Incretin responses to oral glucose load in Japanese non-obese healthy subjects

Associations of fluctuations in blood glucose and insulin with hypoglycemic symptoms

Associations between fluctuations in blood glucose levels and medically unexplained symptoms, such as palpitations, numbness in the extremities, dizziness, and drowsiness, have been a topic of debate for an extended period; however, consensus remains elusive. We therefore examined the associations of blood glucose and insulin levels with symptoms by performing a 5 h glucose tolerance test in patients without diabetes with complaints. A total of 139 (54 men and 85 women, mean age 35.4 years) were included in this study. Blood glucose and insulin levels were measured before and at 15, 30, 60, 90, 120, 150, 180, 240, and 300 min after a 10-h fast and 75 g glucose load. The insulin index was used to divide the participants into early, intermediate, and delayed insulin secretion groups. Hypoglycemic symptoms (neuroglycopenic: warmth, drowsiness, weakness, fainting, decreased thinking ability, and dizziness) and autonomic symptoms (neurogenic: palpitations, cold sweats, anxiety/nervousness, tremors, hunger, and tingling) were evaluated separately. Hypoglycemia (< 70 mg/dL (3.9 mmol/L)) occurred at 240-300 min in 92% of all patients, with hypoglycemic and autonomic symptoms. Hypoglycemic symptoms increased over time and were highest at 240 min, while autonomic symptoms decreased significantly for 15 min and increased at 240 and 300 min. Although hypoglycemic symptoms were not significantly different among the early, intermediate, and delayed secretion groups, the incidence rates of autonomic symptoms were higher in the early insulin secretion group than in the other groups at 30-60-90 min. The characteristics of the early insulin secretion group suggested that symptoms were associated with not only blood glucose levels but also the timing of insulin secretion. Further studies are needed to determine whether dietary interventions tailored to insulin secretion profiles can alleviate these symptoms.

Four features of temporal patterns characterize similarity among individuals and molecules by glucose ingestion in humans

Oral glucose ingestion induces systemic changes of many blood metabolites related not only to glucose, but also other metabolites such as amino acids and lipids through many blood hormones. However, the detailed temporal changes in the concentrations of comprehensive metabolites and hormones over a long time by oral glucose ingestion are uncharacterized. We measured 83 metabolites and 7 hormones in 20 healthy human subjects in response to glucose ingestion. We characterized temporal patterns of blood molecules by four features: (i) the decomposability into “amplitude” and “rate” components, (ii) the similarity of temporal patterns among individuals, (iii) the relation of molecules over time among individuals, and (iv) the similarity of temporal patterns among molecules. Glucose and glucose metabolism-related hormones indicated a rapid increase, and citrulline and lipids, which indicated a rapid decrease, returned to fasting levels faster than amino acids. Compared to glucose metabolism-related molecules and lipids, amino acids showed similar temporal patterns among individuals. The four features of temporal patterns of blood molecules by oral glucose ingestion characterize the differences among individuals and among molecules.

Factors Related to Blood Intact Incretin Levels in Patients with Type 2 Diabetes Mellitus

BACKGROUND

We performed this study to identify factors related to intact incretin levels in patients with type 2 diabetes mellitus (T2DM).

METHODS

We cross-sectionally analyzed 336 patients with T2DM. Intact glucagon-like peptide 1 (iGLP-1) and intact glucose-dependent insulinotropic polypeptide (iGIP) levels were measured in a fasted state and 30 minutes after ingestion of a standard mixed meal. The differences between 30 and 0 minute iGLP-1 and iGIP levels were indicated as ΔiGLP-1 and ΔiGIP.

RESULTS

In simple correlation analyses, fasting iGLP-1 was positively correlated with glucose, C-peptide, creatinine, and triglyceride levels, and negatively correlated with estimated glomerular filtration rate. ΔiGLP-1 was positively correlated only with ΔC-peptide levels. Fasting iGIP showed positive correlations with glycosylated hemoglobin (HbA1c) and fasting glucose levels, and negative correlations with ΔC-peptide levels. ΔiGIP was negatively correlated with diabetes duration and HbA1c levels, and positively correlated with Δglucose and ΔC-peptide levels. In multivariate analyses adjusting for age, sex, and covariates, fasting iGLP-1 levels were significantly related to fasting glucose levels, ΔiGLP-1 levels were positively related to ΔC-peptide levels, fasting iGIP levels were related to fasting C-peptide levels, and ΔiGIP levels were positively related to ΔC-peptide and Δglucose levels.

CONCLUSION

Taken together, intact incretin levels are primarily related to C-peptide and glucose levels. This result suggests that glycemia and insulin secretion are the main factors associated with intact incretin levels in T2DM patients.

Mineralocorticoid Receptor May Regulate Glucose Homeostasis through the Induction of Interleukin-6 and Glucagon-Like peptide-1 in Pancreatic Islets

Because the renin-angiotensin-aldosterone system influences glucose homeostasis, the mineralocorticoid receptor (MR) signal in pancreatic islets may regulate insulin response upon glucose load. Glucagon-like peptide-1 (GLP-1) production is stimulated by interleukin-6 (IL-6) in pancreatic α-cells. To determine how glucose homeostasis is regulated by interactions of MR, IL-6 and GLP-1 in islets, we performed glucose tolerance and histological analysis of islets in primary aldosteronism (PA) model rodents and conducted in vitro experiments using α-cell lines. We measured active GLP-1 concentration in primary aldosteronism (PA) patients before and after the administration of MR antagonist eplerenone. In PA model rodents, aldosterone decreased insulin-secretion and the islet/pancreas area ratio and eplerenone added on aldosterone (E+A) restored those with induction of IL-6 in α-cells. In α-cells treated with E+A, IL-6 and GLP-1 concentrations were increased, and anti-apoptotic signals were enhanced. The E+A-treatment also significantly increased MR and IL-6 mRNA and these upregulations were blunted by MR silencing using small interfering RNA (siRNA). Transcriptional activation of the IL-6 gene promoter by E+A-treatment required an intact MR binding element in the promoter. Active GLP-1 concentration was significantly increased in PA patients after eplerenone treatment. MR signal in α-cells may stimulate IL-6 production and increase GLP-1 secretion, thus protecting pancreatic β-cells and improving glucose homeostasis.

Very short-term effects of the dipeptidyl peptidase-4 inhibitor sitagliptin on the secretion of insulin, glucagon, and incretin hormones in Japanese patients with type 2 diabetes mellitus: analysis of meal tolerance test data

Background

Sitagliptin inhibits dipeptidyl peptidase-4, which inactivates the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide. To assess its antidiabetic potency, we used meal tolerance tests (MTTs) to determine the very short-term effects of sitagliptin on plasma concentrations of insulin and glucagon.

Methods

On day 1, patients with newly diagnosed or uncontrolled type 2 diabetes mellitus started a calorie-restricted diet. On day 2, the first MTT was performed, before treatment with sitagliptin 50 mg/day started later the same day. On day 5, a second MTT was performed. Area under the concentration–time curves (AUCs) of relevant laboratory values were calculated [AUC from time zero to 2 h (AUC_0–2h) and from time zero to 4 h (AUC_0–4h)].

Results

Fifteen patients were enrolled. AUCs for postprandial plasma glucose were decreased after 3 days of sitagliptin treatment [AUC_0–2h 457 ± 115 mg/dL·h (25.4 ± 6.4 mmol/L·h) to 369 ± 108 mg/dL·h (20.5 ± 6.0 mmol/L·h); AUC_0–4h 896 ± 248 mg/dL·h (49.7 ± 13.8 mmol/L·h) to 701 ± 246 mg/dL·h (38.9 ± 13.7 mmol/L·h); both p < 0.001]. AUC_0–2h and AUC_0–4h for postprandial plasma glucagon also decreased: 195 ± 57 to 180 ± 57 pg/mL·h (p < 0.05) and 376 ± 105 to 349 ± 105 pg/mL·h (p < 0.01), respectively. The AUC_0–2h [median with quartile values (25 %, 75 %)] for active GLP-1 increased: 10.5 (8.5, 15.2) to 26.4 (16.7, 32.4) pmol/L·h (p = 0.03).

Conclusions

Very short-term (3-day) treatment with sitagliptin decreases postprandial plasma glucose significantly. This early reduction in glucose may result partly from suppression of excessive glucagon secretion, through a direct effect on active GLP-1. Improvement in postprandial plasma glucose, through suppression of glucagon secretion, is believed to be an advantage of sitagliptin for the treatment of patients with type 2 diabetes.

Effects of Miglitol, Acarbose, and Sitagliptin on Plasma Insulin and Gut Peptides in Type 2 Diabetes Mellitus: A Crossover Study

INTRODUCTION

Both dipeptidyl peptidase-4 inhibitors and α-glucosidase inhibitors (α-GI) have been reported to change the incretin and insulin secretion. To examine the effects of acarbose, miglitol, and sitagliptin on glucose metabolism and secretion of gut peptides, we conducted a crossover study in patients with type 2 diabetes mellitus (T2DM).

METHODS

Eleven Japanese patients with T2DM underwent four meal tolerance tests with single administration of acarbose, miglitol, sitagliptin, or nothing. Fasting and postprandial plasma levels of glucose, insulin, glucagon, active glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), ghrelin, and des-acyl ghrelin were measured.

RESULTS

Early-phase insulin secretion was reduced following acarbose and miglitol, and the areas under the curve (AUC) of insulin at 180 min following acarbose and miglitol were significantly lower than sitagliptin. AUC of plasma glucose at 180 min after acarbose, miglitol, and sitagliptin tended to be lower than in controls, and plasma glucose levels at 30-60 min following miglitol were significantly lower than in controls. Plasma glucagon, ghrelin, and des-acyl ghrelin levels did not differ among the four conditions. Postprandial plasma active GLP-1 levels and AUC of GLP-1 increased significantly in both the sitagliptin and miglitol groups compared to control. Postprandial plasma total GIP levels increased following sitagliptin but decreased after acarbose and miglitol. Changes in incretin levels tended to be greater with miglitol than acarbose.

CONCLUSION

These results showed that sitagliptin and α-GIs, miglitol more so than acarbose, improved hyperglycemia in patients with T2DM after single administration, and had different effects on insulin and incretin secretion.

TRIAL REGISTRATION

UMIN-CTR number, UMIN000009981.

A physiology-based model describing heterogeneity in glucose metabolism: the core of the Eindhoven Diabetes Education Simulator (E-DES)

Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control.