We included 27 participants with a history of TNDM currently with (n = 24) or without (n = 3) relapse of diabetes, and 16 non-TNDM relatives known to be carriers of causal genetic defects and currently with (n = 9) or without (n = 7) diabetes. Insulin sensitivity and secretion were assessed by hyperinsulinemic-euglycemic clamp and arginine-stimulation testing in a subset of 8 TNDM participants and 7 relatives carrying genetic abnormalities, with and without diabetes, compared with 17 unrelated control subjects without diabetes.

In TNDM participants, age at relapse correlated positively with age at puberty (P = 0.019). The mean insulin secretion rate and acute insulin response to arginine were significantly lower in TNDM and relatives of participants with diabetes than in control subjects (4.7 [3.6–5.9] vs. 13.4 [11.8–16.1] pmol/kg/min, P < 0.0001; and 84.4 [33.0–178.8] vs. 399.6 [222.9–514.9] µIU/mL, P = 0.0011), but were not different between participants without diabetes (12.7 [10.4–14.3] pmol/kg/min and 396.3 [303.3–559.3] µIU/mL, respectively) and control subjects. Socioeducational attainment was lower in TNDM participants than in the general population, regardless of diabetes duration.

Relapse of diabetes occurred earlier in TNDM participants compared with relatives and was associated with puberty. Both groups had decreased educational attainment, and those with diabetes had lower insulin secretion capacity; however, there was no difference in insulin resistance in adulthood. These forms of diabetes should be included in maturity-onset diabetes of the young testing panels, and relatives of TNDM patients should be screened for underlying defects, as they may be treated with drugs other than insulin.

A total of 21 exons and exon-intron boundaries of ATP7B were identified by Sanger sequencing.

Two novel compound heterozygous mutations (c.525 dupA/ Val176Serfs*28 and c.2930 C>T/ p.Thr977Met) were detected in ATP7B. After d-penicillamine (D-PCA) therapy, serum aminotransferase and ceruloplasmin levels in this patient were normalized and levels of HbA_1c decreased. However, when the patient ceased to use D-PCA due to an itchy skin, serum levels of fasting blood glucose increased. Dimercaptosuccinic acid capsules were prescribed and memory recovered to some extent, which was accompanied by decreased insulin dosage for glucose control by 5 units.

This is the first report of diabetes caused by WD.

We included 2,236 adults aged ≥65 years without known diabetes from the 2005–2016 National Health and Nutrition Examination Survey. Diabetes was defined using: 1) the Endocrine Society approach (HbA_1c ≥6.5%, FPG ≥126 mg/dL, or 2-h plasma glucose ≥200 mg/dL among those with HbA_1c 5.7–6.4% or FPG 100–125 mg/dL); and 2) a standard approach (HbA_1c ≥6.5% or FPG ≥126 mg/dL). Treatment eligibility was defined using HbA_1c cut points (≥7 to ≥9%). OGTT screening costs were estimated using Medicare fee schedules.

Diabetes prevalence was 15.7% (~5.0 million) using the Endocrine Society’s approach and 7.3% (~2.3 million) using the standard approach. Treatment eligibility ranged from 5.4 to 0.06% and 11.8–1.3% for diabetes cases identified through the Endocrine Society or standard approach, respectively. By definition, diabetes identified exclusively through the Endocrine Society approach had HbA1_1c <6.5% and would not be recommended for glucose-lowering treatment. Screening all older adults with prediabetic HbA_1c/FPG (~18.3 million) with OGTT could cost between $737 million and $1.7 billion.

Adopting the 2019 Endocrine Society guidelines would substantially increase the number of older adults classified as having diabetes, require significant financial resources, but likely offer limited benefits.

We report the resource utilization, costs, and effectiveness measures from the ongoing ASK program compared with usual care (i.e., no screening). Additionally, we report a practical screening scenario by including utilization and costs relevant to routine screening in clinical practice. Finally, we project the potential cost-effectiveness of ASK and routine screening by identifying clinical benchmarks (i.e., diabetic ketoacidosis [DKA] events avoided, HbA_1c improvements vs. no screening) needed to meet value thresholds of $50,000–$150,000 per quality-adjusted life-year (QALY) gained over a lifetime horizon.

Cost per case detected was $4,700 for ASK screening and $14,000 for routine screening. To achieve value thresholds of $50,000–$150,000 per QALY gained, screening costs would need to be offset by cost savings through 20% reductions in DKA events at diagnosis in addition to 0.1% (1.1 mmol/mol) improvements in HbA_1c over a lifetime compared with no screening for patients who develop type 1 diabetes. Value thresholds were not met from avoiding DKA events alone in either scenario.

Presymptomatic type 1 diabetes screening may be cost-effective in areas with a high prevalence of DKA and an infrastructure facilitating screening and monitoring if the benefits of avoiding DKA events and improved HbA_1c persist over long-run time horizons. As more data are collected from ASK, the model will be updated with direct evidence on screening effects.

We thoroughly characterized 6,726 patients with recently diagnosed diabetes. After a median of 2.8 years, we sent a detailed questionnaire on neuropathy, including the Michigan Neuropathy Screening Instrument questionnaire (MNSIq), to identify possible DPN (score ≥4) and the Douleur Neuropathique en 4 Questions (DN4) questionnaire for possible associated neuropathic pain (MNSIq ≥4 + pain in both feet + DN4 score ≥3).

Among 5,249 patients with data on both DPN and pain, 17.9% (n = 938) had possible DPN, including 7.4% (n = 386) with possible neuropathic pain. In regression analyses, central obesity (waist circumference, waist-to-hip ratio, and waist-to-height ratio) was markedly associated with DPN. Other important metabolic factors associated with DPN included hypertriglyceridemia ≥1.7 mmol/L, adjusted prevalence ratio (aPR) 1.36 (95% CI 1.17; 1.59); decreased HDL cholesterol <1.0/1.2 mmol/L (male/female), aPR 1.35 (95% CI 1.12; 1.62); hs-CRP ≥3.0 mg/L, aPR 1.66 (95% CI 1.42; 1.94); C-peptide ≥1,550 pmol/L, aPR 1.72 (95% CI 1.43; 2.07); HbA_1c ≥78 mmol/mol, aPR 1.42 (95% CI 1.06; 1.88); and antihypertensive drug use, aPR 1.34 (95% CI 1.16; 1.55). Smoking, aPR 1.50 (95% CI 1.24; 1.81), and lack of physical activity (0 vs. ≥3 days/week), aPR 1.61 (95% CI 1.39; 1.85), were also associated with DPN. Smoking, high alcohol intake, and failure to increase activity after diabetes diagnosis associated with neuropathic pain.

Possible DPN was associated with metabolic syndrome factors, insulin resistance, inflammation, and modifiable lifestyle habits in early type 2 diabetes.

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.

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.

A nationwide, population-based study evaluated 1,462,362 adolescents (59% men, mean age 17.4 years) during 1996–2016. Data were linked to the Israeli National Diabetes Registry. Weight and height were measured at study entry. Cox proportional models were applied.

During 15,810,751 person-years, 2,177 people (69% men) developed T2D (mean age at diagnosis 27 years). There was an interaction among BMI, sex, and incident T2D (P_interaction = 0.023). In a model adjusted for sociodemographic variables, the hazard ratios for diabetes diagnosis were 1.7 (95% CI 1.4–2.0), 2.8 (2.3–3.5), 5.8 (4.9–6.9), 13.4 (11.5–15.7), and 25.8 (21.0–31.6) among men in the 50th–74th percentile, 75th–84th percentile, overweight, mild obesity, and severe obesity groups, respectively, and 2.2 (1.6–2.9), 3.4 (2.5–4.6), 10.6 (8.3–13.6), 21.1 (16.0–27.8), and 44.7 (32.4–61.5), respectively, in women. An inverse graded relationship was observed between baseline BMI and mean age of T2D diagnosis: 27.8 and 25.9 years among men and women with severe obesity, respectively, and 29.5 and 28.5 years among low-normal BMI (5th–49th percentile; reference), respectively. The projected fractions of adult-onset T2D that were attributed to high BMI (≥85th percentile) at adolescence were 56.9% (53.8–59.9%) and 61.1% (56.8–65.2%) in men and women, respectively.

Severe obesity significantly increases the risk for incidence of T2D in early adulthood in both sexes. The rise in adolescent severe obesity is likely to increase diabetes incidence in young adults in coming decades.

Asymptomatic patients (8–45 years) were screened for CD. Biopsy-confirmed CD participants were randomized to GFD or gluten-containing diet (GCD) to assess changes in HbA_1c and continuous glucose monitoring over 12 months.

Adults had higher CD-seropositivity rates than children (6.8% [95% CI 4.9–8.2%, N = 1,298] vs. 4.7% [95% CI 3.4–5.9%, N = 1,089], P = 0.035) with lower rates of prior CD screening (6.9% vs. 44.2%, P < 0.0001). Fifty-one participants were randomized to a GFD (N = 27) or GCD (N = 24). No HbA_1c differences were seen between the groups (+0.14%, 1.5 mmol/mol; 95% CI –0.79 to 1.08; P = 0.76), although greater postprandial glucose increases (4-h +1.5 mmol/L; 95% CI 0.4–2.7; P = 0.014) emerged with a GFD.

CD is frequently observed in asymptomatic patients with type 1 diabetes, and clinical vigilance is warranted with initiation of a GFD.

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.

All pregnant women in the Australian Capital Territory (ACT) are recommended for GDM testing with a 75-g OGTT using the World Health Organization diagnostic criteria. From January 2015 to May 2017, OGTT samples were collected into sodium fluoride (NaF) tubes and kept at room temperature until completion of the test (delayed centrifugation). From June 2017 to October 2018, OGTT samples in NaF tubes were centrifuged within 10 min (early centrifugation).

A total of 7,509 women were tested with the delayed centrifugation protocol and 4,808 with the early centrifugation protocol. The mean glucose concentrations for the fasting, 1-h and 2-h OGTT samples were, respectively, 0.24 mmol/L (5.4%), 0.34 mmol/L (4.9%), and 0.16 mmol/L (2.3%) higher using the early centrifugation protocol (P < 0.0001 for all), increasing the GDM diagnosis rate from 11.6% (n = 869/7,509) to 20.6% (n = 1,007/4,887).

The findings of this study highlight the critical importance of the preanalytical processing protocol of OGTT blood samples used for diagnosing GDM. Delay in centrifuging of blood collected into NaF tubes will result in substantially lower rates of diagnosis than if blood is centrifuged early.

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.

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.

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.

We prospectively enrolled 3,681 patients with suspected AMI and stratified those by the presence of DM. The ESC 0/1-h and 0/3-h algorithms were used to calculate negative and positive predictive values (NPV, PPV). In addition, alternative cutoffs were calculated and externally validated in 2,895 patients.

In total, 563 patients (15.3%) had DM, and 137 (24.3%) of these had AMI. When the ESC 0/1-h algorithm was used, the NPV was comparable in patients with and without DM (absolute difference [AD] –1.50 [95% CI –5.95, 2.96]). In contrast, the ESC 0/3-h algorithm resulted in a significantly lower NPV in patients with DM (AD –2.27 [95% CI –4.47, –0.07]). The diagnostic performance for rule-in of AMI (PPV) was comparable in both groups: 0/1-h (AD 6.59 [95% CI –19.53, 6.35]) and 0/3-h (AD 1.03 [95% CI –7.63, 9.7]). Alternative cutoffs increased the PPV in both algorithms significantly, while improvements in NPV were only subtle.

Application of the ESC 0/1-h algorithm revealed comparable safety to rule out AMI comparing patients with and without DM, while this was not observed with the ESC 0/3-h algorithm. Although alternative cutoffs might be helpful, patients with DM remain a high-risk population in whom identification of AMI is challenging and who require careful clinical evaluation.

Of 20,418 individuals who underwent single-photon emission computed tomography myocardial perfusion imaging, 2,951 patients with diabetes were matched to 2,951 patients without diabetes based on risk factors using propensity score. TPD was categorized as TPD = 0%, 0% < TPD < 1%, 1% ≤ TPD < 5%, 5% ≤ TPD ≤ 10%, and TPD >10%. Major adverse cardiovascular events (MACE) were defined as a composite of all-cause mortality, myocardial infarction, unstable angina, or late revascularization.

MACE risk was increased in patients with diabetes compared with patients without diabetes at each level of TPD above 0 (P < 0.001 for interaction). In patients with TPD >10%, patients with diabetes had greater than twice the MACE risk compared with patients without diabetes (annualized MACE rate 9.4 [95% CI 6.7–11.6] and 3.9 [95% CI 2.8–5.6], respectively, P < 0.001). Patients with diabetes with even very minimal TPD (0% < TPD < 1%) experienced a higher risk for MACE than those with 0% TPD (hazard ratio 2.05 [95% CI 1.21–3.47], P = 0.007). Patients with diabetes with a TPD of 0.5% had a similar MACE risk as patients without diabetes with a TPD of 8%.

For every level of TPD >0%, even a very minimal deficit of 0% < TPD < 1%, the MACE risk was higher in the patients with diabetes compared with patients without diabetes. Patients with diabetes with minimal ischemia had comparable MACE risk as patients without diabetes with significant ischemia.

UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes.

Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0–47.9 mmol/mol [6.0–6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69–1.97) and 2.26 (95% CI 1.96–2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03–1.20) and 1.20 (1.04–1.38), respectively. Adding HbA_1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001–0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models.

The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA_1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

This retrospective cohort study analyzed patients from Tayside and Fife in the Scottish Care Information–Diabetes Collaboration (SCI-DC) who were observable from the diagnosis of diabetes and had at least five HbA_1c measurements before the outcomes were evaluated. We used the previously reported HbA_1c variability score (HVS), calculated as the percentage of the number of changes in HbA_1c >0.5% (5.5 mmol/mol) among all HbA_1c measurements within an individual. The association between HVS and 10 outcomes was assessed using Cox proportional hazards models.

We included 13,111–19,883 patients in the analyses of each outcome. The patients with HVS >60% were associated with elevated risks of all outcomes compared with the lowest quintile (for example, HVS >80 to ≤100 vs. HVS ≥0 to ≤20, hazard ratio 2.38 [95% CI 1.61–3.53] for major adverse cardiovascular events, 2.4 [1.72–3.33] for all-cause mortality, 2.4 [1.13–5.11] for atherosclerotic cardiovascular death, 2.63 [1.81–3.84] for coronary artery disease, 2.04 [1.12–3.73] for ischemic stroke, 3.23 [1.76–5.93] for heart failure, 7.4 [3.84–14.27] for diabetic retinopathy, 3.07 [2.23–4.22] for diabetic peripheral neuropathy, 5.24 [2.61–10.49] for diabetic foot ulcer, and 3.49 [2.47–4.95] for new-onset chronic kidney disease). Four sensitivity analyses, including adjustment for time-weighted average HbA_1c, confirmed the robustness of the results.

Our study shows that higher HbA_1c variability is associated with increased risks of all-cause mortality, cardiovascular events, and microvascular complications of diabetes independently of high HbA_1c.

We performed a cross-sectional study in severely obese individuals before bariatric surgery. Lean control subjects were recruited from a research website. Cognitive deficits were defined by the National Institutes of Health (NIH) Toolbox (<5th percentile for lean control subjects). Cardiovascular autonomic neuropathy (CAN) was defined by an expiration-to-inspiration (E-to-I) ratio of <5th percentile for lean control subjects. Retinopathy was based on retinal photographs and nephropathy on the estimated glomerular filtration rate (<60 mg/dL) and/or the albumin-to-creatinine ratio (ACR) (≥30 mg/g). NIH Toolbox, E-to-I ratio, mean deviation on frequency doubling technology testing, and ACR were used as sensitive measures of these outcomes. We used multivariable linear regression to explore associations between metabolic factors and these outcomes.

We recruited 138 severely obese individuals and 46 lean control subjects. The prevalence of cognitive deficits, CAN, retinopathy, and nephropathy were 6.5%, 4.4%, 0%, and 6.5% in lean control subjects; 22.2%, 18.2%, 0%, and 6.1% in obese participants with normoglycemia; 17.7%, 21.4%, 1.9%, and 17.9% in obese participants with prediabetes; and 25.6%, 31.9%, 6.1%, and 16.3% in obese participants with diabetes. Waist circumference was significantly associated with cognitive function (–1.48; 95% CI –2.38, –0.57) and E-to-I ratio (–0.007; 95% CI –0.012, –0.002). Prediabetes was significantly associated with retinal function (–1.78; 95% CI –3.56, –0.002).

Obesity alone is likely sufficient to cause cognitive deficits but not retinopathy or nephropathy. Central obesity is the key metabolic risk factor.

We identified 8,528 patients with diabetes (self-report, medication use, or electronic medical record diagnosis) from the Henry Ford Exercise Testing Project (FIT Project). Patients with a BMI <18.5 kg/m² or cancer were excluded. Fitness was measured as the METs achieved during a physician-referred treadmill stress test and categorized as low (<6), moderate (6–9.9), or high (≥10). Adjusted hazard ratios for mortality were calculated using standard BMI (kilograms per meter squared) cutoffs of normal (18.5–24.9), overweight (25–29.9), and obese (≥30). Adjusted splines centered at 22.5 kg/m² were used to examine BMI as a continuous variable.

Patients had a mean age of 58 ± 11 years (49% women) with 1,319 deaths over a mean follow-up of 10.0 ± 4.1 years. Overall, obese patients had a 30% lower mortality hazard (P < 0.001) compared with normal-weight patients. In adjusted spline modeling, higher BMI as a continuous variable was predominantly associated with a lower mortality risk in the lowest fitness group and among patients with moderate fitness and BMI ≥30 kg/m². Compared with the lowest fitness group, patients with higher fitness had an ~50% (6–9.9 METs) and 70% (≥10 METs) lower mortality hazard regardless of BMI (P < 0.001).

Among patients with diabetes, the obesity paradox was less pronounced for patients with the highest fitness level, and these patients also had the lowest risk of mortality.

EarlyBird is a nonintervention prospective cohort study that recruited 307 healthy U.K. children at 5 years of age and followed them throughout childhood. We genotyped 121 single nucleotide polymorphisms (SNPs) previously associated with diabetes risk, identified in the adult population. Association of SNPs with fasting insulin and glucose and HOMA indices of insulin resistance and β-cell function, available from 5 to 16 years of age, were tested. Association analysis with hormones was performed on selected SNPs.

Several candidate loci influenced the course of glycemic and insulin traits, including rs780094 (GCKR), rs4457053 (ZBED3), rs11257655 (CDC123), rs12779790 (CDC123 and CAMK1D), rs1111875 (HHEX), rs7178572 (HMG20A), rs9787485 (NRG3), and rs1535500 (KCNK16). Some of these SNPs interacted with age, the growth hormone–IGF-1 axis, and adrenal and sex steroid activity.

The findings that genetic markers influence both elevated and average courses of glycemic traits and β-cell function in children during puberty independently of BMI are a significant step toward early identification of children at risk for diabetes. These findings build on our previous observations that pancreatic β-cell defects predate insulin resistance in the onset of prediabetes. Understanding the mechanisms of interactions among genetic factors, puberty, and weight gain would allow the development of new and earlier disease-management strategies in children.

In a post hoc analysis of 14,752 Exenatide Study of Cardiovascular Event Lowering (EXSCEL) participants, we examined time-dependent associations between SHEs and subsequent major adverse cardiac events (CV death, nonfatal myocardial infarction [MI] or stroke), fatal/nonfatal MI, fatal/nonfatal stroke, hospitalization for acute coronary syndrome (hACS), hospitalization for heart failure (hHF), and all-cause mortality (ACM), as well as time-dependent associations between nonfatal CV events and subsequent SHEs.

SHEs were uncommon and not associated with once-weekly exenatide therapy (hazard ratio 1.13 [95% CI 0.94–1.36], P = 0.179). In fully adjusted models, SHEs were associated with an increased risk of subsequent ACM (1.83 [1.38–2.42], P < 0.001), CV death (1.60 [1.11–2.30], P = 0.012), and hHF (2.09 [1.37–3.17], P = 0.001), while nonfatal MI (2.02 [1.35–3.01], P = 0.001), nonfatal stroke (2.30 [1.25–4.23], P = 0.007), hACS (2.00 [1.39–2.90], P < 0.001), and hHF (3.24 [1.98–5.30], P < 0.001) were all associated with a subsequent increased risk of SHEs. The elevated bidirectional time-dependent hazards linking SHEs and a composite of all CV events were approximately constant over time, with those individuals at dual risk showing higher comorbidity scores compared with those without.

These findings, showing greater risk of SHEs after CV events as well as greater risk of CV events after SHEs, validate a bidirectional relationship between CV events and SHEs in patients with high comorbidity scores.

In this large-scale retrospective cohort study in Japan, new users of antidepressants (exposure group) and nonusers (nonexposure group), aged 20–79 years, were included between 1 April 2006 and 31 May 2015. Patients with a history of diabetes or receipt of antidiabetes treatment were excluded. Covariates were adjusted by using propensity score matching; the associations were analyzed between risk of new-onset type 2 diabetes and the duration of antidepressant use/dose of antidepressant in the exposure and nonexposure groups by using Cox proportional hazards models. Changes in glycated hemoglobin (HbA_1c) level were examined in groups with continuous use, discontinuation, or a reduction in the dose of antidepressants.

Of 90,530 subjects, 45,265 were in both the exposure and the nonexposure group after propensity score matching; 5,225 patients (5.8%) developed diabetes. Antidepressant use was associated with the risk of diabetes onset in a time- and dose-dependent manner. The adjusted hazard ratio was 1.27 (95% CI 1.16–1.39) for short-term low-dose and 3.95 (95% CI 3.31–4.72) for long-term high-dose antidepressant use. HbA_1c levels were lower in patients who discontinued or reduced the dose of antidepressants (F[2,49] = 8.17; P < 0.001).

Long-term antidepressant use increased the risk of type 2 diabetes onset in a time- and dose-dependent manner. Glucose tolerance improved when antidepressants were discontinued or the dose was reduced after diabetes onset.

Five cohort studies’ participants (n = 8,270) were classified as statin users when they were on statin therapy at the time of DNAm assessment with Illumina 450K or EPIC array or noncurrent users otherwise. Associations of DNAm with various outcomes like incident type 2 diabetes, plasma glucose, insulin, and insulin resistance (HOMA of insulin resistance [HOMA-IR]) as well as with gene expression were investigated.

Discovery (n = 6,820) and replication (n = 1,450) phases associated five DNAm sites with statin use: cg17901584 (1.12 x 10^–25 [DHCR24]), cg10177197 (3.94 x 10^–08 [DHCR24]), cg06500161 (2.67 x 10^–23 [ABCG1]), cg27243685 (6.01 x 10^–09 [ABCG1]), and cg05119988 (7.26 x 10^–12 [SC4MOL]). Two sites were associated with at least one glycemic trait or type 2 diabetes. Higher cg06500161 methylation was associated with higher fasting glucose, insulin, HOMA-IR, and type 2 diabetes (odds ratio 1.34 [95% CI 1.22, 1.47]). Mediation analyses suggested that ABCG1 methylation partially mediates the effect of statins on high insulin and HOMA-IR. Gene expression analyses showed that statin exposure and ABCG1 methylation were associated with ABCG1 downregulation, suggesting epigenetic regulation of ABCG1 expression. Further, outcomes insulin and HOMA-IR were significantly associated with ABCG1 expression.

This study sheds light on potential mechanisms linking statins with type 2 diabetes risk, providing evidence on DNAm partially mediating statins’ effects on insulin traits. Further efforts shall disentangle the molecular mechanisms through which statins may induce DNAm changes, potentially leading to ABCG1 epigenetic regulation.

CVD events in the 1,441 DCCT/EDIC participants were analyzed separately by type (CVD death, acute myocardial infarction [MI], stroke, silent MI, angina, percutaneous transluminal coronary angioplasty/coronary artery bypass graft [PTCA/CABG], and congestive heart failure [CHF]) or as composite outcomes (CVD or major adverse cardiovascular events [MACE]). Proportional rate models and conditional models assessed associations between risk factors and CVD outcomes.

Over a median follow-up of 29 years, 239 participants had 421 CVD events, and 120 individuals had 149 MACE. Age was the strongest risk factor for acute MI, silent MI, stroke, and PTCA/CABG, while glycemia was the strongest risk factor for CVD death, CHF, and angina, second strongest for acute MI and PTCA/CABG, third strongest for stroke, and not associated with silent MI. HbA_1c was the strongest modifiable risk factor for a first CVD event (CVD: HR 1.38 [95% CI 1.21, 1.56] per 1% higher HbA_1c; MACE: HR 1.54 [1.30, 1.82]) and also for subsequent CVD events (CVD: incidence ratio [IR] 1.28 [95% CI 1.09, 1.51]; MACE: IR 1.89 [1.36, 2.61]).

Intensive glycemic management is recommended to lower the risk of initial CVD events in T1D. After a first event, optimal glycemic control may reduce the risk of recurrent CVD events and should be maintained.

A total of 2,287 patients with type 2 diabetes who underwent metabolic surgery between 1998 and 2017 in the Cleveland Clinic Health System were propensity-matched 1:5 to 11,435 nonsurgical patients with BMI ≥30 kg/m² and type 2 diabetes who received usual care with follow-up through December 2018. Multivariable time-to-event regression and random forest machine learning models were built and internally validated using fivefold cross-validation to predict the 10-year risk for four outcomes of interest. The prediction models were programmed to construct user-friendly web-based and smartphone applications of Individualized Diabetes Complications (IDC) Risk Scores for clinical use.

The prediction tools demonstrated the following discrimination ability based on the area under the receiver operating characteristic curve (1 = perfect discrimination and 0.5 = chance) at 10 years in the surgical and nonsurgical groups, respectively: all-cause mortality (0.79 and 0.81), coronary artery events (0.66 and 0.67), heart failure (0.73 and 0.75), and nephropathy (0.73 and 0.76). When a patient’s data are entered into the IDC application, it estimates the individualized 10-year morbidity and mortality risks with and without undergoing metabolic surgery.

The IDC Risk Scores can provide personalized evidence-based risk information for patients with type 2 diabetes and obesity about future cardiovascular outcomes and mortality with and without metabolic surgery based on their current status of obesity, diabetes, and related cardiometabolic conditions.

In CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation—a cohort of 528 individuals with no previous cardiovascular event undergoing CCTA), participants were grouped into CAD^– (clean coronaries) and CAD⁺ (diffuse lumen narrowing or plaques). Plasma proteins were screened by aptamer analysis. Two-way partial least squares was used to simultaneously rank proteins by diabetes status and CAD.

Though CAD⁺ was more prevalent among participants with T2D (HbA_1c 6.7 ± 1.1%) than those without diabetes (56 vs. 30%, P < 0.0001), CCTA-based atherosclerosis burden did not differ. Of the 20 top-ranking proteins, 15 were associated with both T2D and CAD, and 3 (osteomodulin, cartilage intermediate-layer protein 15, and HTRA1) were selectively associated with T2D only and 2 (epidermal growth factor receptor and contactin-1) with CAD only. Elevated renin and GDF15, and lower adiponectin, were independently associated with both T2D and CAD. In multivariate analysis adjusting for the Framingham risk panel, patients with T2D were "protected" from CAD if female (P = 0.007), younger (P = 0.021), and with lower renin levels (P = 0.02).

We concluded that 1) CAD severity and quality do not differ between participants with T2D and without diabetes; 2) renin, GDF15, and adiponectin are shared markers by T2D and CAD; 3) several proteins are specifically associated with T2D or CAD; and 4) in T2D, lower renin levels may protect against CAD.

A total of 24 T1D patients (median age 5.1 years) received a single intravenous infusion of autologous UCB cells and underwent metabolic and immunologic assessments.

No infusion-related adverse events were observed. β-Cell function declined after UCB infusion. Area under the curve C-peptide was 24.3% of baseline 1 year postinfusion (P < 0.001) and 2% of baseline 2 years after infusion (P < 0.001). Flow cytometry revealed increased regulatory T cells (Tregs) (P = 0.04) and naive Tregs (P = 0.001) 6 and 9 months after infusion, respectively.

Autologous UCB infusion in children with T1D is safe and induces changes in Treg frequency but fails to preserve C-peptide.

In this double-blind study, 587 patients taking stable-dose insulin glargine (±metformin ≥1,500 mg/day) were randomized (1:1:1:1:1) to MK-0941 10, 20, 30, or 40 mg or matching placebo t.i.d. before meals (a.c.). This study included an initial 14-week, dose-ranging phase followed by a 40-week treatment phase during which patients were to be uptitrated as tolerated to 40 mg (or placebo) t.i.d. a.c. The primary efficacy end point was change from baseline in A1C at Week 14.

At Week 14, A1C and 2-h postmeal glucose (PMG) improved significantly versus placebo with all MK-0941 doses. Maximal placebo-adjusted least squares mean changes from baseline in A1C (baseline A1C 9.0%) and 2-h PMG were –0.8% and –37 mg/dL (–2 mmol/L), respectively. No significant effects on fasting plasma glucose were observed at any dose versus placebo. By 30 weeks, the initial glycemic responses noted at 14 weeks were not sustained. MK-0941 at one or more doses was associated with significant increases in the incidence of hypoglycemia, triglycerides, systolic blood pressure, and proportion of patients meeting criteria for predefined limits of change for increased diastolic blood pressure.

In patients receiving stable-dose insulin glargine, the GKA MK-0941 led to improvements in glycemic control that were not sustained. MK-0941 was associated with an increased incidence of hypoglycemia and elevations in triglycerides and blood pressure.