The transcriptional regulators IRF4, BATF and IL-33 orchestrate development and maintenance of adipose tissue-resident regulatory T cells.

Foxp3(+) regulatory T (Treg) cells in visceral adipose tissue (VAT-Treg cells) are functionally specialized tissue-resident cells that prevent obesity-associated inflammation and preserve insulin sensitivity and glucose tolerance. Their development depends on the transcription factor PPAR-γ; however, the environmental cues required for their differentiation are unknown. Here we show that interleukin 33 (IL-33) signaling through the IL-33 receptor ST2 and myeloid differentiation factor MyD88 is essential for development and maintenance of VAT-Treg cells and sustains their transcriptional signature. Furthermore, the transcriptional regulators BATF and IRF4 were necessary for VAT-Treg differentiation through direct regulation of ST2 and PPAR-γ expression. IL-33 administration induced vigorous population expansion of VAT-Treg cells, which tightly correlated with improvements in metabolic parameters in obese mice. Human omental adipose tissue Treg cells also showed high ST2 expression, suggesting an evolutionarily conserved requirement for IL-33 in VAT-Treg cell homeostasis.

Baricitinib and ß-Cell Function in Patients with New-Onset Type 1 Diabetes.

BACKGROUND: Janus kinase (JAK) inhibitors, including baricitinib, block cytokine signaling and are effective disease-modifying treatments for several autoimmune diseases. Whether baricitinib preserves ß-cell function in type 1 diabetes is unclear. METHODS: In this phase 2, double-blind, randomized, placebo-controlled trial, we assigned patients with type 1 diabetes diagnosed during the previous 100 days to receive baricitinib (4 mg once per day) or matched placebo orally for 48 weeks. The primary outcome was the mean C-peptide level, determined from the area under the concentration-time curve, during a 2-hour mixed-meal tolerance test at week 48. Secondary outcomes included the change from baseline in the glycated hemoglobin level, the daily insulin dose, and measures of glycemic control assessed with the use of continuous glucose monitoring. RESULTS: A total of 91 patients received baricitinib (60 patients) or placebo (31 patients). The median of the mixed-meal-stimulated mean C-peptide level at week 48 was 0.65 nmol per liter per minute (interquartile range, 0.31 to 0.82) in the baricitinib group and 0.43 nmol per liter per minute (interquartile range, 0.13 to 0.63) in the placebo group (P = 0.001). The mean daily insulin dose at 48 weeks was 0.41 U per kilogram of body weight per day (95% confidence interval [CI], 0.35 to 0.48) in the baricitinib group and 0.52 U per kilogram per day (95% CI, 0.44 to 0.60) in the placebo group. The levels of glycated hemoglobin were similar in the two trial groups. However, the mean coefficient of variation of the glucose level at 48 weeks, as measured by continuous glucose monitoring, was 29.6% (95% CI, 27.8 to 31.3) in the baricitinib group and 33.8% (95% CI, 31.5 to 36.2) in the placebo group. The frequency and severity of adverse events were similar in the two trial groups, and no serious adverse events were attributed to baricitinib or placebo. CONCLUSIONS: In patients with type 1 diabetes of recent onset, daily treatment with baricitinib over 48 weeks appeared to preserve ß-cell function as estimated by the mixed-meal-stimulated mean C-peptide level. (Funded by JDRF International and others; BANDIT Australian New Zealand Clinical Trials Registry number, ACTRN12620000239965.).

Dietary patterns during pregnancy and maternal and birth outcomes in women with type 1 diabetes: the Environmental Determinants of Islet Autoimmunity (ENDIA) study.

AIMS/HYPOTHESIS: Dietary patterns characterised by high intakes of vegetables may lower the risk of pre-eclampsia and premature birth in the general population. The effect of dietary patterns in women with type 1 diabetes, who have an increased risk of complications in pregnancy, is not known. The aim of this study was to investigate the relationship between dietary patterns and physical activity during pregnancy and maternal complications and birth outcomes in women with type 1 diabetes. We also compared dietary patterns in women with and without type 1 diabetes. METHODS: Diet was assessed in the third trimester using a validated food frequency questionnaire in participants followed prospectively in the multi-centre Environmental Determinants of Islet Autoimmunity (ENDIA) study. Dietary patterns were characterised by principal component analysis. The Pregnancy Physical Activity Questionnaire was completed in each trimester. Data for maternal and birth outcomes were collected prospectively. RESULTS: Questionnaires were completed by 973 participants during 1124 pregnancies. Women with type 1 diabetes (n=615 pregnancies with dietary data) were more likely to have a 'fresh food' dietary pattern than women without type 1 diabetes (OR 1.19, 95% CI 1.07, 1.31; p=0.001). In women with type 1 diabetes, an increase equivalent to a change from quartile 1 to 3 in 'fresh food' dietary pattern score was associated with a lower risk of pre-eclampsia (OR 0.37, 95% CI 0.17, 0.78; p=0.01) and premature birth (OR 0.35, 95% CI 0.20, 0.62, p<0.001). These associations were mediated in part by BMI and HbA1c. The 'processed food' dietary pattern was associated with an increased birthweight (ß coefficient 56.8 g, 95% CI 2.8, 110.8; p=0.04). Physical activity did not relate to outcomes. CONCLUSIONS/INTERPRETATION: A dietary pattern higher in fresh foods during pregnancy was associated with sizeable reductions in risk of pre-eclampsia and premature birth in women with type 1 diabetes.

Protocol for the Australian Type 1 Diabetes National Screening Pilot: Assessing the feasibility and acceptability of three general population screening models in children.

AIM: One third of Australian children diagnosed with type 1 diabetes present with life-threatening diabetic ketoacidosis (DKA) at diagnosis. Screening for early-stage, presymptomatic type 1 diabetes, with ongoing follow-up, can substantially reduce this risk (<5% risk). Several screening models are being trialled internationally, without consensus on the optimal approach. This pilot study aims to assess three models for a routine, population-wide screening programme in Australia. METHODS: An implementation science-guided pilot study to evaluate the feasibility, acceptability and costs of three screening models in children will be conducted between July 2022 and June 2024. These models are as follows: (1) Genetic risk-stratified screening using newborn heel prick dried bloodspots, followed by autoantibody testing from 11 months of age; (2) genetic risk-stratified screening of infant (6-12 months) saliva followed by autoantibody testing from 10 months of age; and (3) autoantibody screening using capillary dried bloodspots collected from children aged 2, 6 or 10 years. Cohorts for each model will be recruited from targeted geographic areas across Australia involving ≥2 states per cohort, with a recruitment target of up to 3000 children per cohort (total up to 9000 children). The primary outcome is screening uptake for each cohort. Secondary outcomes include programme feasibility, costs, parental anxiety, risk perception, satisfaction, well-being and quality of life, and health professional attitudes and satisfaction. CONCLUSIONS: This pilot is the first direct comparison of three screening implementation models for general population screening. Findings will provide evidence to inform a potential national screening programme for Australian children. TRIAL REGISTRATION: ACTRN12622000381785.

Continuous glucose monitoring has an increasing role in pre-symptomatic type 1 diabetes: advantages, limitations, and comparisons with laboratory-based testing.

Type 1 diabetes (T1D) is well-recognised as a continuum heralded by the development of islet autoantibodies, progression to islet autoimmunity causing beta cell destruction, culminating in insulin deficiency and clinical disease. Abnormalities of glucose homeostasis are known to exist well before the onset of typical symptoms. Laboratory-based tests such as the oral glucose tolerance test (OGTT) and glycated haemoglobin (HbA1c) have been used to stage T1D and assess the risk of progression to clinical T1D. Continuous glucose monitoring (CGM) can detect early glycaemic abnormalities and can therefore be used to monitor for metabolic deterioration in pre-symptomatic, islet autoantibody positive, at-risk individuals. Early identification of these children can not only reduce the risk of presentation with diabetic ketoacidosis (DKA), but also determine eligibility for prevention trials, which aim to prevent or delay progression to clinical T1D. Here, we describe the current state with regard to the use of the OGTT, HbA1c, fructosamine and glycated albumin in pre-symptomatic T1D. Using illustrative cases, we present our clinical experience with the use of CGM, and advocate for an increased role of this diabetes technology, for monitoring metabolic deterioration and disease progression in children with pre-symptomatic T1D.

Long-term impact of weight loss for people with overweight but not obesity, and with type 2 diabetes: 10-year outcomes of a randomized trial of gastric band surgery.

AIM: Randomized trials reporting 5-year outcomes have shown bariatric surgery  to induce diabetes remission and improve cardiovascular risk. However, the longer-term effects of surgery are uncertain, with only one randomized trial reporting 10-year diabetes outcomes in people with obesity. We aimed to compare 10-year diabetes outcomes of people who are overweight but not obese, randomly assigned to receive either multidisciplinary diabetes care, or multidisciplinary diabetes care combined with gastric band (GB) surgery. METHODS: Between 2009 and 2011, 51 adults were randomized. After 5 years, they were discharged to receive community care and reassessed after 10 years. The primary outcome was diabetes remission, defined as glycated haemoglobin (HbA1c) <6.5% (48 mmol/mol) without glucose-lowering medication. RESULTS: Forty-one participants (20 medical and 21 GB) completed the 10-year assessment. The median (Q1, Q3) weight loss in the GB group was 9.8 (6.7, 16.3)% at 10 years compared with 5.6 (3.4, 7.6)% in the medical group (median difference 4.2%; p = .008). Diabetes remission occurred in five GB participants and no medical participants (relative risk 0.76, 95% CI: 0.55-0.93, p = .048). GB participants used fewer glucose-lowering medications at 10 years but HbA1c, fasting glucose, calculated cardiovascular risk, quality-of-life and incident diabetes complications did not differ significantly between the groups. CONCLUSION: When compared with medical care, GB surgery achieved greater weight loss and modestly increased the likelihood of diabetes remission. However, it did not improve HbA1c, cardiovascular risk or quality of life.

HOMA2-B enhances assessment of type 1 diabetes risk among TrialNet Pathway to Prevention participants.

AIMS/HYPOTHESIS: Methods to identify individuals at highest risk for type 1 diabetes are essential for the successful implementation of disease-modifying interventions. Simple metabolic measures are needed to help stratify autoantibody-positive (Aab+) individuals who are at risk of developing type 1 diabetes. HOMA2-B is a validated mathematical tool commonly used to estimate beta cell function in type 2 diabetes using fasting glucose and insulin. The utility of HOMA2-B in association with type 1 diabetes progression has not been tested. METHODS: Baseline HOMA2-B values from single-Aab+ (n = 2652; mean age, 21.1 ± 14.0 years) and multiple-Aab+ (n = 3794; mean age, 14.5 ± 11.2 years) individuals enrolled in the TrialNet Pathway to Prevention study were compared. Cox proportional hazard models were used to determine associations between HOMA2-B tertiles and time to progression to type 1 diabetes, with adjustments for age, sex, HLA status and BMI z score. Receiver operating characteristic (ROC) analysis was used to test the association of HOMA2-B with type 1 diabetes development in 1, 2, 5 and 10 years. RESULTS: At study entry, HOMA2-B values were higher in single- compared with multiple-Aab+ Pathway to Prevention participants (91.1 ± 44.5 vs 83.9 ± 38.9; p < 0.001). Single- and multiple-Aab+ individuals in the lowest HOMA2-B tertile had a higher risk and faster rate of progression to type 1 diabetes. For progression to type 1 diabetes within 1 year, area under the ROC curve (AUC-ROC) was 0.685, 0.666 and 0.680 for all Aab+, single-Aab+ and multiple-Aab+ individuals, respectively. When correlation between HOMA2-B and type 1 diabetes risk was assessed in combination with additional factors known to influence type 1 diabetes progression (insulin sensitivity, age and HLA status), AUC-ROC was highest for the single-Aab+ group's risk of progression at 2 years (AUC-ROC 0.723 [95% CI 0.652, 0.794]). CONCLUSIONS/INTERPRETATION: These data suggest that HOMA2-B may have utility as a single-time-point measurement to stratify risk of type 1 diabetes development in Aab+ individuals.

Characterising the age-dependent effects of risk factors on type 1 diabetes progression.

AIMS/HYPOTHESIS: Age is known to be one of the most important stratifiers of disease progression in type 1 diabetes. However, what drives the difference in rate of progression between adults and children is poorly understood. Evidence suggests that many type 1 diabetes disease predictors do not have the same effect across the age spectrum. Without a comprehensive analysis describing the varying risk profiles of predictors over the age continuum, researchers and clinicians are susceptible to inappropriate assessment of risk when examining populations of differing ages. We aimed to systematically assess and characterise how the effect of key type 1 diabetes risk predictors changes with age. METHODS: Using longitudinal data from single- and multiple-autoantibody-positive at-risk individuals recruited between the ages of 1 and 45 years in TrialNet's Pathway to Prevention Study, we assessed and visually characterised the age-varying effect of key demographic, immune and metabolic predictors of type 1 diabetes by employing a flexible spline model. Two progression outcomes were defined: participants with single autoantibodies (n=4893) were analysed for progression to multiple autoantibodies or type 1 diabetes, and participants with multiple autoantibodies were analysed (n=3856) for progression to type 1 diabetes. RESULTS: Several predictors exhibited significant age-varying effects on disease progression. Amongst single-autoantibody participants, HLA-DR3 (p=0.007), GAD65 autoantibody positivity (p=0.008), elevated BMI (p=0.007) and HOMA-IR (p=0.002) showed a significant increase in effect on disease progression with increasing age. Insulin autoantibody positivity had a diminishing effect with older age in single-autoantibody-positive participants (p<0.001). Amongst multiple-autoantibody-positive participants, male sex (p=0.002) was associated with an increase in risk for progression, and HLA DR3/4 (p=0.05) showed a decreased effect on disease progression with older age. In both single- and multiple-autoantibody-positive individuals, significant changes in HR with age were seen for multiple measures of islet function. Risk estimation using prediction risk score Index60 was found to be better at a younger age for both single- and multiple-autoantibody-positive individuals (p=0.007 and p<0.001, respectively). No age-varying effect was seen for prediction risk score DPTRS (p=0.861 and p=0.178, respectively). Multivariable analyses suggested that incorporating the age-varying effect of the individual components of these validated risk scores has the potential to enhance the risk estimate. CONCLUSIONS/INTERPRETATION: Analysing the age-varying effect of disease predictors improves understanding and prediction of type 1 diabetes disease progression, and should be leveraged to refine prediction models and guide mechanistic studies.

Decreased occurrence of ketoacidosis and preservation of beta cell function in relatives screened and monitored for type 1 diabetes in Australia and New Zealand.

AIMS: Islet autoantibody screening of infants and young children in the Northern Hemisphere, together with semi-annual metabolic monitoring, is associated with a lower risk of ketoacidosis (DKA) and improved glucose control after diagnosis of clinical (stage 3) type 1 diabetes (T1D). We aimed to determine if similar benefits applied to older Australians and New Zealanders monitored less rigorously. METHODS: DKA occurrence and metabolic control were compared between T1D relatives screened and monitored for T1D and unscreened individuals diagnosed in the general population, ascertained from the Australasian Diabetes Data Network. RESULTS: Between 2005 and 2019, 17,105 relatives (mean (SD) age 15.7 (10.8) years; 52% female) were screened for autoantibodies against insulin, glutamic acid decarboxylase, and insulinoma-associated protein 2. Of these, 652 screened positive to a single and 306 to multiple autoantibody specificities, of whom 201 and 215, respectively, underwent metabolic monitoring. Of 178 relatives diagnosed with stage 3 T1D, 9 (5%) had DKA, 7 of whom had not undertaken metabolic monitoring. The frequency of DKA in the general population was 31%. After correction for age, sex and T1D family history, the frequency of DKA in screened relatives was >80% lower than in the general population. HbA1c and insulin requirements following diagnosis were also lower in screened relatives, consistent with greater beta cell reserve. CONCLUSIONS: T1D autoantibody screening and metabolic monitoring of older children and young adults in Australia and New Zealand, by enabling pre-clinical diagnosis when beta cell reserve is greater, confers protection from DKA. These clinical benefits support ongoing efforts to increase screening activity in the region and should facilitate the application of emerging immunotherapies.

Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample.

AIMS/HYPOTHESIS: Accurate prediction of disease progression in individuals with pre-symptomatic type 1 diabetes has potential to prevent ketoacidosis and accelerate development of disease-modifying therapies. Current tools for predicting risk require multiple blood samples taken during an OGTT. Our aim was to develop and validate a simpler tool based on a single blood draw. METHODS: Models to predict disease progression using a single OGTT time point (0, 30, 60, 90 or 120 min) were developed using TrialNet data collected from relatives with type 1 diabetes and validated in independent populations at high genetic risk of type 1 diabetes (TrialNet, Diabetes Prevention Trial-Type 1, The Environmental Determinants of Diabetes in the Young [1]) and in a general population of Bavarian children who participated in Fr1da. RESULTS: Cox proportional hazards models combining plasma glucose, C-peptide, sex, age, BMI, HbA1c and insulinoma antigen-2 autoantibody status predicted disease progression in all populations. In TrialNet, the AUC for receiver operating characteristic curves for models named M60, M90 and M120, based on sampling at 60, 90 and 120 min, was 0.760, 0.761 and 0.745, respectively. These were not significantly different from the AUC of 0.760 for the gold standard Diabetes Prevention Trial Risk Score, which requires five OGTT blood samples. In TEDDY, where only 120 min blood sampling had been performed, the M120 AUC was 0.865. In Fr1da, the M120 AUC of 0.742 was significantly greater than the M60 AUC of 0.615. CONCLUSIONS/INTERPRETATION: Prediction models based on a single OGTT blood draw accurately predict disease progression from stage 1 or 2 to stage 3 type 1 diabetes. The operational simplicity of M120, its validity across different at-risk populations and the requirement for 120 min sampling to stage type 1 diabetes suggest M120 could be readily applied to decrease the cost and complexity of risk stratification.

Associations between diet, the gut microbiome and short chain fatty acids in youth with islet autoimmunity and type 1 diabetes.

AIM: We aimed to characterize associations between diet and the gut microbiome and short chain fatty acid (SCFA) products in youth with islet autoimmunity or type 1 diabetes (IA/T1D) in comparison with controls. RESEARCH DESIGN AND METHODS: Eighty participants (25 diagnosed with T1D, 17 with confirmed IA, 38 sibling or unrelated controls) from the Australian T1D Gut Study cohort were studied (median [IQR] age 11.7 [8.9, 14.0] years, 43% female). A Food Frequency Questionnaire characterized daily macronutrient intake over the preceding 6 months. Plasma and fecal SCFA were measured by gas chromatography; gut microbiome composition and diversity by 16S rRNA gene sequencing. RESULTS: A 10 g increase in daily carbohydrate intake associated with higher plasma acetate in IA/T1D (adjusted estimate +5.2 (95% CI 1.1, 9.2) µmol/L p = 0.01) and controls (adjusted estimate +4.1 [95% CI 1.7, 8.5] µmol/L p = 0.04). A 5 g increase in total fat intake associated with lower plasma acetate in IA/T1D and controls. A 5% increase in noncore (junk) food intake associated with reduced richness (adjusted estimate -4.09 [95%CI -7.83, -0.35] p = .03) and evenness (-1.25 [95% CI -2.00, -0.49] p < 0.01) of the gut microbiome in IA/T1D. Fiber intake associated with community structure of the microbiome in IA/T1D. CONCLUSIONS: Modest increments in carbohydrate and fat intake associated with plasma acetate in all youth. Increased junk food intake associated with reduced diversity of the gut microbiome in IA/T1D alone. These associations with the gut microbiome in IA/T1D support future efforts to promote SCFA by using dietary interventions.

Factors that predict glycaemic response to sodium-glucose linked transporter (SGLT) inhibitors.

AIM: To determine the clinical and biochemical variables associated with change in HbA1c in patients with type 2 diabetes who start sodium-glucose linked transporter (SGLT) inhibitor therapy. METHODS: We performed a prospective cohort study (ACTRN12616000833460) of 48 adults (30 male, 18 female) with type 2 diabetes who attended a tertiary hospital diabetes clinic. Fasting serum and urine samples, collected during clinic visits prior to and at 1, 12 and 24 weeks after commencing SGLT inhibitor treatment, were analysed for HbA1c, electrolytes, urea, creatinine and glucose. RESULTS: After 12 weeks, SGLT inhibitor therapy was associated with respective median (97% CI) decreases in weight, blood pressure, HbA1c and urine albumin/creatinine ratio of 3.0 (1.7-3.4) kg, 8 (2-16)/4 (3-9) mmHg, 6 (3-14) mmol/mol and 0.69 (0.18-1.8) mg/mmol. These effects persisted to 24 weeks. Urinary frequency and genitourinary infection were common adverse effects. Baseline HbA1c and eGFR independently predicted ΔHbA1c at 12 weeks whereas only baseline HbA1c independently predicted ΔHbA1c at 24 weeks. Urinary fractional glucose excretion and change in fasting glucose 1 week after starting SGLT inhibitor did not contribute to prediction of glycaemic response. CONCLUSIONS: SGLT inhibitor therapy in a hospital clinic setting was associated with clinical improvements comparable to those observed in clinical trials but with higher incidence of genitourinary side-effects. Baseline HbA1c and eGFR, but not urine fractional glucose excretion, predicted glycaemic response.

Proinsulin C-peptide is an autoantigen in people with type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease in which insulin-producing beta cells, found within the islets of Langerhans in the pancreas, are destroyed by islet-infiltrating T cells. Identifying the antigenic targets of beta-cell reactive T cells is critical to gain insight into the pathogenesis of T1D and develop antigen-specific immunotherapies. Several lines of evidence indicate that insulin is an important target of T cells in T1D. Because many human islet-infiltrating CD4+ T cells recognize C-peptide-derived epitopes, we hypothesized that full-length C-peptide (PI33-63), the peptide excised from proinsulin as it is converted to insulin, is a target of CD4+ T cells in people with T1D. CD4+ T cell responses to full-length C-peptide were detected in the blood of: 14 of 23 (>60%) people with recent-onset T1D, 2 of 15 (>13%) people with long-standing T1D, and 1 of 13 (<8%) HLA-matched people without T1D. C-peptide-specific CD4+ T cell clones, isolated from six people with T1D, recognized epitopes from the entire 31 amino acids of C-peptide. Eighty-six percent (19 of 22) of the C-peptide-specific clones were restricted by HLA-DQ8, HLA-DQ2, HLA-DQ8trans, or HLA-DQ2trans, HLA alleles strongly associated with risk of T1D. We also found that full-length C-peptide was a much more potent agonist of some CD4+ T cell clones than an 18mer peptide encompassing the cognate epitope. Collectively, our findings indicate that proinsulin C-peptide is a key target of autoreactive CD4+ T cells in T1D. Hence, full-length C-peptide is a promising candidate for antigen-specific immunotherapy in T1D.

The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening.

AIMS/HYPOTHESIS: Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. METHODS: Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. RESULTS: Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. CONCLUSIONS/INTERPRETATION: Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.

The methionine aminopeptidase 2 inhibitor ZGN-1061 improves glucose control and weight in overweight and obese individuals with type 2 diabetes: A randomized, placebo-controlled trial.

The methionine aminopeptidase 2 (MetAP2) inhibitor ZGN-1061 lowered weight and improved glucose in preclinical studies. We sought to determine its efficacy and safety by performing a multicentre, phase 2, randomized controlled trial involving overweight and obese adults with type 2 diabetes and HbA1c between 7% and 11% inclusive. Participants were randomized to receive subcutaneous treatment with placebo or 0.05, 0.3, 0.9 or 1.8 mg ZGN-1061 every third day for 12 weeks. The primary outcome was change in HbA1c at week 12. Relative to placebo, the 0.9 and 1.8 mg doses induced clinically meaningful reductions in HbA1c of 0.6% (95% CI 0.2% to 0.9%; P = 0.0006) and 1.0% (95% CI 0.6% to 1.4%; P < 0.0001), respectively. The 1.8 mg dose also induced weight loss of 2.2% (95% CI 1.1% to 3.3%; P = 0.0002). The incidence of adverse events was balanced across the treatment groups. We conclude that MetAP2 inhibition with ZGN-1061 for 12 weeks improved glucose control and aided weight loss in overweight and obese people with type 2 diabetes. However, given safety issues, Zafgen has discontinued MetAP2 inhibitor development.

Changes in pancreatic exocrine function in young at-risk children followed to islet autoimmunity and type 1 diabetes in the ENDIA study.

BACKGROUNDS: We aimed to monitor pancreatic exocrine function longitudinally in relation to the development of islet autoimmunity (IA) and type 1 diabetes (T1D) in at-risk children with a first-degree relative with T1D, who were followed prospectively in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. METHODS: Fecal elastase-1 (FE-1) concentration was measured longitudinally in 85 ENDIA children from median age 1.0 (IQR 0.7,1.3) year. Twenty-eight of 85 children (progressors) developed persistent islet autoantibodies at median age of 1.5 (IQR 1.1,2.5) years, of whom 11 went on to develop clinical diabetes. The other 57 islet autoantibody-negative children (non-progressors) followed similarly were age and gender-matched with the progressors. An adjusted linear mixed model compared FE-1 concentrations in progressors and non-progressors. RESULTS: Baseline FE-1 did not differ between progressors and non-progressors, or by HLA DR type or proband status. FE-1 decreased over time in progressors in comparison to non-progressors (Wald statistic 5.46, P = .02); in some progressors the fall in FE-1 preceded the onset of IA. CONCLUSIONS: Pancreatic exocrine function decreases in the majority of young at-risk children who progress to IA and T1D.

Higher frequency of vertebrate-infecting viruses in the gut of infants born to mothers with type 1 diabetes.

BACKGROUND: Microbial exposures in utero and early life shape the infant microbiome, which can profoundly impact on health. Compared to the bacterial microbiome, very little is known about the virome. We set out to characterize longitudinal changes in the gut virome of healthy infants born to mothers with or without type 1 diabetes using comprehensive virome capture sequencing. METHODS: Healthy infants were selected from Environmental Determinants of Islet Autoimmunity (ENDIA), a prospective cohort of Australian children with a first-degree relative with type 1 diabetes, followed from pregnancy. Fecal specimens were collected three-monthly in the first year of life. RESULTS: Among 25 infants (44% born to mothers with type 1 diabetes) at least one virus was detected in 65% (65/100) of samples and 96% (24/25) of infants during the first year of life. In total, 26 genera of viruses were identified and >150 viruses were differentially abundant between the gut of infants with a mother with type 1 diabetes vs without. Positivity for any virus was associated with maternal type 1 diabetes and older infant age. Enterovirus was associated with older infant age and maternal smoking. CONCLUSIONS: We demonstrate a distinct gut virome profile in infants of mothers with type 1 diabetes, which may influence health outcomes later in life. Higher prevalence and greater number of viruses observed compared to previous studies suggests significant underrepresentation in existing virome datasets, arising most likely from less sensitive techniques used in data acquisition.

Glycaemic trajectory and predictors of suboptimal glycaemic control in people with type 2 diabetes.

We aimed to describe the glycaemic trajectory and define characteristics associated with suboptimal glycaemic control in the type 2 diabetes clinic. Higher glycosylated haemoglobin (HbA1c) at 1 year was associated with higher baseline HbA1c, concurrent anti-depressant or antipsychotic medication, higher bodyweight and low treatment adherence. These characteristics may help identify patients unlikely to attain HbA1c treatment targets and be better served by a different model of care.

Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables.

AIMS/HYPOTHESIS: Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2 h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. METHODS: Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. RESULTS: A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CONCLUSIONS/INTERPRETATION: CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes.