Basu, Rita

Abstract Carbohydrate metabolism in humans is regulated by insulin secretion from pancreatic β‐cells and glucose disposal by insulin‐sensitive tissues. Insulin facilitates glucose utilization in peripheral tissues and suppresses hepatic glucose production. Any defects in insulin action predispose an individual to glucose intolerance and Type 2 diabetes mellitus. Early detection of defects in insulin action could provide opportunities to prevent or delay progression of the disease state. There are different approaches to assess insulin action. Initial methods, such as peripheral insulin concentration and simple indices, have several limitations. Subsequently, researchers developed methodologies using intravenous glucose infusion to determine glucose fluxes. However, these methodologies are limited by being non‐physiological. Newer, innovative techniques that have been developed are more sophisticated and physiological. By modelling glucose kinetics using isotope dilution techniques, several robust parameters can be obtained that are physiologically relevant and sound. This brief review summarizes most of the non‐physiological and physiological methodologies used to measure the variables of insulin action.

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.

The aim of this study was to determine the effect of prolonged 11β-hydroxysteroid dehydrogenase-1 (11β-HSD1) inhibition on basal and hormone-stimulated glucose metabolism in fasted conscious dogs. For 7 days prior to study, either an 11β-HSD1 inhibitor (HSD1-I; n = 6) or placebo (PBO; n = 6) was administered. After the basal period, a 4-h metabolic challenge followed, where glucagon (3×-basal), epinephrine (5×-basal), and insulin (2×-basal) concentrations were increased. Hepatic glucose fluxes did not differ between groups during the basal period. In response to the metabolic challenge, hepatic glucose production was stimulated in PBO, resulting in hyperglycemia such that exogenous glucose was required in HSD-I ( P < 0.05) to match the glycemia between groups. Net hepatic glucose output and endogenous glucose production were decreased by 11β-HSD1 inhibition ( P < 0.05) due to a reduction in net hepatic glycogenolysis ( P < 0.05), with no effect on gluconeogenic flux compared with PBO. In addition, glucose utilization ( P < 0.05) and the suppression of lipolysis were increased ( P < 0.05) in HSD-I compared with PBO. These data suggest that inhibition of 11β-HSD1 may be of therapeutic value in the treatment of diseases characterized by insulin resistance and excessive hepatic glucose production.

Plasma glucose 2H‐enrichment in positions 5 (2H5) and 2 (2H2) from deuterated water (2H2O) provides a measure of the gluconeogenic contribution to endogenous glucose production. Urinary glucuronide analysis can circumvent blood sampling but it is not known if glucuronide and glucose enrichments are equal. Thirteen subjects with impaired fasting glucose/impaired glucose tolerance and 11 subjects with normal fasting glucose and normal glucose tolerance ingested 2H2O to ∼0.5% body water and acetaminophen. Glucose and glucuronide 2H5 and 2H2 were measured by 2H NMR spectroscopy of monoacetone glucose. For normal fasting glucose/normal glucose tolerance, 2H5 was 0.23 ± 0.02% and 0.25 ± 0.02% for glucose and glucuronide, respectively, whereas 2H2 was 0.47 ± 0.01% and 0.49 ± 0.02%, respectively. For impaired fasting glucose/impaired glucose tolerance, 2H5 was 0.22 ± 0.01% and 0.26 ± 0.02% for glucose and glucuronide, respectively, whereas 2H2 was 0.46 ± 0.01% and 0.49 ± 0.02%, respectively. The gluconeogenic contribution to endogenous glucose production measured from glucose and glucuronide were identical for both normal fasting glucose/normal glucose tolerance (48 ± 4 vs. 51 ± 3%) and impaired fasting glucose/impaired glucose tolerance (48 ± 2 vs. 53 ± 3%). Magn Reson Med 70:315–319, 2013. © 2012 Wiley Periodicals, Inc.

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 present analysis tests the hypothesis that quantifiable disruption of the glucose-stimulated insulin-secretion dose-response pathway mediates impaired fasting glycemia (IFG) and type 2 diabetes mellitus (DM). To this end, adults with normal and impaired fasting glycemia (NFG, n = 30), IFG ( n = 32), and DM ( n = 14) were given a mixed meal containing 75 g glucose. C-peptide and glucose were measured over 4 h, 13 times in NFG and IFG and 16 times in DM (age range 50–57 yr, body mass index 28–32 kg/m2). Wavelet-based deconvolution analysis was used to estimate time-varying C-peptide secretion rates. Logistic dose-response functions were constructed analytically of the sensitivity, potency, and efficacy (in the pharmacological sense of slope, one-half maximal stimulation, and maximal effect) of glucose's stimulation of prehepatic insulin (C-peptide) secretion. A hysteresis changepoint time, demarcating unequal glucose potencies for onset and recovery pathways, was estimated simultaneously. According to this methodology, NFG subjects exhibited distinct onset and recovery potencies of glucose in stimulating C-peptide secretion (6.5 and 8.5 mM), thereby defining in vivo hysteresis (potency shift −2.0 mM). IFG patients manifested reduced glucose onset potency (8.6 mM), and diminished C-peptide hysteretic shift (−0.80 mM). DM patients had markedly decreased glucose potency (18.8 mM), reversal of C-peptide's hysteretic shift (+4.5 mM), and 30% lower C-peptide sensitivity to glucose stimulation. From these data, we conclude that a dynamic dose-response model of glucose-dependent control of C-peptide secretion can identify disruption of in vivo hysteresis in patients with IFG and DM. Pathway-defined analytic models of this kind may aid in the search for prediabetes biomarkers.

We hypothesized that individuals who have undergone gastric bypass have greater insulin sensitivity that obese subjects but less compared with lean. We measured free fatty acid (FFA) and glucose kinetics during a two-step, hyperinsulinemic euglycemic clamp in nondiabetic subjects who were 38 ± 5 mo post-gastric bypass surgery (GB; n = 15), in lean subjects (L; n = 15), and in obese subjects (O; n = 16). Fasting FFAa were not significantly different between the three study groups but during both doses of insulin were significantly higher in O than in either GB or L. The effective insulin concentration resulting in half-maximal suppression of FFA was similar in L and GB and significantly less in both groups compared with O. Glucose infusion rates during low-dose insulin were not significantly different in GB compared with either L or O. During high-dose insulin, glucose infusion rates were significantly greater in GB than in O but less than in L. Endogenous glucose production in GB was significantly lower than O only during low dose of insulin. We conclude that gastric bypass is associated with improvements in adipose tissue insulin sensitivity to levels similar to lean, healthy persons and also with improvements in the response of glucose metabolism to insulin. These changes may be due to preferential reduction in visceral fat and decreased FFA availability. However, some differences in insulin sensitivity in GB remain compared with L. Residual insulin resistance may be related to excess total body fat or abnormal lipolysis and requires further study.