We studied the effects of more intensive glycemic control in 11,071 patients with type 2 diabetes (T2D), without missing values, in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial, using Cox models.

During 5 years’ follow-up, intensive glycemic control reduced major vascular events (hazard ratio [HR] 0.90 [95% CI 0.83–0.98]), with the major driver being a reduction in the development of macroalbuminuria. There was no evidence of differences in the effect, regardless of baseline ASCVD risk or HbA_1c level (P for interaction = 0.29 and 0.94, respectively). Similarly, the beneficial effects of intensive glycemic control on all-cause mortality were not significantly different across baseline ASCVD risk (P = 0.15) or HbA_1c levels (P = 0.87). The risks of severe hypoglycemic events were higher in the intensive glycemic control group compared with the standard glycemic control group (HR 1.85 [1.41–2.42]), with no significant heterogeneity across subgroups defined by ASCVD risk or HbA_1c at baseline (P = 0.09 and 0.18, respectively).

The major benefits for patients with T2D in ADVANCE did not substantially differ across levels of baseline ASCVD risk and HbA_1c.

Using a group-based modeling approach, we identified sleep duration trajectories based on sleep duration in ages 20–25, 26–35, 36–45, and 46+ years, which were retrospectively assessed in 2009 among 60,068 women from the Nurses’ Health Study II (median age 54.9 years) who were free of diabetes, cardiovascular disease, and cancer. We investigated the prospective associations between sleep duration trajectories and diabetes risk (2009–2017) using multivariable Cox proportional hazards models.

We documented 1,797 incident diabetes cases over a median follow-up of 7.8 years (442,437 person-years). Six sleep duration trajectories were identified: persistent 5-, 6-, 7-, or 8-h sleep duration and increased or decreased sleep duration. After multivariable adjustment for diabetes risk factors, compared with the persistent 7-h sleep duration group, the hazard ratio was 1.43 (95% CI 1.10, 1.84) for the 5-h group, 1.17 (1.04, 1.33) for the 6-h group, 0.96 (0.84, 1.10) for the 8-h group, 1.33 (1.09, 1.61) for the increased sleep duration group, and 1.32 (1.10, 1.59) for the decreased sleep duration group. Additional adjustment for time-updated comorbidities and BMI attenuated these associations, although a significantly higher risk remained in the decreased sleep duration group (1.24 [1.03, 1.50]).

Persistent short sleep duration or changes in sleep duration from early to middle adulthood were associated with higher risk of type 2 diabetes in later life. These associations were weaker after obesity and metabolic comorbidities were accounted for.

This multicenter, double-blind, treat-to-target trial randomized participants to faster aspart (n = 546) or IAsp (n = 545). All available information, regardless of treatment discontinuation or use of ancillary treatment, was used for evaluation of effect.

Noninferiority for the change from baseline in HbA_1c 16 weeks after randomization (primary end point) was confirmed for faster aspart versus IAsp (estimated treatment difference [ETD] –0.04% [95% CI –0.11; 0.03]; –0.39 mmol/mol [–1.15; 0.37]; P < 0.001). Faster aspart was superior to IAsp for change from baseline in 1-h postprandial glucose (PPG) increment using a meal test (ETD –0.40 mmol/L [–0.66; –0.14]; –7.23 mg/dL [–11.92; –2.55]; P = 0.001 for superiority). Change from baseline in self-measured 1-h PPG increment for the mean over all meals favored faster aspart (ETD –0.25 mmol/L [–0.42; –0.09]); –4.58 mg/dL [–7.59; –1.57]; P = 0.003). The overall rate of treatment-emergent severe or blood glucose (BG)–confirmed hypoglycemia was statistically significantly lower for faster aspart versus IAsp (estimated treatment ratio 0.81 [95% CI 0.68; 0.97]).

In combination with insulin degludec, faster aspart provided effective overall glycemic control, superior PPG control, and a lower rate of severe or BG-confirmed hypoglycemia versus IAsp in adults with type 2 diabetes not optimally controlled with a basal-bolus regimen.

This article reports on a prospective, randomized, open-label, blinded end point trial with nested case-control study. Asymptomatic younger adults with T2D were randomized 1:1:1 to a 12-week intervention of 1) routine care, 2) supervised aerobic exercise training, or 3) a low-energy (~810 kcal/day) MRP. Participants underwent echocardiography, cardiopulmonary exercise testing, and cardiac magnetic resonance (CMR) at baseline and 12 weeks. The primary outcome was change in left ventricular (LV) peak early diastolic strain rate (PEDSR) as measured by CMR. Healthy volunteers were enrolled for baseline case-control comparison.

Eighty-seven participants with T2D (age 51 ± 7 years, HbA_1c 7.3 ± 1.1%) and 36 matched control participants were included. At baseline, those with T2D had evidence of diastolic dysfunction (PEDSR 1.01 ± 0.19 vs. 1.10 ± 0.16 s^–1, P = 0.02) compared with control participants. Seventy-six participants with T2D completed the trial (30 routine care, 22 exercise, and 24 MRP). The MRP arm lost 13 kg in weight and had improved blood pressure, glycemia, LV mass/volume, and aortic stiffness. The exercise arm had negligible weight loss but increased exercise capacity. PEDSR increased in the exercise arm versus routine care (β = 0.132, P = 0.002) but did not improve with the MRP (β = 0.016, P = 0.731).

In asymptomatic working-age adults with T2D, exercise training improved diastolic function. Despite beneficial effects of weight loss on glycemic control, concentric LV remodeling, and aortic stiffness, a low-energy MRP did not improve diastolic function.

We conducted a retrospective, cross-sectional analysis of 2003–2016 National Health and Nutrition Examination Survey (NHANES) data. We included people ≥18 years who had ever been told they had diabetes, had an HbA_1C >6.4%, or had a fasting plasma glucose >125 mg/dL. Pregnant women, and those aged <20 years receiving only insulin were excluded. We assessed trends in use of ADA’s seven preferred classes from 2003–2004 to 2015–2016. We also examined use by hypoglycemia risk (sulfonylureas, insulin, and meglitinides), weight effect (sulfonylureas, thiazolidinediones [TZDs], insulin, and meglitinides), cardiovascular benefit (canagliflozin, empagliflozin, and liraglutide), and cost (brand-name medications and insulin analogs).

The final sample included 6,323 patients. The proportion taking any medication increased from 58% in 2003–2004 to 67% in 2015–2016 (P < 0.001). Use of metformin and insulin analogs increased, while use of sulfonylureas, TZDs, and human insulin decreased. Following the 2012 ADA recommendation, the choice of drug did not vary significantly by older age, weight, or presence of cardiovascular disease. Patients with low HbA_1C, or HbA_1C <6%, and age ≥65 years were less likely to receive hypoglycemia-inducing medications, while older patients with comorbidities were more likely. Insurance, but not income, was associated with the use of higher-cost medications.

Following ADA recommendations, the use of metformin increased, but physicians generally did not individualize treatment according to patients’ characteristics. Substantial opportunities exist to improve pharmacologic management of diabetes.

Cox regression models were constructed to analyze 20 years of data from the Danish National Patient Registry with respect to effect of the antihyperglycemic therapies on the three end points.

A total of 66,807 people with type 2 diabetes were treated with metformin (MET) including a combination of second- and third-line therapies. People on MET plus sulfonylurea (SU) had the highest risk of all end points, except for severe hypoglycemia, for which people on MET plus basal insulin (BASAL) had a higher risk. The lowest risk of major adverse cardiovascular events was seen for people on a regimen including a glucagon-like peptide 1 (GLP-1) receptor agonist. People treated with MET, GLP-1, and BASAL had a lower risk of all three end points than people treated with MET and BASAL, especially for severe hypoglycemia. The lowest risk of all three end points was, in general, seen for people treated with MET, sodium–glucose cotransporter 2 inhibitor, and GLP-1.

Findings from this study do not support SU as the second-line treatment choice for patients with type 2 diabetes. Moreover, the results indicate that adding a GLP-1 for people treated with MET and BASAL could be considered, especially if those people suffer from severe hypoglycemia.

This retrospective cohort combined data from the National Veterans Health Administration, Medicare, Medicaid, and the National Death Index. New users of metformin or sulfonylureas were followed from development of reduced kidney function (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m² or serum creatinine ≥1.4 mg/dL [female] or 1.5 mg/dL [male]) through hospitalization for lactic acidosis, death, loss to follow-up, or study end. Lactic acidosis hospitalization was defined as a composite of primary discharge diagnosis or laboratory-confirmed lactic acidosis (lactic acid ≥2.5 mmol/L and either arterial blood pH <7.35 or serum bicarbonate ≤19 mmol/L within 24 h of admission). We report the cause-specific hazard of lactic acidosis hospitalization between metformin and sulfonylureas from a propensity score–matched weighted cohort and conduct an additional competing risks analysis to account for treatment change and death.

The weighted cohort included 24,542 metformin and 24,662 sulfonylurea users who developed reduced kidney function (median age 70 years, median eGFR 55.8 mL/min/1.73 m²). There were 4.18 (95% CI 3.63, 4.81) vs. 3.69 (3.19, 4.27) lactic acidosis hospitalizations per 1,000 person-years among metformin and sulfonylurea users, respectively (adjusted hazard ratio [aHR] 1.21 [95% CI 0.99, 1.50]). Results were consistent for both primary discharge diagnosis (aHR 1.11 [0.87, 1.44]) and laboratory-confirmed lactic acidosis (1.25 [0.92, 1.70]).

Among veterans with diabetes who developed reduced kidney function, occurrence of lactic acidosis hospitalization was uncommon and not statistically different between patients who continued metformin and those patients who continued sulfonylureas.

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.

This age-, sex-, BMI-, and diabetes duration–matched cohort study used data from a U.K. primary care database from 1 January 2005 to 17 January 2018. Participants aged ≥16 years with type 2 diabetes were included. Exposed participants were those who developed OSA after their diabetes diagnosis; unexposed participants were those without diagnosed OSA. Outcomes were composite CVD (ischemic heart disease [IHD], stroke/transient ischemic attack [TIA], heart failure [HF]), peripheral vascular disease (PVD), atrial fibrillation (AF), peripheral neuropathy (PN), diabetes-related foot disease (DFD), referable retinopathy, chronic kidney disease (CKD), and all-cause mortality. The same outcomes were explored in patients with preexisting OSA before a diagnosis of type 2 diabetes versus diabetes without diagnosed OSA.

A total of 3,667 exposed participants and 10,450 matched control participants were included. Adjusted hazard ratios for the outcomes were as follows: composite CVD 1.54 (95% CI 1.32, 1.79), IHD 1.55 (1.26, 1.90), HF 1.67 (1.35, 2.06), stroke/TIA 1.57 (1.27, 1.94), PVD 1.10 (0.91, 1.32), AF 1.53 (1.28, 1.83), PN 1.32 (1.14, 1.51), DFD 1.42 (1.16, 1.74), referable retinopathy 0.99 (0.82, 1.21), CKD (stage 3–5) 1.18 (1.02, 1.36), albuminuria 1.11 (1.01, 1.22), and all-cause mortality 1.24 (1.10, 1.40). In the prevalent OSA cohort, the results were similar, but some associations were not observed.

Patients with type 2 diabetes who develop OSA are at increased risk of CVD, AF, PN, DFD, CKD, and all-cause mortality compared with patients without diagnosed OSA. Patients with type 2 diabetes who develop OSA are a high-risk population, and strategies to detect OSA and prevent cardiovascular and microvascular complications should be implemented.

FPG and urinary biomarkers of oxidative DNA damage (8-hydroxy-deoxyguanosine [8-OHdG]), lipid peroxidation (8-iso-prostaglandin-F2α [8-iso-PGF2α]), and acrylamide exposure (N-acetyl-S-[2-carbamoylethyl]-l-cysteine [AAMA], N-acetyl-S-[2-carbamoyl-2-hydroxyethyl]-l-cysteine [GAMA]) were measured for 3,270 general adults from the Wuhan-Zhuhai cohort. The associations of urinary acrylamide metabolites with 8-OHdG, 8-iso-PGF2α, and FPG were assessed by linear mixed models. The mediating roles of 8-OHdG and 8-iso-PGF2α were evaluated by mediation analysis.

We found significant linear positive dose-response relationships of urinary acrylamide metabolites with 8-OHdG, 8-iso-PGF2α, and FPG (except GAMA with FPG) and 8-iso-PGF2α with FPG. Each 1-unit increase in log-transformed level of AAMA, AAMA + GAMA (UAAM), or 8-iso-PGF2α was associated with a 0.17, 0.15, or 0.23 mmol/L increase in FPG, respectively (P and/or P trend < 0.05). Each 1% increase in AAMA, GAMA, or UAAM was associated with a 0.19%, 0.27%, or 0.22% increase in 8-OHdG, respectively, and a 0.40%, 0.48%, or 0.44% increase in 8-iso-PGF2α, respectively (P and P trend < 0.05). Increased 8-iso-PGF2α rather than 8-OHdG significantly mediated 64.29% and 76.92% of the AAMA- and UAAM-associated FPG increases, respectively.

Exposure of the general adult population to acrylamide was associated with FPG elevation, oxidative DNA damage, and lipid peroxidation, which in turn partly mediated acrylamide-associated FPG elevation.

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.

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 association between CD34⁺ cell migration and cardiovascular mortality was reassessed at 6 years after revascularization. In a new series of T2D-CLI and control subjects, immuno-sorted bone marrow CD34⁺ cells were profiled for miRNA expression and assessed for apoptosis and angiogenesis activity. The differentially regulated miRNA-21 and its proapoptotic target, PDCD4, were titrated to verify their contribution in transferring damaging signals from CD34⁺ cells to endothelial cells.

Multivariable regression analysis confirmed that CD34⁺ cell migration forecasts long-term cardiovascular mortality. CD34⁺ cells from T2D-CLI patients were more apoptotic and less proangiogenic than control subjects and featured miRNA-21 downregulation, modulation of several long noncoding RNAs acting as miRNA-21 sponges, and upregulation of the miRNA-21 proapoptotic target PDCD4. Silencing miR-21 in control subject CD34⁺ cells phenocopied the T2D-CLI cell behavior. In coculture, T2D-CLI CD34⁺ cells imprinted naïve endothelial cells, increasing apoptosis, reducing network formation, and modulating the TUG1 sponge/miRNA-21/PDCD4 axis. Silencing PDCD4 or scavenging reactive oxygen species protected endothelial cells from the negative influence of T2D-CLI CD34⁺ cells.

Migration of CD34⁺ cells predicts long-term cardiovascular mortality in T2D-CLI patients. An altered paracrine signaling conveys antiangiogenic and proapoptotic features from CD34⁺ cells to the endothelium. This damaging interaction may increase the risk for life-threatening complications.

Blood, medical history, and personal data were collected in a substudy of 888 participants in the Sleep Apnea Cardiovascular End Points (SAVE) trial in which patients with OSA and stable CVD were randomized to receive CPAP plus usual care, or usual care alone. Serum glucose and glycated hemoglobin A_1c (HbA_1c) were measured at baseline, 6 months, and 2 and 4 years and incident diabetes diagnoses recorded.

Median follow-up was 4.3 years. In those with preexisting diabetes (n = 274), there was no significant difference between the CPAP and usual care groups in serum glucose, HbA_1c, or antidiabetic medications during follow-up. There were also no significant between-group differences in participants with prediabetes (n = 452) or in new diagnoses of diabetes. Interaction testing suggested that women with diabetes did poorly in the usual care group, while their counterparts on CPAP therapy remained stable.

Among patients with established CVD and OSA, we found no evidence that CPAP therapy over several years affects glycemic control in those with diabetes or prediabetes or diabetes risk over standard-of-care treatment. The potential differential effect according to sex deserves further investigation.

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.