This was a cohort study using an active-comparator, new-user design and nationwide register data from Sweden, Denmark, and Norway during 2010–2016. The cohort included 38,731 new users of GLP-1 receptor agonists (liraglutide 92.5%, exenatide 6.2%, lixisenatide 0.7%, and dulaglutide 0.6%), matched 1:1 on age, sex, and propensity score to a new user of the active comparator, dipeptidyl peptidase 4 (DPP-4) inhibitors. The main outcome was serious renal events, a composite including renal replacement therapy, death from renal causes, and hospitalization for renal events. Secondary outcomes were the individual components of the main outcome. Hazard ratios (HRs) were estimated using Cox models and an intention-to-treat exposure definition. Mean (SD) follow-up time was 3.0 (1.7) years.

Mean (SD) age of the study population was 59 (10) years, and 18% had cardiovascular disease. A serious renal event occurred in 570 users of GLP-1 receptor agonists (incidence rate 4.8 events per 1,000 person-years) and in 722 users of DPP-4 inhibitors (6.3 events per 1,000 person-years, HR 0.76 [95% CI 0.68–0.85], absolute difference –1.5 events per 1,000 person-years [–2.1 to –0.9]). Use of GLP-1 receptor agonists was associated with a significantly lower risk of renal replacement therapy (HR 0.73 [0.62–0.87]) and hospitalization for renal events (HR 0.73 [0.65–0.83]) but not death from renal causes (HR 0.72 [0.48–1.10]). When we used an as treated exposure definition in which patients were censored at treatment cessation or switch to the other study drug, the HR for the primary outcome was 0.60 (0.49–0.74).

In this large cohort of patients seen in routine clinical practice in three countries, use of GLP-1 receptor agonists, as compared with DPP-4 inhibitors, was associated with a reduced risk of serious renal events.

In this phase 3, open-label, multicenter trial, 321 patients with HbA_1c≥7.5 to ≤10.0% (58–86 mmol/mol) and fasting plasma glucose (FPG) ≤13.8 mmol/L (250 mg/dL) were randomized 1:1 to iGlarLixi or Lixi for 52 weeks. The primary end point was change in HbA_1c at week 26.

Change in HbA_1c from baseline to week 26 was significantly greater with iGlarLixi (–1.58% [–17.3 mmol/mol]) than with Lixi (–0.51% [–5.6 mmol/mol]), confirming the superiority of iGlarLixi (least squares [LS] mean difference –1.07% [–11.7 mmol/mol], P < 0.0001). At week 26, significantly greater proportions of patients treated with iGlarLixi reached HbA_1c <7% (53 mmol/mol) (65.2% vs. 19.4%; P < 0.0001), and FPG reductions were greater with iGlarLixi than Lixi (LS mean difference –2.29 mmol/L [–41.23 mg/dL], P < 0.0001). Incidence of documented symptomatic hypoglycemia (≤3.9 mmol/L [70 mg/dL]) was higher with iGlarLixi (13.0% vs. 2.5%) through week 26, with no severe hypoglycemic events in either group. Incidence of gastrointestinal events through week 52 was lower with iGlarLixi (36.0% vs. 50.0%), and rates of treatment-emergent adverse events were similar.

This phase 3 study demonstrated superior glycemic control and fewer gastrointestinal adverse events with iGlarLixi than with Lixi, which may support it as a new treatment option for Japanese patients with T2DM that is inadequately controlled with OADs.

5,181 participants from the cross-sectional Metabolic Syndrome in Men (METSIM) study that included Finnish men (age 57 ± 7 years, BMI 26.5 ± 3.5 kg/m²) having metabolomics data available were included in our study. Metabolomics analysis was performed based on fasting plasma samples. On the basis of an oral glucose tolerance test, Matsuda ISI and Disposition Index values were calculated as markers of insulin sensitivity and insulin secretion. A total of 4,851 participants had a 7.4-year follow-up visit, and 522 participants developed type 2 diabetes.

Creatine, 1-palmitoleoylglycerol (16:1), urate, 2-hydroxybutyrate/2-hydroxyisobutyrate, xanthine, xanthurenate, kynurenate, 3-(4-hydroxyphenyl)lactate, 1-oleoylglycerol (18:1), 1-myristoylglycerol (14:0), dimethylglycine, and 2-hydroxyhippurate (salicylurate) were significantly associated with an increased risk of type 2 diabetes. These metabolites were associated with decreased insulin secretion or insulin sensitivity or both. Among the metabolites that were associated with a decreased risk of type 2 diabetes, 1-linoleoylglycerophosphocholine (18:2) significantly reduced the risk of type 2 diabetes.

Several novel and previously reported microbial metabolites related to the gut microbiota were associated with an increased risk of incident type 2 diabetes, and they were also associated with decreased insulin secretion and insulin sensitivity. Microbial metabolites are important biomarkers for the risk of type 2 diabetes.

A cohort study was conducted in 54,075 adults without diabetes who underwent 3-min HRV measurement during health checkups between 2011 and 2014 at Kangbuk Samsung Hospital. We analyzed the time domain (SD of the normal-to-normal interval [SDNN] and root mean square differences of successive normal-to-normal interval [RMSSD]) and the frequency domain (total power, normalized low-frequency power [LF], and normalized high-frequency power [HF] and LF/HF ratio). We compared the risk of diabetes until 2017 according to tertiles of heart rate and HRV variables, with tertile 1 serving as the reference group.

During 243,758.2 person-years, 1,369 subjects were diagnosed with diabetes. Both time and frequency domain variables were lower in the group with diabetes, with the exception of those with normalized LF and LF/HF ratio. In Cox analysis, as SDNN, RMSSD, and normalized HF tertiles increased, the risk of diabetes decreased (hazard ratios [95% CIs] of tertile 3: 0.81 [0.70–0.95], 0.76 [0.65–0.90], and 0.78 [0.67–0.91], respectively), whereas the risk of diabetes increased in the case of heart rate, normalized LF, and LF/HF ratio (hazard ratios [95% CIs] of tertile 3: 1.41 [1.21–1.65], 1.32 [1.13–1.53], and 1.31 [1.13–1.53), respectively) after adjusting for age, sex, BMI, smoking, drinking, systolic blood pressure, lipid level, CRP, and HOMA of insulin resistance.

Abnormal HRV, especially decreased vagal activity and deviation in sympathovagal imbalance to sympathetic activity, might precede incident diabetes.

Up to 4,761 offspring from the Avon Longitudinal Study of Parents and Children were studied. Linear models were used to examine effects of a genetic risk score (162 variants) for adult type 2 diabetes on 229 metabolomic traits (lipoprotein subclass–specific cholesterol and triglycerides, amino acids, glycoprotein acetyls, others) measured at age 8 years, 16 years, 18 years, and 25 years. Two-sample Mendelian randomization (MR) was also conducted using genome-wide association study data on metabolomic traits in an independent sample of 24,925 adults.

At age 8 years, associations were most evident for type 2 diabetes liability (per SD-higher) with lower lipids in HDL subtypes (e.g., –0.03 SD, 95% CI –0.06, –0.003 for total lipids in very large HDL). At 16 years, associations were stronger with preglycemic traits, including citrate and with glycoprotein acetyls (0.05 SD, 95% CI 0.01, 0.08), and at 18 years, associations were stronger with branched chain amino acids. At 25 years, associations had strengthened with VLDL lipids and remained consistent with previously altered traits, including HDL lipids. Two-sample MR estimates among adults indicated persistent patterns of effect of disease liability.

Our results support perturbed HDL lipid metabolism as one of the earliest features of type 2 diabetes liability, alongside higher branched-chain amino acid and inflammatory levels. Several features are apparent in childhood as early as age 8 years, decades before the clinical onset of disease.

We included 84,285 postmenopausal women without a history of diabetes from the national Women’s Health Initiative Observational Study (WHI-OS). Replication analysis was then conducted among 62,338 women who participated in the WHI-Clinical Trial (WHI-CT). Additionally, data from a case-control study of 3,749 women nested in the WHI-OS with information on biomarkers of inflammation and endothelial dysfunction were examined using mediation analysis to determine the relative contributions of these known biomarkers by which manganese affects type 2 diabetes risk.

Compared with the lowest quintile of energy-adjusted dietary manganese, WHI-OS participants in the highest quintile had a 30% lower risk of type 2 diabetes (hazard ratio [HR] 0.70 [95% CI 0.65, 0.76]). A consistent association was also confirmed in the WHI-CT (HR 0.79 [95% CI 0.73, 0.85]). In the nested case-control study, higher energy-adjusted dietary manganese was associated with lower circulating levels of inflammatory biomarkers that significantly mediated the association between dietary manganese and type 2 diabetes risk. Specifically, 19% and 12% of type 2 diabetes risk due to manganese were mediated through interleukin 6 and hs-CRP, respectively.

Higher intake of manganese was directly associated with a lower type 2 diabetes risk independent of known risk factors. This association may be partially mediated by inflammatory biomarkers.

Four years of data were extracted from a hospital electronic health record system. This included laboratory and point-of-care blood glucose (BG) values to identify biochemical and clinically significant hypoglycemic episodes (BG ≤3.9 and ≤2.9 mmol/L, respectively). We used patient demographics, administered medications, vital signs, laboratory results, and procedures performed during the hospital stays to inform the model. Two iterations of the data set included the doses of insulin administered and the past history of inpatient hypoglycemia. Eighteen different prediction models were compared using the area under the receiver operating characteristic curve (AUROC) through a 10-fold cross validation.

We analyzed data obtained from 17,658 inpatients with diabetes who underwent 32,758 admissions between July 2014 and August 2018. The predictive factors from the logistic regression model included people undergoing procedures, weight, type of diabetes, oxygen saturation level, use of medications (insulin, sulfonylurea, and metformin), and albumin levels. The machine learning model with the best performance was the XGBoost model (AUROC 0.96). This outperformed the logistic regression model, which had an AUROC of 0.75 for the estimation of the risk of clinically significant hypoglycemia.

Advanced machine learning models are superior to logistic regression models in predicting the risk of hypoglycemia in inpatients with diabetes. Trials of such models should be conducted in real time to evaluate their utility to reduce inpatient hypoglycemia.

A total of 4,699 people with diabetes who enrolled in the National Health and Nutrition Examination Survey from 2003 to 2014 were recruited for this study. Energy and macronutrient intake was measured by a 24-h dietary recall. The differences () in energy and macronutrient intake between dinner and breakfast ( = dinner – breakfast) were categorized into quintiles. Death information was obtained from the National Death Index until 2015. Cox proportional hazards regression models were developed to evaluate the survival relationship between and diabetes, cardiovascular disease (CVD), and all-cause mortality.

Among the 4,699 participants, 913 deaths, including 269 deaths due to diabetes and 314 deaths due to CVD, were documented. After adjustment for potential confounders, compared with participants in the lowest quintile of in terms of total energy and protein, participants in the highest quintile were more likely to die due to diabetes (hazard ratio [HR]_energy 1.92, 99% CI 1.08–3.42; HR_protein 1.92, 99% CI 1.06–3.49) and CVD (HR_energy 1.69, 99% CI 1.02–2.80; HR_protein 1.96, 99% CI 1.14–3.39). The highest quintile of total fat was related to CVD mortality (HR 1.67, 99% CI 1.01–2.76). Isocalorically replacing 5% of total energy at dinner with breakfast was associated with 4% and 5% lower risk of diabetes (HR 0.96, 95% CI 0.94–0.98) and CVD (HR 0.95, 95% CI 0.93–0.97) mortality, respectively.

Higher intake of energy, total fat, and protein from dinner than breakfast was associated with greater diabetes, CVD, and all-cause mortality in people with diabetes.

The Action to Control Cardiovascular Risk in Diabetes Blood Pressure trial (ACCORD BP), a two-by-two factorial randomized controlled trial, examined effects of SBP (<120 vs. <140 mmHg) and glycemic (HbA_1c <6% vs. 7.0–7.9% [<42 vs. 53–63 mmol/mol]) control on cardiovascular events in T2DM (N = 4,731). We examined whether effects of SBP control on cardiovascular composite were modified by baseline DBP and glycemic control.

Intensive SBP lowering decreased the risk of the cardiovascular composite (hazard ratio [HR] 0.76 [95% CI 0.59–0.98]) in the standard glycemic arm but not in the intensive glycemic arm (HR 1.06 [95% CI 0.81–1.40]). Spline regression models relating the effects of the intervention on the cardiovascular composite across the range of baseline DBP did not show evidence of effect modification by low baseline DBP for the cardiovascular composite in the standard or intensive glycemic arms. The relation between the effect of the intensive SBP intervention and baseline DBP was similar between glycemic arms for the cardiovascular composite three-way interaction (P = 0.83).

In persons with T2DM, intensive SBP lowering decreased the risk of cardiovascular composite end point irrespective of baseline DBP in the setting of standard glycemic control. Hence, low baseline DBP should not be an impediment to intensive SBP lowering in patients with T2DM treated with guidelines recommending standard glycemic control.

We performed exploratory analyses to identify potential mediators of the effect of liraglutide on major adverse CV events (MACE; composite of CV death, nonfatal myocardial infarction, or nonfatal stroke) from the following candidates: glycated hemoglobin (HbA_1c), body weight, urinary albumin-to-creatinine ratio (UACR), confirmed hypoglycemia, sulfonylurea use, insulin use, systolic blood pressure, and LDL cholesterol. These candidates were selected as CV risk factors on which liraglutide had an effect in LEADER such that a reduction in CV risk might result. We used two methods based on a Cox proportional hazards model and the new Vansteelandt method designed to use all available information from the mediator and to control for confounding factors.

Analyses using the Cox methods and Vansteelandt method indicated potential mediation by HbA_1c (up to 41% and 83% mediation, respectively) and UACR (up to 29% and 33% mediation, respectively) on the effect of liraglutide on MACE. Mediation effects were small for other candidates.

These analyses identify HbA_1c and, to a lesser extent, UACR as potential mediators of the CV effects of liraglutide. Whether either is a marker of an unmeasured factor or a true mediator remains a key question that invites further investigation.

Patients with T2DM received either once weekly tirzepatide (1, 5, 10, or 15 mg), dulaglutide (1.5 mg), or placebo for 26 weeks. Changes from baseline in alanine aminotransferase (ALT), aspartate aminotransferase (AST), keratin-18 (K-18), procollagen III (Pro-C3), and adiponectin were analyzed in a modified intention-to-treat population.

Significant (P < 0.05) reductions from baseline in ALT (all groups), AST (all groups except tirzepatide 10 mg), K-18 (tirzepatide 5, 10, 15 mg), and Pro-C3 (tirzepatide 15 mg) were observed at 26 weeks. Decreases with tirzepatide were significant compared with placebo for K-18 (10 mg) and Pro-C3 (15 mg) and with dulaglutide for ALT (10, 15 mg). Adiponectin significantly increased from baseline with tirzepatide compared with placebo (10, 15 mg).

In post hoc analyses, higher tirzepatide doses significantly decreased NASH-related biomarkers and increased adiponectin in patients with T2DM.

This prospective, open-label, randomized clinical trial included 176 patients with poorly controlled T2D (admission blood glucose [BG] 228 ± 82 mg/dL and HbA_1c 9.5 ± 2.2%), treated with oral agents or insulin before admission. Patients were treated with a basal-bolus regimen with glargine U300 (n = 92) or glargine U100 (n = 84) and glulisine before meals. We adjusted insulin daily to a target BG of 70–180 mg/dL. The primary end point was noninferiority in the mean difference in daily BG between groups. The major safety outcome was the occurrence of hypoglycemia.

There were no differences between glargine U300 and U100 in mean daily BG (186 ± 40 vs. 184 ± 46 mg/dL, P = 0.62), percentage of readings within target BG of 70–180 mg/dL (50 ± 27% vs. 55 ± 29%, P = 0.3), length of stay (median [IQR] 6.0 [4.0, 8.0] vs. 4.0 [3.0, 7.0] days, P = 0.06), hospital complications (6.5% vs. 11%, P = 0.42), or insulin total daily dose (0.43 ± 0.21 vs. 0.42 ± 0.20 units/kg/day, P = 0.74). There were no differences in the proportion of patients with BG <70 mg/dL (8.7% vs. 9.5%, P > 0.99), but glargine U300 resulted in significantly lower rates of clinically significant hypoglycemia (<54 mg/dL) compared with glargine U100 (0% vs. 6.0%, P = 0.023).

Hospital treatment with glargine U300 resulted in similar glycemic control compared with glargine U100 and may be associated with a lower incidence of clinically significant hypoglycemia.

A total of 291 subjects aged 35–60 years with normal glucose tolerance (NGT), newly diagnosed impaired fasting glucose or glucose tolerance (IFG/IGT), or type 2 diabetes were screened by a standard 2-h oral glucose tolerance test (OGTT) with the use of traditional measures to evaluate β-cell function. From these participants, 74 subjects were recruited for an oral minimal model test, and β-cell function was assessed with model-derived indices. Circulating RBP4 levels were measured by a commercially available ELISA kit.

Circulating RBP4 levels were significantly and inversely correlated with β-cell function indicated by the Stumvoll first-phase and second-phase insulin secretion indices, but not with HOMA of β-cell function, calculated from the 2-h OGTT in 291 subjects across the spectrum of glycemia. The inverse association was also observed in subjects involved in the oral minimal model test with β-cell function assessed by both direct measures and model-derived measures, after adjustment for potential confounders. Moreover, RBP4 emerged as an independent factor of the disposition index-total insulin secretion.

Circulating RBP4 levels are inversely and independently correlated with β-cell function across the spectrum of glycemia, providing another possible explanation of the linkage between RBP4 and the pathogenesis of type 2 diabetes.