OBJECTIVE

Recent work has shown that insulin stimulates its own secretion in insulin-sensitive humans, suggesting that insulin resistance in the β-cell could cause β-cell dysfunction. We have tested whether insulin exposure and insulin sensitivity modulate β-cell function in subjects with normal glucose tolerance (NGT) and whether they contribute to dysglycemia in impaired glucose regulation (IGR).

RESEARCH DESIGN AND METHODS

Insulin sensitivity (by euglycemic clamp), insulin-induced secretory response at isoglycemia (IISR) (as C-peptide percent change from basal during the clamp), glucose-induced secretory response (GISR) to an intravenous glucose bolus, and β-cell glucose sensitivity (β-GS) (by oral glucose tolerance test [OGTT] modeling) were measured in 1,151 NGT and 163 IGR subjects from the RISC (Relationship between Insulin Sensitivity and Cardiovascular Disease) study.

RESULTS

In NGT, IISR was related to both insulin sensitivity and antecedent insulin exposure; GISR was related to insulin exposure. IISR was positively, if weakly, related to β-GS (r= 0.16, P < 0.0001). Both IISR (−23 [39] vs. −9 [2]%, median [interquartile range], P < 0.03) and β-GS (69 [47] vs. 118 [83] pmol ⋅ min–1 ⋅ m–2 ⋅ mmol–1 ⋅ L, P < 0.0001) were decreased in IGR compared with NGT. Insulin sensitivity and β-GS were the major determinants of mean OGTT glucose in both NGT and IGR, with a minor role for IISR. In a multivariate logistic model, IGR was predicted by β-GS (odds ratio 4.84 [95% CI 2.89–8.09]) and insulin sensitivity (3.06 [2.19–4.27]) but not by IISR (1.11 [0.77–1.61]).

CONCLUSIONS

Pre-exposure to physiological hyperinsulinemia stimulates insulin secretion to a degree that depends on insulin sensitivity. However, this phenomenon has limited impact on β-cell dysfunction and dysglycemia.

OBJECTIVE

In mice, 4F, an apolipoprotein A-I mimetic peptide that restores HDL function, prevents diabetes-induced atherosclerosis. We sought to determine whether HDL function is impaired in type 2 diabetic (T2D) patients and whether 4F treatment improves HDL function in T2D patient plasma in vitro.

RESEARCH DESIGN AND METHODS

HDL anti-inflammatory function was determined in 93 T2D patients and 31 control subjects as the ability of test HDLs to inhibit LDL-induced monocyte chemotactic activity in human aortic endothelial cell monolayers. The HDL antioxidant properties were measured using a cell-free assay that uses dichlorofluorescein diacetate. Oxidized fatty acids in HDLs were measured by liquid chromatography–tandem mass spectrometry. In subgroups of patients and control subjects, the HDL inflammatory index was repeated after incubation with L-4F.

RESULTS

The HDL inflammatory index was 1.42 ± 0.29 in T2D patients and 0.70 ± 0.19 in control subjects (P < 0.001). The cell-free assay was impaired in T2D patients compared with control subjects (2.03 ± 1.35 vs. 1.60 ± 0.80, P < 0.05), and also HDL intrinsic oxidation (cell-free assay without LDL) was higher in T2D patients (1,708 ± 739 vs. 1,233 ± 601 relative fluorescence units, P < 0.001). All measured oxidized fatty acids were significantly higher in the HDLs of T2D patients. There was a significant correlation between the cell-free assay values and the content of oxidized fatty acids in HDL fractions. L-4F treatment restored the HDL inflammatory index in diabetic plasma samples (from 1.26 ± 0.17 to 0.71 ± 0.11, P < 0.001) and marginally affected it in healthy subjects (from 0.81 ± 0.16 to 0.66 ± 0.10, P < 0.05).

CONCLUSIONS

In patients with T2D, the content of oxidized fatty acids is increased and the anti-inflammatory and antioxidant activities of HDLs are impaired.

OBJECTIVE

Previous studies have found that high insulin sensitivity predicts weight gain; this association has not been confirmed. Our aim was to systematically analyze metabolic predictors of spontaneous weight changes.

RESEARCH DESIGN AND METHODS

In 561 women and 467 men from the Relationship Between Insulin Sensitivity and Cardiovascular Disease (RISC) cohort (mean age 44 years, BMI range 19–44 kg/m2, 9% impaired glucose tolerance) followed up for 3 years, we measured insulin sensitivity (by a euglycemic clamp) and β-cell function (by modeling of the C-peptide response to oral glucose and by acute insulin response to intravenous glucose).

RESULTS

Insulin sensitivity was similar in weight gainers (top 20% of the distribution of BMI changes), weight losers (bottom 20%), and weight stable subjects across quartiles of baseline BMI. By multiple logistic or linear regression analyses controlling for center, age, sex, and baseline BMI, neither insulin sensitivity nor any β-cell function parameter showed an independent association with weight gain; this was true in normal glucose tolerance, impaired glucose tolerance, and whether subjects progressed to dysglycemia or not. Baseline BMI was significantly higher in gainers (26.1 ± 4.1 kg/m2) and losers (26.6 ± 3.7 kg/m2) than in weight stable subjects (24.8 ± 3.8 kg/m2, P < 0.0001 for both gainers and losers). Baseline waist circumference (or equivalently, BMI or weight) was a positive, independent predictor of both weight gain and weight loss (odds ratio 1.48 [95% CI 1.12–1.97]) in men and (1.67 [1.28–2.12]) in women. In men only, better insulin sensitivity was an additional independent predictor of weight loss.

CONCLUSIONS

Neither insulin sensitivity nor insulin secretion predicts spontaneous weight gain. Individuals who have attained a higher weight are prone to either gaining or losing weight regardless of their glucose tolerance.

OBJECTIVE

This report examines what is known about the relationship between obesity and type 2 diabetes and how future research in these areas might be directed to benefit prevention, interventions, and overall patient care.

RESEARCH DESIGN AND METHODS

An international working group of 32 experts in the pathophysiology, genetics, clinical trials, and clinical care of obesity and/or type 2 diabetes participated in a conference held on 6–7 January 2011 and cosponsored by The Endocrine Society, the American Diabetes Association, and the European Association for the Study of Diabetes. A writing group comprising eight participants subsequently prepared this summary and recommendations. Participants reviewed and discussed published literature and their own unpublished data.

RESULTS

The writing group unanimously supported the summary and recommendations as representing the working group's majority or unanimous opinions.

CONCLUSIONS

The major questions linking obesity to type 2 diabetes that need to be addressed by combined basic, clinical, and population-based scientific approaches include the following: 1) Why do not all patients with obesity develop type 2 diabetes? 2) Through what mechanisms do obesity and insulin resistance contribute to β-cell decompensation, and if/when obesity prevention ensues, how much reduction in type 2 diabetes incidence will follow? 3) How does the duration of type 2 diabetes relate to the benefits of weight reduction by lifestyle, weight-loss drugs, and/or bariatric surgery on β-cell function and glycemia? 4) What is necessary for regulatory approval of medications and possibly surgical approaches for preventing type 2 diabetes in patients with obesity? Improved understanding of how obesity relates to type 2 diabetes may help advance effective and cost-effective interventions for both conditions, including more tailored therapy. To expedite this process, we recommend further investigation into the pathogenesis of these coexistent conditions and innovative approaches to their pharmacological and surgical management.

OBJECTIVE

Dapagliflozin, a highly selective inhibitor of the renal sodium-glucose cotransporter-2, increases urinary excretion of glucose and lowers plasma glucose levels in an insulin-independent manner. We evaluated the efficacy and safety of dapagliflozin in treatment-naive patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

This was a 24-week parallel-group, double-blind, placebo-controlled phase 3 trial. Patients with A1C 7.0–10% (n = 485) were randomly assigned to one of seven arms to receive once-daily placebo or 2.5, 5, or 10 mg dapagliflozin once daily in the morning (main cohort) or evening (exploratory cohort). Patients with A1C 10.1–12% (high-A1C exploratory cohort; n = 73) were randomly assigned 1:1 to receive blinded treatment with a morning dose of 5 or 10 mg/day dapagliflozin. The primary end point was change from baseline in A1C in the main cohort, statistically tested using an ANCOVA.

RESULTS

In the main cohort, mean A1C changes from baseline at week 24 were −0.23% with placebo and −0.58, −0.77 (P = 0.0005 vs. placebo), and −0.89% (P < 0.0001 vs. placebo) with 2.5, 5, and 10 mg dapagliflozin, respectively. Signs, symptoms, and other reports suggestive of urinary tract infections and genital infection were more frequently noted in the dapagliflozin arms. There were no major episodes of hypoglycemia. Data from exploratory cohorts were consistent with these results.

CONCLUSIONS

Dapagliflozin lowered hyperglycemia in treatment-naive patients with newly diagnosed type 2 diabetes. The near absence of hypoglycemia and an insulin-independent mechanism of action make dapagliflozin a unique addition to existing treatment options for type 2 diabetes.

OBJECTIVE

Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action.

RESEARCH DESIGN AND METHODS

We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084).

RESULTS

The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 × 10−71). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction.

CONCLUSIONS

Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.

OBJECTIVE

To determine if the dipeptidyl peptidase-4 inhibitor vildagliptin more effectively inhibits glucagon levels than the sulfonylurea glimepiride during a meal.

RESEARCH DESIGN AND METHODS

Glucagon responses to a standard meal were measured at baseline and study end point (mean 1.8 years) in a trial evaluating add-on therapy to metformin with 50 mg vildagliptin b.i.d. compared with glimepiride up to 6 mg q.d. in type 2 diabetes (baseline A1C 7.3 ± 0.6%).

RESULTS

A1C and prandial glucose area under the curve (AUC)0–2 h were reduced similarly in both groups, whereas prandial insulin AUC0–2 h increased to a greater extent by glimepiride. Prandial glucagon AUC0–2 h (baseline 66.6 ± 2.3 pmol · h−1 · l−1) decreased by 3.4 ± 1.6 pmol · h−1 · l−1 by vildagliptin (n = 137) and increased by 3.8 ± 1.7 pmol · h−1 · l−1 by glimepiride (n = 121). The between-group difference was 7.3 ± 2.1 pmol · h−1 · l−1 (P < 0.001).

CONCLUSIONS

Vildagliptin therapy but not glimepiride improves postprandial α-cell function, which persists for at least 2 years.

OBJECTIVE

Relatives of type 1 diabetic patients are at enhanced risk of developing diabetes. We investigated the mode of onset of hyperglycemia and how insulin sensitivity and β-cell function contribute to the progression to the disease.

RESEARCH DESIGN AND METHODS

In 328 islet cell autoantibody–positive, nondiabetic relatives from the observational arms of the Diabetes Prevention Trial-1 Study (median age 11 years [interquartile range 8], sequential OGTTs (2,143 in total) were performed at baseline, every 6 months, and 2.7 years [2.7] later, when 115 subjects became diabetic. β-Cell glucose sensitivity (slope of the insulin-secretion/plasma glucose dose-response function) and insulin sensitivity were obtained by mathematical modeling of the OGTT glucose/C-peptide responses.

RESULTS

In progressors, baseline insulin sensitivity, fasting insulin secretion, and total postglucose insulin output were similar to those of nonprogressors, whereas β-cell glucose sensitivity was impaired (median 48 pmol/min per m2 per mmol/l [interquartile range 36] vs. 87 pmol/min per m2 per mmol/l [67]; P < 0.0001) and predicted incident diabetes (P < 0.0001) independently of sex, age, BMI, and clinical risk. In progressors, 2-h glucose levels changed little until 0.78 years before diagnosis, when they started to rise rapidly (∼13 mmol · l−1 · year−1); glucose sensitivity began to decline significantly (P < 0.0001) earlier (1.45 years before diagnosis) than the plasma glucose surge. During this anticipation phase, both insulin secretion and insulin sensitivity were essentially stable.

CONCLUSIONS

In high-risk relatives, β-cell glucose sensitivity is impaired and is a strong predictor of diabetes progression. The time trajectories of plasma glucose are frequently biphasic, with a slow linear increase followed by a rapid surge, and are anticipated by a further deterioration of β-cell glucose sensitivity.

Background

Insulin resistance is a risk factor for type 2 diabetes and cardiovascular disease progression. Current diagnostic tests, such as glycemic indicators, have limitations in the early detection of insulin resistant individuals. We searched for novel biomarkers identifying these at-risk subjects.

Methods

Using mass spectrometry, non-targeted biochemical profiling was conducted in a cohort of 399 nondiabetic subjects representing a broad spectrum of insulin sensitivity and glucose tolerance (based on the hyperinsulinemic euglycemic clamp and oral glucose tolerance testing, respectively).

Results

Random forest statistical analysis selected α-hydroxybutyrate (α–HB) as the top-ranked biochemical for separating insulin resistant (lower third of the clamp-derived MFFM = 33 [12] µmol·min−1·kgFFM−1, median [interquartile range], n = 140) from insulin sensitive subjects (MFFM = 66 [23] µmol·min−1·kgFFM−1) with a 76% accuracy. By targeted isotope dilution assay, plasma α–HB concentrations were reciprocally related to MFFM; and by partition analysis, an α–HB value of 5 µg/ml was found to best separate insulin resistant from insulin sensitive subjects. α–HB also separated subjects with normal glucose tolerance from those with impaired fasting glycemia or impaired glucose tolerance independently of, and in an additive fashion to, insulin resistance. These associations were also independent of sex, age and BMI. Other metabolites from this global analysis that significantly correlated to insulin sensitivity included certain organic acid, amino acid, lysophospholipid, acylcarnitine and fatty acid species. Several metabolites are intermediates related to α-HB metabolism and biosynthesis.

Conclusions

α–hydroxybutyrate is an early marker for both insulin resistance and impaired glucose regulation. The underlying biochemical mechanisms may involve increased lipid oxidation and oxidative stress.

The consensus algorithm for the medical management of type 2 diabetes was published in August 2006 with the expectation that it would be updated, based on the availability of new interventions and new evidence to establish their clinical role. The authors continue to endorse the principles used to develop the algorithm and its major features. We are sensitive to the risks of changing the algorithm cavalierly or too frequently, without compelling new information. An update to the consensus algorithm published in January 2008 specifically addressed safety issues surrounding the thiazolidinediones. In this revision, we focus on the new classes of medications that now have more clinical data and experience.

Epidemiological studies consistently show that circulating sex hormone binding globulin (SHBG) levels are lower in type 2 diabetes patients than non-diabetic individuals, but the causal nature of this association is controversial. Genetic studies can help dissect causal directions of epidemiological associations because genotypes are much less likely to be confounded, biased or influenced by disease processes. Using this Mendelian randomization principle, we selected a common single nucleotide polymorphism (SNP) near the SHBG gene, rs1799941, that is strongly associated with SHBG levels. We used data from this SNP, or closely correlated SNPs, in 27 657 type 2 diabetes patients and 58 481 controls from 15 studies. We then used data from additional studies to estimate the difference in SHBG levels between type 2 diabetes patients and controls. The SHBG SNP rs1799941 was associated with type 2 diabetes [odds ratio (OR) 0.94, 95% CI: 0.91, 0.97; P = 2 × 10−5], with the SHBG raising allele associated with reduced risk of type 2 diabetes. This effect was very similar to that expected (OR 0.92, 95% CI: 0.88, 0.96), given the SHBG-SNP versus SHBG levels association (SHBG levels are 0.2 standard deviations higher per copy of the A allele) and the SHBG levels versus type 2 diabetes association (SHBG levels are 0.23 standard deviations lower in type 2 diabetic patients compared to controls). Results were very similar in men and women. There was no evidence that this variant is associated with diabetes-related intermediate traits, including several measures of insulin secretion and resistance. Our results, together with those from another recent genetic study, strengthen evidence that SHBG and sex hormones are involved in the aetiology of type 2 diabetes.

OBJECTIVE—The purpose of this study was to assess incidence of and risk factors for recurrent cardiovascular disease (CVD) in type 2 diabetes.

RESEARCH DESIGN AND METHODS—We estimated the incidence of recurrent cardiovascular events in type 2 diabetic patients, aged 40–97 years, followed by a network of diabetes clinics. The analysis was conducted separately for 2,788 patients with CVD at enrollment (cohort A) and for 844 patients developing the first episode during the observation period (cohort B).

RESULTS—During 4 years of follow-up, in cohort A the age-adjusted incidence of a recurrent event (per 1,000 person-years) was 72.7 (95% CI 58.3–87.1) in men and 32.5 (21.2–43.7) in women, whereas in cohort B it was 40.1 (17.4–62.9) in men and 22.4 (12.9–32.0) in women. After controls were included for potential predictors (familial CVD, obesity, smoking, diabetes duration, glycemic control, microvascular complications, geographic area, and antihypertensive and lipid-lowering treatment), male sex, older age, and insulin use were significant independent risk predictors (cohort A) and serum triglyceride levels ≥1.69 mmol/l emerged as the only metabolic (negative) prognostic factor (cohort B). In both cohorts, a prior CVD episode, especially myocardial infarction, was by far the strongest predictor of recurrent CVD.

CONCLUSIONS—Approximately 6% of unselected diabetic patients in secondary prevention develop recurrent major CVD every year. Those with long-standing previous CVD show a higher incidence of recurrence. Male sex, age, high triglyceride levels, and insulin use are additional predictors of recurrence.

OBJECTIVE— Physical activity is a modifiable risk factor for type 2 diabetes, partly through its action on insulin sensitivity. We report the relation between insulin sensitivity and physical activity measured by accelerometry.

RESEARCH DESIGN AND METHODS— This is a cross-sectional study of 346 men and 455 women, aged 30–60 years, without cardiovascular disease and not treated by drugs for diabetes, hypertension, dyslipidemia, or obesity. Participants were recruited in 18 clinical centers from 13 European countries. Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamp. Physical activity was recorded by accelerometry for a median of 6 days. We studied the relationship of insulin sensitivity with total activity (in counts per minute), percent of time spent sedentary, percent of time in light activity, and activity intensity (whether the participant recorded some vigorous or some moderate activity).

RESULTS— In both men and women, total activity was associated with insulin sensitivity (P < 0.0001). Time spent sedentary, in light activity, and activity intensity was also associated with insulin sensitivity (P < 0.0004/0.01, 0.002/0.03, and 0.02/0.004, respectively, for men/women) but lost significance once adjusted for total activity. Adjustment for confounders such as adiposity attenuated the relationship with total activity; there were no interactions with confounders. Even in the 25% most sedentary individuals, total activity was significantly associated with better insulin sensitivity (P < 0.0001).

CONCLUSIONS— Accumulated daily physical activity is a major determinant of insulin sensitivity. Time spent sedentary, time spent in light-activity, and bouts of moderate or vigorous activity did not impact insulin sensitivity independently of total activity.

OBJECTIVE

Physical activity is a modifiable risk factor for type 2 diabetes, partly through its action on insulin sensitivity. We report the relation between insulin sensitivity and physical activity measured by accelerometry.

RESEARCH DESIGN AND METHODS

This cross-sectional study is of 346 men and 455 women, aged 30 to 60 years, without cardiovascular disease and not treated by drugs for diabetes, hypertension, dyslipidaemia or obesity; they were recruited in 18 clinical centres from 13 European countries. Insulin sensitivity was measured by hyperinsulinaemic euglycaemic clamp. Physical activity was recorded by accelerometry for a median of six days. We studied the relationship of insulin sensitivity with total activity (number of counts/min), percent time spent sedentary, percent tine in light activity and activity intensity (whether the participant recorded some vigorous or some moderate activity).

RESULTS

In both men and women, total activity was associated with insulin sensitivity (P < 0.0001). Time spent sedentary, in light activity, and activity intensity were also associated with insulin sensitivity (P < 0.0004/0.01; 0.002/0.03; 0.02/0.004 respectively for men/women), but lost significance once adjusted for total activity. Adjustment for confounders, such as adiposity, attenuated the relations with total activity; there were no interactions with confounders. Even in the 25% most sedentary individuals, total activity was significantly associated with better insulin sensitivity (P < 0.0001)

CONCLUSIONS

Accumulated daily physical activity is a major determinant of insulin sensitivity. Neither time spent sedentary, in light-activity, nor bouts of moderate or vigorous activity impacted on insulin sensitivity independently of total activity.