Cobelli, Claudio

We recently demonstrated a diurnal pattern to insulin action (i.e., insulin sensitivity [SI]) in healthy individuals with higher SI at breakfast than at dinner. To determine whether such a pattern exists in type 1 diabetes, we studied 19 subjects with C-peptide–negative diabetes (HbA1c 7.1 ± 0.6%) on insulin pump therapy with normal gastric emptying. Identical mixed meals were ingested during breakfast, lunch, and dinner at 0700, 1300, and 1900 h in randomized Latin square of order on 3 consecutive days when measured daily physical activity was equal. The triple tracer technique enabled measurement of glucose fluxes. Insulin was administered according to the customary insulin:carbohydrate ratio for each participant. Although postprandial glucose excursions did not differ among meals, insulin concentration was higher (P < 0.01) and endogenous glucose production less suppressed (P < 0.049) at breakfast than at lunch. There were no differences in meal glucose appearance or in glucose disappearance between meals. Although there was no statistical difference (P = 0.34) in SI between meals in type 1 diabetic subjects, the diurnal pattern of SI taken across the three meals in its entirety differed (P = 0.016) from that of healthy subjects. Although the pattern in healthy subjects showed decreasing SI between breakfast and lunch, the reverse SI pattern was observed in type 1 diabetic subjects. The results suggest that in contrast to healthy subjects, SI diurnal pattern in type 1 diabetes is specific to the individual and cannot be extrapolated to the type 1 diabetic population as a whole, implying that artificial pancreas algorithms may need to be personalized.

Recently, we proposed a model describing the suppression of endogenous glucose production (EGP) during a meal. It assumes that EGP suppression depends on glucose concentration and its rate of change and on delayed insulin action. Hepatic insulin sensitivity (SILmeal) can be derived from EGP model parameters. This model was shown to adequately describe EGP profiles measured with multiple tracer techniques; however, SILmealhas never been compared directly with its euglycemic hyperinsulinemic clamp counterpart (SILclamp). To do so, 62 subjects with different degrees of glucose tolerance underwent a triple-tracer mixed meal. Fifty-seven subjects also underwent a labeled ([3-3H]glucose) euglycemic hyperinsulinemic clamp. From the triple-tracer meal data, virtually model-independent estimates of EGP were obtained using the tracer-to-tracee clamp technique, and the EGP model was identified in each subject. Model fit was satisfactory, and SILmealwas estimated with good precision. Correlation between SILclampand SILmealwas good ( r = 0.72, P < 0.001); however, SILmealwas lower than SILclamp(4.60 ± 0.64 vs. 8.73 ± 1.07 10−4dl·kg−1·min−1per μU/ml, P < 0.01). This difference may be due to different ranges of insulin explored during the two tests (ΔIclamp= 15.60 ± 1.61 vs. ΔImeal= 83.37 ± 10.71 μU/ml) as well as steady- vs. non-steady-state glucose and insulin profiles. In conclusion, the new EGP model provides an estimate of hepatic insulin sensitivity during a meal that is in good agreement with that derived in the same individuals with a hyperinsulinemic clamp. When used in conjunction with the minimal model, the approach potentially enables estimation of hepatic insulin sensitivity from a single-tracer labeled meal or oral glucose tolerance test.

We designed an experiment to examine the effect of bile acid sequestration with Colesevelam on fasting and postprandial glucose metabolism in type 2 diabetes. To do so, we tested the hypothesis that Colesevelam increases the disposition index (DI), and this increase is associated with increased glucagon-like peptide-1 (GLP-1) concentrations. Thirty-eight subjects on metformin monotherapy were studied using a double-blind, placebo-controlled, parallel-group design. Subjects were studied before and after 12 weeks of Colesevelam or placebo using a labeled triple-tracer mixed meal to measure the rate of meal appearance (Meal Ra), endogenous glucose production (EGP), and glucose disappearance (Rd). Insulin sensitivity and β-cell responsivity indices were estimated using the oral minimal model and then used to calculate DI. Therapy with Colesevelam was associated with a decrease in fasting (7.0 ± 0.2 vs. 6.6 ± 0.2 mmol/L; P = 0.004) and postprandial glucose concentrations (3,145 ± 138 vs. 2,896 ± 127 mmol/6 h; P = 0.01) in the absence of a change in insulin concentrations. Minimal model–derived indices of insulin secretion and action were unchanged. Postprandial GLP-1 concentrations were not altered by Colesevelam. Although EGP and Rd were unchanged, integrated Meal Ra was decreased by Colesevelam (5,191 ± 204 vs. 5,817 ± 204 μmol/kg/6 h; P = 0.04), suggesting increased splanchnic sequestration of meal-derived glucose.

OBJECTIVE Physical activity (PA), even at low intensity, promotes health and improves hyperglycemia. However, the effect of low-intensity PA captured with accelerometery on glucose variability in healthy individuals and patients with type 1 diabetes has not been examined. Quantifying the effects of PA on glycemic variability would improve artificial endocrine pancreas (AEP) algorithms. RESEARCH DESIGN AND METHODS We studied 12 healthy control subjects (five males, 37.7 ± 13.7 years of age) and 12 patients with type 1 diabetes (five males, 37.4 ± 14.2 years of age) for 88 h. Participants performed PA approximating a threefold increase over their basal metabolic rate. PA was captured using a PA-monitoring system, and interstitial fluid glucose concentrations were captured with continuous glucose monitors. In random order, one meal per day was followed by inactivity, and the other meals were followed by walking. Glucose and PA data for a total of 216 meals were analyzed from 30 min prior to meal ingestion to 270 min postmeal. RESULTS In healthy subjects, the incremental glucose area under the curve was 4.5 mmol/L/270 min for meals followed by walking, whereas it was 9.6 mmol/L/270 min (P = 0.022) for meals followed by inactivity. The corresponding glucose excursions for those with type 1 diabetes were 7.5 mmol/L/270 min and 18.4 mmol/L/270 min, respectively (P &lt; 0.001). CONCLUSIONS Walking significantly impacts postprandial glucose excursions in healthy populations and in those with type 1 diabetes. AEP algorithms incorporating PA may enhance tight glycemic control end points.

The mechanisms by which common genetic variation predisposes to type 2 diabetes remain unclear. The disease-associated variants in TCF7L2 (rs7903146) and WFS1 (rs10010131) have been shown to affect response to exogenous glucagon-like peptide 1 (GLP-1), while variants in KCNQ1 (rs151290, rs2237892, and rs2237895) alter endogenous GLP-1 secretion. We set out to validate these observations using a model of GLP-1–induced insulin secretion. We studied healthy individuals using a hyperglycemic clamp and GLP-1 infusion. In addition, we measured active and total GLP-1 in response to an oral challenge in nondiabetic subjects. After genotyping the relevant single nucleotide polymorphisms, generalized linear regression models and repeated-measures ANCOVA models incorporating potential confounders, such as age and BMI, were used to assess the associations, if any, of response with genotype. These variants did not alter GLP-1 concentrations in response to oral intake. No effects on β-cell responsiveness to hyperglycemia and GLP-1 infusion were apparent. Diabetes-associated variation (T allele at rs7903146) in TCF7L2 may impair the ability of hyperglycemia to suppress glucagon (45 ± 2 vs. 47 ± 2 vs. 60 ± 5 ng/L for CC, CT, and TT, respectively, P = 0.02). In nondiabetic subjects, diabetes-associated genetic variation does not alter GLP-1 concentrations after an oral challenge or its effect on insulin secretion.

OBJECTIVE Glucagon-like peptide (GLP)-1 receptor is encoded by GLP1R. The effect of genetic variation at this locus on the response to GLP-1 is unknown. This study assessed the effect of GLP1R polymorphisms on insulin secretion in response to hyperglycemia and to infused GLP-1 in nondiabetic subjects. RESEARCH DESIGN AND METHODS Eighty-eight healthy individuals (aged 26.3 ± 0.6 years, fasting glucose 4.83 ± 0.04 mmol/l) were studied using a hyperglycemic clamp. GLP-1 was infused for the last 2 h of the study (0.75 pmol/kg/min over 121–180 min, 1.5 pmol/kg/min over 181–240 min). β-Cell responsivity (ΦTotal) was measured using a C-peptide minimal model. The effect of 21 tag single nucleotide polymorphisms (SNPs) in GLP1R on ΦTotal was examined. RESULTS Two SNPs (rs6923761 and rs3765467) were nominally associated with altered β-cell responsivity in response to GLP-1 infusion. CONCLUSIONS Variation in GLP1R may alter insulin secretion in response to exogenous GLP-1. Future studies will determine whether such variation accounts for interindividual differences in response to GLP-1–based therapy.

Glucagon-like peptide-1 (GLP-1)-based therapies for diabetes have aroused interest because of their effects on insulin secretion and glycemic control. However, a mechanistic model enabling quantitation of pancreatic response to GLP-1 has never been developed. To develop such a model we studied 88 healthy individuals (age 26.3 ± 0.6 yr, BMI 24.9 ± 0.4 kg/m 2 ) by use of a hyperglycemic clamp. A variable infusion maintained glucose concentrations at 150 mg/dl for 240 min. At 120 min, an intravenous infusion of GLP-1 was started (0.75 pmol·kg −1 ·min −1 from 120–180 min, 1.5 pmol·kg −1 ·min −1 from 181–240 min). Consequently, plasma C-peptide concentration rose from 1,852.0 ± 62.8 pmol/l at 120 min to 4,272.2 ± 176.4 pmol/l at 180 min and to 6,995.8 ± 323.5 pmol/l at 240 min. Four models of GLP-1 action on insulin secretion were considered. All models share the common assumption that insulin secretion is made up of two components, one proportional to glucose rate of change through dynamic responsivity, Φ d , and one proportional to glucose through static responsivity, Φ s , but differing by modality of GLP-1 control. The model that best fit C-peptide data assumes that above-basal insulin secretion depends linearly on GLP-1 concentration and its rate of change. An index (Π) measuring the percentage increase of secretion due to GLP-1 is derived. Before GLP-1 infusion, Φ d = 245.7 ± 15.6 10 −9 and Φ s = 25.2 ± 1.4 10 −9 min −1 . Under GLP-1 stimulus, Π = 12.6 ± 0.71% per pmol/l, meaning that an increase of 5 pmol/l in peripheral GLP-1 concentrations induces an ∼60% increase in over-basal insulin secretion.

In this article, a first aim was to develop a minimal modeling approach to noninvasively assess hepatic insulin extraction in 204 healthy subjects studied with a standard meal by coupling the already available meal C-peptide minimal model with a new insulin model. The ingredients of this model are posthepatic IDR, which in turn is described in terms of pancreatic ISR and hepatic insulin extraction HE, and a linear monocompartmental model of insulin kinetics. Even if ISR is provided by the C-peptide minimal model, the simultaneous assessment of HE and insulin kinetics is critical, since compensations may arise between parameters describing these two processes. Therefore, as a second aim of this study, a method was developed to predict standard values of insulin kinetic parameters in an individual on the basis of the individual's anthropometric characteristics. The statistical analysis, based on linear regression of insulin kinetic parameters estimated from IM-IVGTT data performed on the same subjects, demonstrated that insulin kinetic parameters can be accurately predicted from age and body surface area. Once kinetic parameters of the new insulin model were fixed to these values, HE profile and indexes during a meal were reliably estimated in each individual, indicating a significant suppression during the meal since the overall index of HE, equal to 60 ± 1% in the basal state, is reduced to 40 ± 1% during a meal. However, standard parameters provide an approximation of the individual one; thus, the third aim was to define the impact on estimated indexes of using standard instead of individually estimated values. Our results showed that the 25% uncertainty affecting as an average insulin kinetic parameters of an individual, when they are predicted from age and body surface area, translates into a similar relative uncertainty in the individual's hepatic insulin extraction indexes.

OBJECTIVE In this study, we sought to determine whether postprandial insulin secretion, insulin action, glucose effectiveness, and glucose turnover were abnormal in type 2 diabetes. RESEARCH DESIGN AND METHODS Fourteen subjects with type 2 diabetes and 11 nondiabetic subjects matched for age, weight, and BMI underwent a mixed-meal test using the triple-tracer technique. Indexes of insulin secretion, insulin action, and glucose effectiveness were assessed using the oral “minimal” and C-peptide models. RESULTS Fasting and postprandial glucose concentrations were higher in the diabetic than nondiabetic subjects. Although peak insulin secretion was delayed (P &lt; 0.001) and lower (P &lt; 0.05) in type 2 diabetes, the integrated total postprandial insulin response did not differ between groups. Insulin action, insulin secretion, disposition indexes, and glucose effectiveness all were lower (P &lt; 0.05) in diabetic than in nondiabetic subjects. Whereas the rate of meal glucose appearance did not differ between groups, the percent suppression of endogenous glucose production (EGP) was slightly delayed and the increment in glucose disappearance was substantially lower (P &lt; 0.01) in diabetic subjects during the first 3 h after meal ingestion. Together, these defects resulted in an excessive rise in postprandial glucose concentrations in the diabetic subjects. CONCLUSIONS When measured using methods that avoid non–steady-state error, the rate of appearance of ingested glucose was normal and suppression of EGP was only minimally impaired. However, when considered in light of the prevailing glucose concentration, both were abnormal. In contrast, rates of postprandial glucose disappearance were substantially decreased due to defects in insulin secretion, insulin action, and glucose effectiveness.

OBJECTIVE—The purpose of this study was to determine the mechanism by which dipeptidyl peptidase-4 inhibitors lower postprandial glucose concentrations. RESEARCH DESIGN AND METHODS—We measured insulin secretion and action as well as glucose effectiveness in 14 subjects with type 2 diabetes who received vildagliptin (50 mg b.i.d.) or placebo for 10 days in random order separated by a 3-week washout. On day 9 of each period, subjects ate a mixed meal. Insulin sensitivity (SI), glucose effectiveness, and β-cell responsivity indexes were estimated using the oral glucose and C-peptide minimal models. At 300 min 0.02 unit/kg insulin was administered intravenously. RESULTS—Vildagliptin reduced postprandial glucose concentrations (905 ± 94 vs. 1,008 ± 104 mmol/6 h, P = 0.02). Vildagliptin did not alter net SI (7.71 ± 1.28 vs. 6.41 ± 0.84 10−4 dl · kg−1 · min−1 · μU−1 · ml−1, P = 0.13) or glucose effectiveness (0.019 ± 0.002 vs. 0.018 ± 0.002 dl · kg−1 · min−1, P = 0.65). However, the net β-cell responsivity index was increased (35.7 ± 5.2 vs. 28.9 ± 5.2 10−9 min−1, P = 0.03) as was total disposition index (381 ± 48 vs. 261 ± 35 10−14 dl · kg−1 · min−2 · pmol−1 · l−1, P = 0.006). Vildagliptin lowered postprandial glucagon concentrations (27.0 ± 1.1 vs. 29.7 ± 1.5 μg · l−1 · 6 h−1, P = 0.03), especially after administration of exogenous insulin (81.5 ± 6.4 vs. 99.3 ± 5.6 ng/l, P = 0.02). CONCLUSIONS—Vildagliptin lowers postprandial glucose concentrations by stimulating insulin secretion and suppressing glucagon secretion but not by altered insulin action or glucose effectiveness. A novel observation is that vildagliptin alters α-cell responsiveness to insulin administration, but the significance of this action is as yet unclear.