity from Glucose Sensor and Insulin Pump Data: In Silico and In Vivo Validation in Youths with Type 1 Diabetes.

Background: Estimation of insulin sensitivity (SI) and its daily variation are key for optimizing insulin therapy in patients with type 1 diabetes (T1D). We recently developed a method for SI estimation from continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) data in adults with T1D (SISP) and validated it under restrained experimental conditions. Herein, we validate in vivo a new version of SISP performing well in daily life unrestrained conditions. Methods: The new SISP was tested in both simulated and real data. The simulated dataset consists of 100 virtual adults of the UVa/Padova T1D Simulator monitored during an open-loop experiment, whereas the real dataset consists of 10 youths with T1D monitored during a hybrid closed-loop meal study. In both datasets, participants underwent two consecutive meals (breakfast and lunch, at 7 and 11 am) with the same carbohydrate content (70 g). Plasma glucose and insulin were measured during each meal to estimate the oral glucose minimal model SI (SIMM). CGM and CSII data were used for SISP calculation, which was then validated against the gold standard SIMM. Results: SISP was estimated with good precision (median coefficient of variation <20%) in 100% of the real and 91% of the simulated meals. SISP and SIMM were highly correlated, both in the simulated and real datasets (R = 0.82 and R = 0.83, P < 0.001), and exhibited a similar intraday pattern. Conclusions: SISP is suitable for estimating SI in both closed- and open-loop settings, provided that the subject wears a CGM sensor and a subcutaneous insulin pump.

Impaired Diurnal Pattern of Meal Tolerance and Insulin Sensitivity in Type 2 Diabetes: Implications for Therapy.

To assess the diurnal patterns of postprandial glucose tolerance and insulin sensitivity, 19 subjects with type 2 diabetes (8 women; 60 ± 11 years; BMI 32 ± 5 kg/m2) and 19 anthropometrically matched subjects with no diabetes (ND; 11 women; 53 ± 12 years; BMI 29 ± 5 kg/m2) were studied during breakfast (B), lunch (L), and dinner (D) with identical mixed meals (75 g carbohydrates) on 3 consecutive days in a randomized Latin square design. Three stable isotopes of glucose were ustilized to estimate meal fluxes, and mathematical models were used in estimating indices of insulin action and ß-cell function. Postmeal glucose excursions were higher at D versus B and at D versus L in type 2 diabetes (P < 0.05), while in ND they were higher at D versus B (P = 0.025) and at L versus B (P = 0.04). The insulin area under the curve was highest at B compared with L and D in type 2 diabetes, while no differences were observed in ND. Disposition index (DI) was higher at B than at L (P < 0.01) and at D (P < 0.001) in ND subjects, whereas DI was low with unchanging pattern across B-L-D in individuals with type 2 diabetes. Furthermore, between-meal differences in ß-cell responsivity to glucose (F) and insulin sensitivity (SI) were concurrent with changes in the DI within groups. Fasting and postmeal glucose, insulin, and C-peptide concentrations, along with estimates of endogenous glucose production (EGP), Rd, SI, F, hepatic extraction of insulin, insulin secretion rate, extracted insulin, and DI, were altered in type 2 diabetes compared with ND (P < 0.011 for all). The data show a diurnal pattern of postprandial glucose tolerance in overweight otherwise glucose-tolerant ND individuals that differs from overweight individuals with type 2 diabetes. The results not only provide valuable insight into management strategies for better glycemic control in people with type 2 diabetes, but also improved understanding of daytime glucose metabolism in overweight individuals without impaired glucose tolerance or overt diabetes.

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.

BACKGROUND: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. METHODS: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. RESULTS: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. CONCLUSION: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

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

BACKGROUND: Glucagon 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. METHODS: Here, 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. RESULTS: The 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. CONCLUSIONS: The methods described in this study for simultaneous detection and quantitation of glucagon tracers have clinical utility for investigating glucagon kinetics in vivo in humans.

Accuracy of a Factory-Calibrated Continuous Glucose Monitor in Individuals With Diabetes on Hemodialysis.

OBJECTIVE: Continuous glucose monitoring (CGM) improves diabetes management, but its reliability in individuals on hemodialysis is poorly understood and potentially affected by interstitial and intravascular volume variations. RESEARCH DESIGN AND METHODS: We assessed the accuracy of a factory-calibrated CGM by using venous blood glucose measurements (vBGM) during hemodialysis sessions and self-monitoring blood glucose (SMBG) at home. RESULTS: Twenty participants completed the protocol. The mean absolute relative difference of the CGM was 13.8% and 14.4%, when calculated on SMBG (n = 684) and on vBGM (n = 624), and 98.7% and 100% of values in the Parkes error grid A/B zones, respectively. Throughout 181 days of CGM monitoring, the median time in range (70-180 mg/dL) was 38.5% (interquartile range 29.3-57.9), with 28.7% (7.8-40.6) of the time >250 mg/dL. CONCLUSIONS: The overall performance of a factory-calibrated CGM appears reasonably accurate and clinically relevant for use in practice by individuals on hemodialysis and health professionals to improve diabetes management.

Automated Insulin Delivery with SGLT2i Combination Therapy in Type 1 Diabetes.

Background: Use of sodium-glucose cotransporter 2 inhibitors (SGLT2i) as adjunct therapy to insulin in type 1 diabetes (T1D) has been previously studied. In this study, we present data from the first free-living trial combining low-dose SGLT2i with commercial automated insulin delivery (AID) or predictive low glucose suspend (PLGS) systems. Methods: In an 8-week, randomized, controlled crossover trial, adults with T1D received 5 mg/day empagliflozin (EMPA) or no drug (NOEMPA) as adjunct to insulin therapy. Participants were also randomized to sequential orders of AID (Control-IQ) and PLGS (Basal-IQ) systems for 4 and 2 weeks, respectively. The primary endpoint was percent time-in-range (TIR) 70-180 mg/dL during daytime (7:00-23:00 h) while on AID (NCT04201496). Findings: A total of 39 subjects were enrolled, 35 were randomized, 34 (EMPA; n = 18 and NOEMPA n = 16) were analyzed according to the intention-to-treat principle, and 32 (EMPA; n = 16 and NOEMPA n = 16) completed the trial. On AID, EMPA versus NOEMPA had higher daytime TIR 81% versus 71% with a mean estimated difference of +9.9% (confidence interval [95% CI] 0.6-19.1); p = 0.04. On PLGS, the EMPA versus NOEMPA daytime TIR was 80% versus 63%, mean estimated difference of +16.5% (95% CI 7.3-25.7); p < 0.001. One subject on SGLT2i and AID had one episode of diabetic ketoacidosis with nonfunctioning insulin pump infusion site occlusion contributory. Interpretation: In an 8-week outpatient study, addition of 5 mg daily empagliflozin to commercially available AID or PLGS systems significantly improved daytime glucose control in individuals with T1D, without increased hypoglycemia risk. However, the risk of ketosis and ketoacidosis remains. Therefore, future studies with SGLT2i will need modifications to closed-loop control algorithms to enhance safety.

Inhibition of 11ß-Hydroxysteroid dehydrogenase-1 with AZD4017 in patients with nonalcoholic steatohepatitis or nonalcoholic fatty liver disease: A randomized, double-blind, placebo-controlled, phase II study.

AIM: To evaluate whether short-term treatment with a selective 11ß-Hydroxysteroid dehydrogenase-1 (11ß-HSD1) inhibitor, AZD4017, would block hepatic cortisol production and thereby decrease hepatic fat in patients with nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH), with or without type 2 diabetes (T2D). MATERIALS AND METHODS: This was a randomized, double-blind, placebo-controlled, phase 2 study conducted at two sites. Key inclusion criteria were the presence of NAFLD or NASH on magnetic resonance imaging (MRI) or recent biopsy positive for NASH. Enrolled patients were randomly assigned (1:1) to AZD4017 or placebo for 12 weeks. Primary outcomes were between-group differences in mean change from baseline to week 12 in liver fat fraction (LFF) and conversion of 13 C cortisone to 13 C cortisol in the liver. RESULTS: A total of 93 patients were randomized; 85 patients completed treatment. The mean (standard deviation [SD]) change in LFF was -0.667 (5.246) and 0.139 (4.323) in the AZD4017 and placebo groups (P = 0.441). For patients with NASH and T2D, the mean (SD) change in LFF was significantly improved in the AZD4017 versus the placebo group (-1.087 [5.374] vs. 1.675 [3.318]; P = 0.033). Conversion of 13 C cortisone to 13 C cortisol was blocked in all patients in the AZD4017 group. There were no significant between-group differences (AZD4017 vs. placebo) in changes in fibrosis, weight, levels of liver enzymes or lipids, or insulin sensitivity. CONCLUSION: Although the study did not meet one of the primary outcomes, AZD4017 blocked the conversion of 13 C cortisone to 13 C cortisol in the liver in all patients who received the drug. In patients with NASH and T2D, AZD4017 improved liver steatosis versus placebo.

Continuous Ketone Monitoring Consensus Report 2021.

This article is the work product of the Continuous Ketone Monitoring Consensus Panel, which was organized by Diabetes Technology Society and met virtually on April 20, 2021. The panel consisted of 20 US-based experts in the use of diabetes technology, representing adult endocrinology, pediatric endocrinology, advanced practice nursing, diabetes care and education, clinical chemistry, and bioengineering. The panelists were from universities, hospitals, freestanding research institutes, government, and private practice. Panelists reviewed the medical literature pertaining to ten topics: (1) physiology of ketone production, (2) measurement of ketones, (3) performance of the first continuous ketone monitor (CKM) reported to be used in human trials, (4) demographics and epidemiology of diabetic ketoacidosis (DKA), (5) atypical hyperketonemia, (6) prevention of DKA, (7) non-DKA states of fasting ketonemia and ketonuria, (8) potential integration of CKMs with pumps and automated insulin delivery systems to prevent DKA, (9) clinical trials of CKMs, and (10) the future of CKMs. The panelists summarized the medical literature for each of the ten topics in this report. They also developed 30 conclusions (amounting to three conclusions for each topic) about CKMs and voted unanimously to adopt the 30 conclusions. This report is intended to support the development of safe and effective continuous ketone monitoring and to apply this technology in ways that will benefit people with diabetes.

Exercise effect on insulin-dependent and insulin-independent glucose utilization in healthy individuals and individuals with type 1 diabetes: a modeling study.

Exercise effects (EE) on whole body glucose rate of disappearance (Rd) occur through insulin-independent (IIRd) and insulin-dependent (IDRd) mechanisms. Quantifying these processes in vivo would allow a better understanding of the physiology of glucose regulation. This is of particular importance in individuals with type 1 diabetes (T1D) since such a knowledge may help to improve glucose management. However, such a model is still lacking. Here, we analyzed data from six T1D and six nondiabetic (ND) subjects undergoing a labeled glucose clamp study during, before, and after a 60-min exercise session at 65% V̇o2max on three randomized visits: euglycemia-low insulin, euglycemia-high insulin, and hyperglycemia-low insulin. We tested a set of models, all sharing a single-compartment description of glucose kinetics, but differing in how exercise is assumed to modulate glucose disposal. Model selection was based on parsimony criteria. The best model assumed an exercise-induced immediate effect on IIRd and a delayed effect on IDRd. It predicted that exercise increases IIRd, compared with rest, by 66%-82% and 67%-97% in T1D and ND, respectively, not significantly different between the two groups. Conversely, the exercise effect on IDRd ranged between 81% and 155% in T1D and it was significantly higher than ND, which ranged between 10% and 40%. The exaggerated effect observed in IDRd can explain the higher hypoglycemia risk related to individuals with T1D. This novel exercise model could help in informing safe and effective glucose management during and after exercise in individuals with T1D.NEW & NOTEWORTHY Here, we present a new mathematical model describing the effect of moderate physical activity on insulin-mediated and noninsulin-mediated glucose disposal in subjects with and without diabetes. We believe that this represents a step-forward in the knowledge of type 1 diabetes pathophysiology, and an useful tool to design safe and effective insulin-therapies.

Modeling the acute effects of exercise on glucose dynamics in healthy nondiabetic subjects.

To shed light on how acute exercise affects blood glucose (BG) concentrations in nondiabetic subjects, we develop a physiological pharmacokinetic/pharmacodynamic model of postprandial glucose dynamics during exercise. We unify several concepts of exercise physiology to derive a multiscale model that includes three important effects of exercise on glucose dynamics: increased endogenous glucose production (EGP), increased glucose uptake in skeletal muscle (SM), and increased glucose delivery to SM by capillary recruitment (i.e. an increase in surface area and blood flow in capillary beds). We compare simulations to experimental observations taken in two cohorts of healthy nondiabetic subjects (resting subjects (n = 12) and exercising subjects (n = 12)) who were each given a mixed-meal tolerance test. Metabolic tracers were used to quantify the glucose flux. Simulations reasonably agree with postprandial measurements of BG concentration and EGP during exercise. Exercise-induced capillary recruitment is predicted to increase glucose transport to SM by 100%, causing hypoglycemia. When recruitment is blunted, as in those with capillary dysfunction, the opposite occurs and higher than expected BG levels are predicted. Model simulations show how three important exercise-induced phenomena interact, impacting BG concentrations. This model describes nondiabetic subjects, but it is a first step to a model that describes glucose dynamics during exercise in those with type 1 diabetes (T1D). Clinicians and engineers can use the insights gained from the model simulations to better understand the connection between exercise and glucose dynamics and ultimately help patients with T1D make more informed insulin dosing decisions around exercise.

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline.

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.

Hyperglycemia But Not Hyperinsulinemia Is Favorable for Exercise in Type 1 Diabetes: A Pilot Study.

OBJECTIVE: To distinguish the effects of hyperglycemia and hyperinsulinemia on exercise-induced increases in Rd and endogenous glucose production (EGP) in type 1 diabetes. RESEARCH DESIGN AND METHODS: We studied six participants without diabetes and six participants with type 1 diabetes on three visits in random order for the following: euglycemia, low insulin (EuLoI); euglycemia, high insulin (EuHiI); and hyperglycemia, low insulin (HyLoI). Glucose fluxes were measured using [6,6-2H2] glucose before, during, and after 60 min of exercise. RESULTS: Rd increased (P < 0.01) with exercise within groups, while peak Rd during exercise was lower (P < 0.01) in participants with type 1 diabetes than participants without diabetes during all visits. In type 1 diabetes participants, EGP increased (P < 0.001) with exercise during EuLoI and HyLoI but not during EuHiI. This demonstrates that hyperinsulinemia, but not hyperglycemia, blunts the compensatory exercise-induced increase in EGP in type 1 diabetes. CONCLUSIONS: The data from this pilot study indicate that 1) exercise-induced compensatory increase in EGP was inhibited in participants with type 1 diabetes with hyperinsulinemia but not with hyperglycemia; 2) in contrast, in participants without diabetes, exercise-induced increase in EGP was inhibited only during combined hyperinsulinemia and hyperglycemia. Taken together, these results suggest that low insulin coupled with euglycemia or modest hyperglycemia appear to be the most favorable milieu for type 1 diabetes during exercise.

Novel Insights Into Effects of Cortisol and Glucagon on Nocturnal Glucose Production in Type 2 Diabetes.

CONTEXT: The effect of physiological changes in night-time cortisol and glucagon on endogenous glucose production (EGP) and nocturnal glycemia are unknown. OBJECTIVE: To determine the effects of changes in cortisol and glucagon on EGP during the night. DESIGN: Two overnight protocols were conducted. In Protocol 1, endogenous cortisol was blocked with metyrapone and hydrocortisone infused either at constant (constant) or increasing (variable) rates to mimic basal or physiological nocturnal cortisol concentrations. In Protocol 2, endogenous glucagon was blocked with somatostatin and exogenous glucagon was infused at either basal or elevated rates to mimic nocturnal glucagon concentrations observed in nondiabetic (ND) and type 2 diabetes (T2D) individuals. EGP was measured using [3-3H] glucose and gluconeogenesis estimated with 2H2O in all studies. SETTING: Mayo Clinic Clinical Research Trials Unit, Rochester, MN, US. PARTICIPANTS: In Protocol 1, 34 subjects (17 ND and 17 T2D) and in Protocol 2, 39 subjects (21 ND and 18 T2D) were studied. MAIN OUTCOME MEASURES: Endogenous glucose production. RESULTS: EGP, gluconeogenesis, and glycogenolysis were higher with variable than with constant cortisol at 7 am in T2D subjects. In contrast, nocturnal EGP did not differ in ND subjects between variable and constant cortisol. While elevated glucagon increased EGP, glycogenolysis, and gluconeogenesis in ND, the data in T2D subjects indicated that EGP and gluconeogenesis but not glycogenolysis were higher during the early part of the night. CONCLUSION: Nocturnal hyperglucagonemia, but not physiological rise in cortisol, contributes to nocturnal hyperglycemia in T2D due to increased gluconeogenesis.

A novel natural tracer method to measure complex carbohydrate metabolism.

While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and ß-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice (n = 8) or sorghum (n = 8) and glucose (n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 µM·kg-1·2 h-1), endogenous glucose production (-835 ± 283 vs. -1,123 ± 323 µM·kg-1·2 h-1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 µM·kg-1·2 h-1) differed (P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10-5 (dl·kg-1·min-2)/pM, P = 0.006) and ß-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10-14 (dl·kg-1·min-2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and ß-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults.

A novel measure of glucose homeostasis (or loss thereof) comprising the joint dynamics of glucose, insulin, glucagon, and cortisol.

Quantification of disturbances in glucose-insulin homeostasis has been the cornerstone of appraising insulin resistance and detecting early-stage diabetes. Metabolic homeostasis arises from feedback and feed-forward interactions among (at least) all four of glucose, insulin, glucagon, and cortisol. Quantifying such tetrapartite interactions in the fasting (endogenously regulated) state overnight could elucidate very early regulatory disruption. In the present study, healthy subjects without diabetes (ND; n = 20) and patients with Type 2 diabetes (T2D; n = 21) were investigated by repeated overnight blood sampling of all four of glucose, insulin, glucagon, and cortisol concentrations. To obviate confounding by hormone-specific disappearance rates, analyses were performed at the level of production (glucose) or secretion (insulin, glucagon, and cortisol) rates estimated by regularized deconvolution analysis. Then, a novel method for quantifying the loss of homeostasis among glucose, insulin, and glucagon (and, when available, cortisol) secretion patterns was developed. Potential early stage prediabetic candidates were identified. The new methodology avoids many of the difficulties encountered in the conventional estimation of insulin-glucose sensitivity or resistance, while incorporating the dynamics of the key coregulators under fasting conditions.

Modeling the acute effects of exercise on insulin kinetics in type 1 diabetes.

Our objective is to develop a physiology-based model of insulin kinetics to understand how exercise alters insulin concentrations in those with type 1 diabetes (T1D). We reveal the relationship between the insulin absorption rate ([Formula: see text]) from subcutaneous tissue, the insulin delivery rate ([Formula: see text]) to skeletal muscle, and two physiological parameters that characterize the tissue: the perfusion rate (Q) and the capillary permeability surface area (PS), both of which increase during exercise because of capillary recruitment. We compare model predictions to experimental observations from two pump-wearing T1D cohorts [resting subjects ([Formula: see text]) and exercising subjects ([Formula: see text])] who were each given a mixed-meal tolerance test and a bolus of insulin. Using independently measured values of Q and PS from literature, the model predicts that during exercise insulin concentration increases by 30% in plasma and by 60% in skeletal muscle. Predictions reasonably agree with experimental observations from the two cohorts, without the need for parameter estimation by curve fitting. The insulin kinetics model suggests that the increase in surface area associated with exercise-induced capillary recruitment significantly increases [Formula: see text] and [Formula: see text], which explains why insulin concentrations in plasma and skeletal muscle increase during exercise, ultimately enhancing insulin-dependent glucose uptake. Preventing hypoglycemia is of paramount importance in determining the proper insulin dose during exercise. The presented model provides mechanistic insight into how exercise affects insulin kinetics, which could be useful in guiding the design of decision support systems and artificial pancreas control algorithms.

Paradigm Shifts in Nocturnal Glucose Control in Type 2 Diabetes.

Context: A better understanding of nocturnal regulation of glucose homeostasis will provide the framework for designing rational therapeutic strategies to improve the management of overnight glucose in patients with type 2 diabetes (T2D). Objective: To establish the nocturnal pattern and regulation of glucose production (EGP) in humans and to determine whether the pattern is dysregulated in people with T2D. Design: Subjects were infused with [3-3H] glucose overnight. Arterial blood samples were drawn for hormones and analytes to estimate EGP throughout the night. Deuterium-labeled water was provided to measure gluconeogenesis (GNG) using the hexamethylenetetramine method of Landau. Setting: Mayo Clinic Clinical Research Trials Unit, Rochester, MN, USA. Participants and Interventions: A total of 43 subjects [23 subjects with T2D and 20 nondiabetic (ND) subjects comparable for age and body mass index] were included in this study. Main Outcome(s) Measure(s): Glucose and EGP. Results: Plasma glucose, C-peptide, and glucagon concentrations were higher throughout the night, whereas insulin concentrations were higher in subjects with T2D vs ND subjects at 1:00 and 4:00 am but similar at 7:00 am. EGP was higher in the subjects with T2D than in the ND subjects throughout the night (P < 0.001). Glycogenolysis (GGL) fell and GNG rose, resulting in significantly higher (P < 0.001) rates of GNG at 4:00 and 7:00 am and significantly (P < 0.001) higher rates of GGL at 1:00, 4:00, and 7:00 am in T2D as compared with ND. Conclusions: These data imply that optimal therapies for T2D for nocturnal/fasting glucose control should target not only the absolute rates of EGP but also the contributing pathways of GGL and GNG sequentially.

Greater early postprandial suppression of endogenous glucose production and higher initial glucose disappearance is achieved with fast-acting insulin aspart compared with insulin aspart.

AIM: To investigate the mechanisms behind the lower postprandial glucose (PPG) concentrations achieved with fast-acting insulin aspart (faster aspart) than with insulin aspart (IAsp). MATERIALS AND METHODS: In a randomized, double-blind, crossover trial, 41 people with type 1 diabetes received identical subcutaneous single faster aspart and IAsp doses (individualized for each participant), together with a standardized mixed meal (including 75 g carbohydrate labelled with [1-13 C] glucose). PPG turnover was determined by the triple-tracer meal method using continuous, variable [6-3 H] glucose and [6,6-2 H2 ] glucose infusion. RESULTS: Insulin exposure within the first hour was 32% greater with faster aspart than with IAsp (treatment ratio faster aspart/IAsp 1.32 [95% confidence interval {CI} 1.18;1.48]; P < .001), leading to a 0.59-mmol/L non-significantly smaller PPG increment at 1 hour (ΔPG1h ; treatment difference faster aspart-IAsp -0.59 mmol/L [95% CI -1.19; 0.01]; P = .055). The trend towards reduced ΔPG1h with faster aspart was attributable to 12% greater suppression of endogenous glucose production (EGP; treatment ratio 1.12 [95% CI 1.01; 1.25]; P = .040) and 23% higher glucose disappearance (1.23 [95% CI 1.05; 1.45]; P = .012) with faster aspart than with IAsp during the first hour. Suppression of free fatty acid levels during the first hour was 36% greater for faster aspart than for IAsp (1.36 [95% CI 1.01;1.88]; P = .042). CONCLUSIONS: The trend towards improved PPG control with faster aspart vs IAsp in this study was attributable to both greater early suppression of EGP and stimulation of glucose disappearance.