Explore the vast range of titles available.

Glucose metabolism is normally regulated by a feedback loop including islet β cells and insulin-sensitive tissues, in which tissue sensitivity to insulin affects magnitude of β-cell response. If insulin resistance is present, β cells maintain normal glucose tolerance by increasing insulin output. Only when β cells cannot release sufficient insulin in the presence of insulin resistance do glucose concentrations rise. Although β-cell dysfunction has a clear genetic component, environmental changes play an essential part. Modern research approaches have helped to establish the important role that hexoses, aminoacids, and fatty acids have in insulin resistance and β-cell dysfunction, and the potential role of changes in the microbiome. Several new approaches for treatment have been developed, but more effective therapies to slow progressive loss of β-cell function are needed. Recent findings from clinical trials provide important information about methods to prevent and treat type 2 diabetes and some of the adverse effects of these interventions. However, additional long-term studies of drugs and bariatric surgery are needed to identify new ways to prevent and treat type 2 diabetes and thereby reduce the harmful effects of this disease.

Obesity and insulin resistance are associated with the development of type 2 diabetes. It is well accepted that beta cell dysfunction is required for hyperglycaemia to occur. The prevailing view is that, in the presence of insulin resistance, beta cell dysfunction that occurs early in the course of the disease process is the critical abnormality. An alternative model has been proposed in which primary beta cell overstimulation results in insulin hypersecretion that then leads to the development of obesity and insulin resistance, and ultimately to beta cell exhaustion. In this review, data from preclinical and clinical studies, including intervention studies, are discussed in the context of these models. The preponderance of the data supports the view that an early beta cell functional defect is the more likely mechanism underlying the pathogenesis of hyperglycaemia in the majority of individuals who develop type 2 diabetes.

The SELECT trial previously reported a 20% reduction in major adverse cardiovascular events with semaglutide ( n  = 8,803) versus placebo ( n  = 8,801) in patients with overweight/obesity and established cardiovascular disease, without diabetes. In the present study, we examined the effect of once-weekly semaglutide 2.4 mg on kidney outcomes in the SELECT trial. The incidence of the pre-specified main composite kidney endpoint (death from kidney disease, initiation of chronic kidney replacement therapy, onset of persistent estimated glomerular filtration rate (eGFR) < 15 ml min −1  1.73 m − 2 , persistent ≥50% reduction in eGFR or onset of persistent macroalbuminuria) was lower with semaglutide (1.8%) versus placebo (2.2%): hazard ratio (HR) = 0.78; 95% confidence interval (CI) 0.63, 0.96; P  = 0.02. The treatment benefit at 104 weeks for eGFR was 0.75 ml min −1  1.73 m − 2 (95% CI 0.43, 1.06; P  < 0.001) overall and 2.19 ml min −1  1.73 m − 2 (95% CI 1.00, 3.38; P  < 0.001) in patients with baseline eGFR <60 ml min −1  1.73 m − 2 . These results suggest a benefit of semaglutide on kidney outcomes in individuals with overweight/obesity, without diabetes. ClinicalTrials.gov identifier: NCT03574597 . In a pre-specified secondary analysis of the SELECT trial, once-weekly subcutaneous semaglutide 2.4 mg in patients with obesity was associated with a 22% reduction in the main 5-component kidney composite endpoint compared to patients on placebo.

Our objective was to quantify and predict diabetes risk reduction during the Diabetes Prevention Program Outcomes Study (DPPOS) in participants who returned to normal glucose regulation at least once during the Diabetes Prevention Program (DPP) compared with those who consistently met criteria for prediabetes. DPPOS is an ongoing observational study of participants from the DPP randomised trial. For this analysis, diabetes cumulative incidence in DPPOS was calculated for participants with normal glucose regulation or prediabetes status during DPP with and without stratification by previous randomised treatment group. Cox proportional hazards modelling and generalised linear mixed models were used to quantify the effect of previous (DPP) glycaemic status on risk of later (DPPOS) diabetes and normal glucose regulation status, respectively, per SD in change. Included in this analysis were 1990 participants of DPPOS who had been randomly assigned to treatment groups during DPP (736 intensive lifestyle intervention, 647 metformin, 607 placebo). These studies are registered at ClinicalTrials.gov, NCT00004992 (DPP) and NCT00038727 (DPPOS). Diabetes risk during DPPOS was 56% lower for participants who had returned to normal glucose regulation versus those who consistently had prediabetes (hazard ratio [HR] 0·44, 95% CI 0·37–0·55, p<0·0001) and was unaffected by previous group assignment (interaction test for normal glucose regulation and lifestyle intervention, p=0·1722; normal glucose regulation and metformin, p=0·3304). Many, but not all, of the variables that increased diabetes risk were inversely associated with the chance of a participant reaching normal glucose regulation status in DPPOS. Specifically, previous achievement of normal glucose regulation (odds ratio [OR] 3·18, 95% CI 2·71–3·72, p<0·0001), increased β-cell function (OR 1·28; 95% CI 1·18–1·39, p<0·0001), and insulin sensitivity (OR 1·16, 95% CI 1·08–1·25, p<0·0001) were associated with normal glucose regulation in DPPOS, whereas the opposite was true for prediction of diabetes, with increased β-cell function (HR 0·80, 95% CI 0·71–0·89, p<0·0001) and insulin sensitivity (HR 0·83, 95% CI 0·74–0·94, p=0·0001) having a protective effect. Among participants who did not return to normal glucose regulation in DPP, those assigned to the intensive lifestyle intervention had a higher diabetes risk (HR 1·31, 95% CI 1·03–1·68, p=0·0304) and lower chance of normal glucose regulation (OR 0·59, 95% CI 0·42–0·82, p=0·0014) than did the placebo group in DPPOS. We conclude that prediabetes is a high-risk state for diabetes, especially in patients who remain with prediabetes despite intensive lifestyle intervention. Reversion to normal glucose regulation, even if transient, is associated with a significantly reduced risk of future diabetes independent of previous treatment group. US National Institutes of Health.

To examine the impact of SARS-CoV-2 on long-term glycemia. We conducted a retrospective inception cohort study using Veterans Health Administration data (March 1, 2020-May 31, 2022) among individuals with ≥ 1 positive nasal swab for SARS-CoV-2 and individuals with ≥ 1 laboratory test of any type but no positive swab. Two incident diabetes cohorts were defined based on: 1) a computable phenotype using a combination of diagnosis codes, laboratory tests, and receipt of glucose-lowering medications (n = 17,754); and 2) the presence of ≥ 2 HbA1c results ≥ 6.5% (n = 4,768). We fit log-binomial models examining associations of SARS-CoV-2 with diabetes remission, defined as ≥ 2 HbA1c measurements < 6.5% ≥ 90 days apart after cessation of any glucose-lowering medications. To help equalize laboratory surveillance of glycemia, we conducted a subgroup analysis among non-hospitalized participants. In cohorts 1 and 2 respectively, 25% and 29% had ≥ 1 positive test for SARS-CoV-2 prior to enrollment, and 21% and 11% had remission. SARS-CoV-2 was associated with a higher chance of remission by both definitions (1: RR 1.22 [95%CI 1.14-1.29]; 2: RR 1.27 [95%CI 1.07-1.50]) over an average 503 (±202) and 494 (±184) days. The association was attenuated among non-hospitalized participants (1: RR 1.11 [1.04-1.20]; 2: R: 1.17 [95%CI 0.97-1.42]). Diabetes remission was more common in Veterans with new-onset diabetes after SARS-CoV-2. In non-hospitalized participants, who were likely to have more similar laboratory surveillance, the association was diminished. Differences in surveillance or transient hyperglycemia may explain the observed association.

The orexigenic gut hormone ghrelin and its receptor are present in pancreatic islets. Although ghrelin reduces insulin secretion in rodents, its effect on insulin secretion in humans has not been established. The goal of this study was to test the hypothesis that circulating ghrelin suppresses glucose-stimulated insulin secretion in healthy subjects. Ghrelin (0.3, 0.9 and 1.5 nmol/kg/h) or saline was infused for more than 65 min in 12 healthy patients (8 male/4 female) on 4 separate occasions in a counterbalanced fashion. An intravenous glucose tolerance test was performed during steady state plasma ghrelin levels. The acute insulin response to intravenous glucose (AIRg) was calculated from plasma insulin concentrations between 2 and 10 min after the glucose bolus. Intravenous glucose tolerance was measured as the glucose disappearance constant (Kg) from 10 to 30 min. The three ghrelin infusions raised plasma total ghrelin concentrations to 4-, 15-, and 23-fold above the fasting level, respectively. Ghrelin infusion did not alter fasting plasma insulin or glucose, but compared with saline, the 0.3, 0.9, and 1.5 nmol/kg/h doses decreased AIRg (2,152 +/- 448 vs. 1,478 +/- 2,889, 1,419 +/- 275, and 1,120 +/- 174 pmol/l) and Kg (0.3 and 1.5 nmol/kg/h doses only) significantly (P < 0.05 for all). Ghrelin infusion raised plasma growth hormone and serum cortisol concentrations significantly (P < 0.001 for both), but had no effect on glucagon, epinephrine, or norepinephrine levels (P = 0.44, 0.74, and 0.48, respectively). This is a robust proof-of-concept study showing that exogenous ghrelin reduces glucose-stimulated insulin secretion and glucose disappearance in healthy humans. Our findings raise the possibility that endogenous ghrelin has a role in physiologic insulin secretion, and that ghrelin antagonists could improve beta-cell function.

This double-blind, randomized, controlled trial evaluated rosiglitazone, metformin, and glyburide as an initial treatment in patients with type 2 diabetes. Rosiglitazone reduced the risk of treatment failure (the primary outcome) by 32% as compared with metformin and by 63% as compared with glyburide. The potential risks, benefits, and costs of these medications should all be considered to help inform the choice of pharmacotherapy for patients with type 2 diabetes. In patients with type 2 diabetes, rosiglitazone reduced the risk of treatment failure by 32% as compared with metformin and by 63% as compared with glyburide. The attainment and maintenance of near-normal glycemia reduces the risk of long-term complications of diabetes. 1 – 3 Despite lifestyle and pharmacologic interventions, glucose levels increase over time in type 2 diabetes, probably as a consequence of declining β-cell function. 4 The progressive nature of type 2 diabetes makes it difficult to maintain target levels of glycated hemoglobin with traditional glucose-lowering agents 5 , 6 and generally necessitates the escalation of drug doses and the use of combination therapies or insulin. 7 Thiazolidinediones reduce insulin resistance by sensitizing muscle, liver, and adipose tissue to insulin 8 and delay progression to type 2 diabetes in patients with glucose . . .

OBJECTIVE:--We sought to examine racial and ethnic differences in A1C in individuals with impaired glucose tolerance (IGT). RESEARCH DESIGN AND METHODS-- We studied 3,819 individuals aged >=25 years with IGT who were found to be eligible to participant in the Diabetes Prevention Program. A1C was compared among five racial and ethnic groups before and after adjustment for factors that differed among groups or might affect glycemia including age, sex, education, marital status, blood pressure, adiposity (BMI and waist circumference), hematocrit, fasting and post-glucose load glucose levels, glucose area under the curve (AUC), β-cell function, and insulin resistance. RESULTS:--Mean ± SD A1C was 5.91 ± 0.50%. Among whites, A1C was 5.80 ± 0.44%, among Hispanics 5.89 ± 0.46%, among Asian 5.96 ± 0.45%, among American Indians 5.96 ± 0.46%, and among blacks 6.19 ± 0.59%. Age, sex, systolic blood pressure, diastolic blood pressure, BMI, fasting glucose, glucose AUC, corrected insulin response, and insulin resistance were each independent predictors of A1C. Adjusting for these and other factors, mean A1C levels were 5.78% for whites, 5.93% for Hispanics, 6.00% for Asians, 6.12% for American Indians, and 6.18% for blacks (P < 0.001). CONCLUSIONS:-- A1C levels are higher among U.S. racial and ethnic minority groups with IGT after adjustment for factors likely to affect glycemia. Among patients with IGT, A1C may not be valid for assessing and comparing glycemic control across racial and ethnic groups or as an indicator of health care disparities.

Aims/hypothesis Amyloid deposition and inflammation are characteristic of islet pathology in type 2 diabetes. The aim of this study was to determine whether islet amyloid formation is required for the development of islet inflammation in vivo. Methods Human islet amyloid polypeptide transgenic mice and non-transgenic littermates (the latter incapable of forming islet amyloid) were fed a low-fat (10%) or high-fat (60%) diet for 12 months; high-fat feeding induces islet amyloid formation in transgenic mice. At the conclusion of the study, glycaemia, beta cell function, islet amyloid deposition, markers of islet inflammation and islet macrophage infiltration were measured. Results Fasting plasma glucose levels did not differ by diet or genotype. Insulin release in response to i.v. glucose was significantly greater in both high vs low fat groups, and significantly lower in both transgenic compared with non-transgenic groups. Only high-fat-fed transgenic mice developed islet amyloid and showed a trend towards reduced beta cell area. Compared with islets from low-fat-fed transgenic or high-fat-fed non-transgenic mice, islets of high-fat-fed transgenic mice displayed a significant increase in the expression of genes encoding chemokines ( Ccl2, Cxcl1 ), macrophage/dendritic cell markers ( Emr1, Itgax ), NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome components ( Nlrp3, Pycard, Casp1 ) and proinflammatory cytokines ( Il1b, Tnf, Il6 ), as well as increased F4/80 staining, consistent with increased islet inflammation and macrophage infiltration. Conclusions/interpretation Our results indicate that islet amyloid formation is required for the induction of islet inflammation in this long-term high-fat-diet model, and thus could promote beta cell dysfunction in type 2 diabetes via islet inflammation.