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.).

Teplizumab and ß-Cell Function in Newly Diagnosed Type 1 Diabetes.

BACKGROUND: Teplizumab, a humanized monoclonal antibody to CD3 on T cells, is approved by the Food and Drug Administration to delay the onset of clinical type 1 diabetes (stage 3) in patients 8 years of age or older with preclinical (stage 2) disease. Whether treatment with intravenous teplizumab in patients with newly diagnosed type 1 diabetes can prevent disease progression is unknown. METHODS: In this phase 3, randomized, placebo-controlled trial, we assessed ß-cell preservation, clinical end points, and safety in children and adolescents who were assigned to receive teplizumab or placebo for two 12-day courses. The primary end point was the change from baseline in ß-cell function, as measured by stimulated C-peptide levels at week 78. The key secondary end points were the insulin doses that were required to meet glycemic goals, glycated hemoglobin levels, time in the target glucose range, and clinically important hypoglycemic events. RESULTS: Patients treated with teplizumab (217 patients) had significantly higher stimulated C-peptide levels than patients receiving placebo (111 patients) at week 78 (least-squares mean difference, 0.13 pmol per milliliter; 95% confidence interval [CI], 0.09 to 0.17; P<0.001), and 94.9% (95% CI, 89.5 to 97.6) of patients treated with teplizumab maintained a clinically meaningful peak C-peptide level of 0.2 pmol per milliliter or greater, as compared with 79.2% (95% CI, 67.7 to 87.4) of those receiving placebo. The groups did not differ significantly with regard to the key secondary end points. Adverse events occurred primarily in association with administration of teplizumab or placebo and included headache, gastrointestinal symptoms, rash, lymphopenia, and mild cytokine release syndrome. CONCLUSIONS: Two 12-day courses of teplizumab in children and adolescents with newly diagnosed type 1 diabetes showed benefit with respect to the primary end point of preservation of ß-cell function, but no significant differences between the groups were observed with respect to the secondary end points. (Funded by Provention Bio and Sanofi; PROTECT ClinicalTrials.gov number, NCT03875729.).

vPIF-1 is an insulin-like antiferroptotic viral peptide.

Iridoviridae, such as the lymphocystis disease virus-1 (LCDV-1) and other viruses, encode viral insulin-like peptides (VILPs) which are capable of triggering insulin receptors (IRs) and insulin-like growth factor receptors. The homology of VILPs includes highly conserved disulfide bridges. However, the binding affinities to IRs were reported to be 200- to 500-fold less effective compared to the endogenous ligands. We therefore speculated that these peptides also have noninsulin functions. Here, we report that the LCDV-1 VILP can function as a potent and highly specific inhibitor of ferroptosis. Induction of cell death by the ferroptosis inducers erastin, RSL3, FIN56, and FINO2 and nonferroptotic necrosis produced by the thioredoxin-reductase inhibitor ferroptocide were potently prevented by LCDV-1, while human insulin had no effect. Fas-induced apoptosis, necroptosis, mitotane-induced cell death and growth hormone-releasing hormone antagonist-induced necrosis were unaffected, suggesting the specificity to ferroptosis inhibition by the LCDV-1 VILP. Mechanistically, we identified the viral C-peptide to be required for inhibition of lipid peroxidation and ferroptosis inhibition, while the human C-peptide exhibited no antiferroptotic properties. In addition, the deletion of the viral C-peptide abolishes radical trapping activity in cell-free systems. We conclude that iridoviridae, through the expression of insulin-like viral peptides, are capable of preventing ferroptosis. In analogy to the viral mitochondrial inhibitor of apoptosis and the viral inhibitor of RIP activation (vIRA) that prevents necroptosis, we rename the LCDV-1 VILP a viral peptide inhibitor of ferroptosis-1. Finally, our findings indicate that ferroptosis may function as a viral defense mechanism in lower organisms.

A novel antisense lncRNA, ARBAG harboring an RNA destabilizing GWAS variant for C-peptide dictates the transcript isoforms of GABRA6 in cerebellum.

Human disease-associated genetic variations often map to long non-coding RNA (lncRNA) genes; however, elucidation of their functional impact is challenging. We previously identified a new genetic variant rs4454083 (A/G) residing in exon of an uncharacterized lncRNA ARBAG that strongly associates with plasma levels of C-peptide, a hormone that regulates insulin bioavailability. On the opposite strand, rs4454083 also corresponds to an intron of a cerebellum-specific GABA receptor subunit gene GABRA6 that mediates strengthening of inhibitory synapses by insulin. Here, we show that alleles of rs4454083 modulate transcript levels of the antisense gene, ARBAG, which then controls the expression of the sense gene, GABRA6. Predisposing to low C-peptide, GG (a minor allele genotype across ethnicities) stabilizes ARBAG lncRNA causing higher transcript levels in cerebellum. ARBAG lncRNA abundance leads to cleavage of GABRA6 mRNA at the complementary region, resulting in a dysfunctional GABRA6 protein that would not be recruited for synapse strengthening. Together, our findings in human cerebellar cell-line and induced Pluripotent Stem Cells (iPSCs) demonstrate biological role of a novel lncRNA in determining the ratio of mRNA isoforms of a protein-coding gene and the ability of an embedded variant in modulating lncRNA stability leading to inter-individual differences in protein expression.

Closed-Loop Therapy and Preservation of C-Peptide Secretion in Type 1 Diabetes.

BACKGROUND: Whether improved glucose control with hybrid closed-loop therapy can preserve C-peptide secretion as compared with standard insulin therapy in persons with new-onset type 1 diabetes is unclear. METHODS: In a multicenter, open-label, parallel-group, randomized trial, we assigned youths 10.0 to 16.9 years of age within 21 days after a diagnosis of type 1 diabetes to receive hybrid closed-loop therapy or standard insulin therapy (control) for 24 months. The primary end point was the area under the curve (AUC) for the plasma C-peptide level (after a mixed-meal tolerance test) at 12 months after diagnosis. The analysis was performed on an intention-to-treat basis. RESULTS: A total of 97 participants (mean [±SD] age, 12±2 years) underwent randomization: 51 were assigned to receive closed-loop therapy and 46 to receive control therapy. The AUC for the C-peptide level at 12 months (primary end point) did not differ significantly between the two groups (geometric mean, 0.35 pmol per milliliter [interquartile range, 0.16 to 0.49] with closed-loop therapy and 0.46 pmol per milliliter [interquartile range, 0.22 to 0.69] with control therapy; mean adjusted difference, -0.06 pmol per milliliter [95% confidence interval {CI}, -0.14 to 0.03]). There was not a substantial between-group difference in the AUC for the C-peptide level at 24 months (geometric mean, 0.18 pmol per milliliter [interquartile range, 0.06 to 0.22] with closed-loop therapy and 0.24 pmol per milliliter [interquartile range, 0.05 to 0.30] with control therapy; mean adjusted difference, -0.04 pmol per milliliter [95% CI, -0.14 to 0.06]). The arithmetic mean glycated hemoglobin level was lower in the closed-loop group than in the control group by 4 mmol per mole (0.4 percentage points; 95% CI, 0 to 8 mmol per mole [0.0 to 0.7 percentage points]) at 12 months and by 11 mmol per mole (1.0 percentage points; 95% CI, 7 to 15 mmol per mole [0.5 to 1.5 percentage points]) at 24 months. Five cases of severe hypoglycemia occurred in the closed-loop group (in 3 participants), and one occurred in the control group; one case of diabetic ketoacidosis occurred in the closed-loop group. CONCLUSIONS: In youths with new-onset type 1 diabetes, intensive glucose control for 24 months did not appear to prevent the decline in residual C-peptide secretion. (Funded by the National Institute for Health and Care Research and others; CLOuD ClinicalTrials.gov number, NCT02871089.).

The MHC Class II Antigen-Processing and Presentation Pathway Is Dysregulated in Type 1 Diabetes.

Peptide loading of MHC class II (MHCII) molecules is facilitated by HLA-DM (DM), which catalyzes CLIP release, stabilizes empty MHCII, and edits the MHCII-bound peptide repertoire. HLA-DO (DO) binds to DM and modulates its activity, resulting in an altered set of peptides presented at the cell surface. MHCII-peptide presentation in individuals with type 1 diabetes (T1D) is abnormal, leading to a breakdown in tolerance; however, no direct measurement of the MHCII pathway activity in T1D patients has been performed. In this study, we measured MHCII Ag-processing pathway activity in humans by determining MHCII, MHCII-CLIP, DM, and DO levels by flow cytometry for peripheral blood B cells, dendritic cells, and monocytes from 99 T1D patients and 97 controls. Results showed that MHCII levels were similar for all three APC subsets. In contrast, MHCII-CLIP levels, independent of sex, age at blood draw, disease duration, and diagnosis age, were significantly increased for all three APCs, with B cells showing the largest increase (3.4-fold). DM and DO levels, which usually directly correlate with MHCII-CLIP levels, were unexpectedly identical in T1D patients and controls. Gene expression profiling on PBMC RNA showed that DMB mRNA was significantly elevated in T1D patients with residual C-peptide. This resulted in higher levels of DM protein in B cells and dendritic cells. DO levels were also increased, suggesting that the MHCII pathway maybe differentially regulated in individuals with residual C-peptide. Collectively, these studies show a dysregulation of the MHCII Ag-processing pathway in patients with T1D.

The metabolic potential of inflammatory and insulinaemic dietary patterns and risk of type 2 diabetes.

AIMS/HYPOTHESIS: Diets with higher inflammatory and insulinaemic potential have been associated with an increased risk of type 2 diabetes. However, it remains unknown whether plasma metabolomic profiles related to proinflammatory/hyperinsulinaemic diets and to inflammatory/insulin biomarkers are associated with type 2 diabetes risk. METHODS: We analysed 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study to identify the plasma metabolome related to empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), four circulating inflammatory biomarkers and C-peptide. Dietary intakes were assessed using validated food frequency questionnaires. Plasma metabolomic profiling was conducted by LC-MS/MS. Metabolomic signatures were derived using elastic net regression. Multivariable Cox regression was used to examine associations of the metabolomic profiles with type 2 diabetes risk. RESULTS: We identified 27 metabolites commonly associated with both EDIP and inflammatory biomarker z score and 21 commonly associated with both EDIH and C-peptide. Higher metabolomic dietary inflammatory potential (MDIP), reflecting higher metabolic potential of both an inflammatory dietary pattern and circulating inflammatory biomarkers, was associated with higher type 2 diabetes risk. The HR comparing highest vs lowest quartiles of MDIP was 3.26 (95% CI 2.39, 4.44). We observed a strong positive association with type 2 diabetes risk for the metabolomic signature associated with EDIP-only (HR 3.75; 95% CI 2.71, 5.17) or inflammatory biomarkers-only (HR 4.07; 95% CI 2.91, 5.69). In addition, higher metabolomic dietary index for hyperinsulinaemia (MDIH), reflecting higher metabolic potential of both an insulinaemic dietary pattern and circulating C-peptide, was associated with greater type 2 diabetes risk (HR 3.00; 95% CI 2.22, 4.06); further associations with type 2 diabetes were HR 2.79 (95% CI 2.07, 3.76) for EDIH-only signature and HR 3.89 (95% CI 2.82, 5.35) for C-peptide-only signature. The diet scores were significantly associated with risk, although adjustment for the corresponding metabolomic signature scores attenuated the associations with type 2 diabetes, these remained significant. CONCLUSIONS/INTERPRETATION: The metabolomic signatures reflecting proinflammatory or hyperinsulinaemic diets and related biomarkers were positively associated with type 2 diabetes risk, supporting that these dietary patterns may influence type 2 diabetes risk via the regulation of metabolism.

A first-in-human, open-label Phase 1b and a randomised, double-blind Phase 2a clinical trial in recent-onset type 1 diabetes with AG019 as monotherapy and in combination with teplizumab.

AIMS/HYPOTHESIS: We hypothesised that islet beta cell antigen presentation in the gut along with a tolerising cytokine would lead to antigen-specific tolerance in type 1 diabetes. We evaluated this in a parallel open-label Phase 1b study using oral AG019, food-grade Lactococcus lactis bacteria genetically modified to express human proinsulin and human IL-10, as a monotherapy and in a parallel, randomised, double-blind Phase 2a study using AG019 in combination with teplizumab. METHODS: Adults (18-42 years) and adolescents (12-17 years) with type 1 diabetes diagnosed within 150 days were enrolled, with documented evidence of at least one autoantibody and a stimulated peak C-peptide level >0.2 nmol/l. Participants were allocated to interventions using interactive response technology. We treated 42 people aged 12-42 years with recent-onset type 1 diabetes, 24 with Phase 1b monotherapy (open-label) and 18 with Phase 2a combination therapy. In the Phase 2a study, after treatment of the first two open-label participants, all people involved were blinded to group assignment, except for the Data Safety Monitoring Board members and the unblinded statistician. The primary endpoint was safety and tolerability based on the incidence of treatment-emergent adverse events, collected up to 6 months post treatment initiation. The secondary endpoints were pharmacokinetics, based on AG019 detection in blood and faeces, and pharmacodynamic activity. Metabolic and immune endpoints included stimulated C-peptide levels during a mixed meal tolerance test, HbA1c levels, insulin use, and antigen-specific CD4+ and CD8+ T cell responses using an activation-induced marker assay and pooled tetramers, respectively. RESULTS: Data from 24 Phase 1b participants and 18 Phase 2a participants were analysed. No serious adverse events were reported and none of the participants discontinued AG019 due to treatment-emergent adverse events. No systemic exposure to AG019 bacteria, proinsulin or human IL-10 was demonstrated. In AG019 monotherapy-treated adults, metabolic variables were stabilised up to 6 months (C-peptide, insulin use) or 12 months (HbA1c) post treatment initiation. In participants treated with AG019/teplizumab combination therapy, all measured metabolic variables stabilised or improved up to 12 months and CD8+ T cells with a partially exhausted phenotype were significantly increased at 6 months. Circulating preproinsulin-specific CD4+ and CD8+ T cells were detected before and after treatment, with a reduction in the frequency of preproinsulin-specific CD8+ T cells after treatment with monotherapy or combination therapy. CONCLUSIONS/INTERPRETATION: Oral delivery of AG019 was well tolerated and safe as monotherapy and in combination with teplizumab. AG019 was not shown to interfere with the safety profile of teplizumab and may have additional biological effects, including changes in preproinsulin-specific T cells. These preliminary data support continuing studies with this agent alone and in combination with teplizumab or other systemic immunotherapies in type 1 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT03751007, EudraCT 2017-002871-24 FUNDING: This study was funded by Precigen ActoBio.

An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study.

AIMS/HYPOTHESIS: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. METHODS: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic. RESULTS: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. CONCLUSIONS/INTERPRETATION: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. DATA AVAILABILITY: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch .

Glycaemia risk index uncovers distinct glycaemic variability patterns associated with remission status in type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this work was to define a unique remission status using glycaemia risk index (GRI) and other continuous glucose monitoring (CGM) metrics in individuals with type 1 diabetes for improved phenotyping. METHODS: A group of 140 individuals with type 1 diabetes were recruited for a cross-sectional study. The participants were categorised into four groups based on their remission status, which was defined as insulin-dose-adjusted A1c (IDAA1c) <9 or C-peptide ≥300 pmol/l: new-onset (n=24); mid-remission (n=44); post-remission (n=44); and non-remission (individuals who did not experience remission, n=28). Participants in the remission phase were referred to as 'remitters', while those who were not in the remission phase were referred to as 'non-remitters', the latter group including new-onset, post-remission and non-remission participants. Clinical variables such as HbA1c, C-peptide and insulin daily dose, as well as IDAA1C and CGM data, were collected. The patterns of CGM metrics were analysed for each group using generalised estimating equations to investigate the glycaemic variability patterns associated with remission status. Then, unsupervised hierarchical clustering was used to place the participants into subgroups based on GRI and other CGM core metrics. RESULTS: The glycaemic variability patterns associated with remission status were found to be distinct based on the circadian CGM metrics. Remitters showed improved control of blood glucose levels over 14 days within the range of 3.9-10 mmol/l, and lower GRI compared with non-remitters (p<0.001). Moreover, GRI strongly correlated with IDAA1C (r=0.62; p<0.001) and was sufficient to distinguish remitters from non-remitters. Further, four subgroups demonstrating distinct patterns of glycaemic variability associated with different remission status were identified by clustering on CGM metrics: remitters with low risk of dysglycaemia; non-remitters with high risk of hypoglycaemia; non-remitters with high risk of hyperglycaemia; and non-remitters with moderate risk of dysglycaemia. CONCLUSIONS/INTERPRETATION: GRI, an integrative index, together with other traditional CGM metrics, helps to identify different glycaemic variability patterns; this might provide specifically tailored monitoring and management strategies for individuals in the various subclusters.

Gut microbiome shifts in people with type 1 diabetes are associated with glycaemic control: an INNODIA study.

AIMS/HYPOTHESIS: The gut microbiome is implicated in the disease process leading to clinical type 1 diabetes, but less is known about potential changes in the gut microbiome after the diagnosis of type 1 diabetes and implications in glucose homeostasis. We aimed to analyse potential associations between the gut microbiome composition and clinical and laboratory data during a 2 year follow-up of people with newly diagnosed type 1 diabetes, recruited to the Innovative approaches to understanding and arresting type 1 diabetes (INNODIA) study. In addition, we analysed the microbiome composition in initially unaffected family members, who progressed to clinical type 1 diabetes during or after their follow-up for 4 years. METHODS: We characterised the gut microbiome composition of 98 individuals with newly diagnosed type 1 diabetes (ND cohort) and 194 autoantibody-positive unaffected family members (UFM cohort), representing a subgroup of the INNODIA Natural History Study, using metagenomic sequencing. Participants from the ND cohort attended study visits within 6 weeks from the diagnosis and 3, 6, 12 and 24 months later for stool sample collection and laboratory tests (HbA1c, C-peptide, diabetes-associated autoantibodies). Participants from the UFM cohort were assessed at baseline and 6, 12, 18, 24 and 36 months later. RESULTS: We observed a longitudinal increase in 21 bacterial species in the ND cohort but not in the UFM cohort. The relative abundance of Faecalibacterium prausnitzii was inversely associated with the HbA1c levels at diagnosis (p=0.0019). The rate of the subsequent disease progression in the ND cohort, as assessed by change in HbA1c, C-peptide levels and insulin dose, was associated with the abundance of several bacterial species. Individuals with rapid decrease in C-peptide levels in the ND cohort had the lowest gut microbiome diversity. Nineteen individuals who were diagnosed with type 1 diabetes in the UFM cohort had increased abundance of Sutterella sp. KLE1602 compared with the undiagnosed UFM individuals (p=1.2 × 10-4). CONCLUSIONS/INTERPRETATION: Our data revealed associations between the gut microbiome composition and the disease progression in individuals with recent-onset type 1 diabetes. Future mechanistic studies as well as animal studies and human trials are needed to further validate the significance and causality of these associations.

The INNODIA Type 1 Diabetes Natural History Study: a European cohort of newly diagnosed children, adolescents and adults.

AIMS/HYPOTHESIS: Type 1 diabetes is an heterogenous condition. Characterising factors explaining differences in an individual's clinical course and treatment response will have important clinical and research implications. Our aim was to explore type 1 diabetes heterogeneity, as assessed by clinical characteristics, autoantibodies, beta cell function and glycaemic outcomes, during the first 12 months from diagnosis, and how it relates to age at diagnosis. METHODS: Data were collected from the large INNODIA cohort of individuals (aged 1.0-45.0 years) newly diagnosed with type 1 diabetes, followed 3 monthly, to assess clinical characteristics, C-peptide, HbA1c and diabetes-associated antibodies, and their changes, during the first 12 months from diagnosis, across three age groups: <10 years; 10-17 years; and ≥18 years. RESULTS: The study population included 649 individuals (57.3% male; age 12.1±8.3 years), 96.9% of whom were positive for one or more diabetes-related antibodies. Baseline (IQR) fasting C-peptide was 242.0 (139.0-382.0) pmol/l (AUC 749.3 [466.2-1106.1] pmol/l × min), with levels increasing with age (p<0.001). Over time, C-peptide remained lower in participants aged <10 years but it declined in all age groups. In parallel, glucose levels progressively increased. Lower baseline fasting C-peptide, BMI SD score and presence of diabetic ketoacidosis at diagnosis were associated with lower stimulated C-peptide over time. HbA1c decreased during the first 3 months (p<0.001), whereas insulin requirement increased from 3 months post diagnosis (p<0.001). CONCLUSIONS/INTERPRETATION: In this large cohort with newly diagnosed type 1 diabetes, we identified age-related differences in clinical and biochemical variables. Of note, C-peptide was lower in younger children but there were no main age differences in its rate of decline.

Phenotype and predictors of insulin independence in adults presenting with diabetic ketoacidosis: a prospective cohort study.

AIMS/HYPOTHESIS: The aim of this work was to describe the phenotype of adults presenting with a first episode of diabetic ketoacidosis (DKA) in Cape Town, South Africa, and identify predictors of insulin independence at 12 and 60 months after presentation. METHODS: A prospective, descriptive cohort study of all individuals, 18 years or older, presenting for the first time with DKA to four public-sector hospitals of the Groote Schuur Academic Health Complex was performed. Clinical, biochemical and laboratory data including GAD antibody and C-peptide status were collected at baseline. Insulin was systematically weaned and stopped in individuals who achieved normoglycaemia within the months after DKA. Individuals were followed for 12 months and then annually until 5 years after initial presentation with ketoacidosis. RESULTS: Eighty-eight individuals newly diagnosed with diabetes when presenting with DKA were included and followed for 5 years. The mean ± SD age was 35±10 years and the median (IQR) BMI at diagnosis was 28.5 (23.3-33.4) kg/m2. Overall, 46% were insulin independent 12 months after diagnosis and 26% remained insulin independent 5 years after presentation. Forty-one participants (47%) tested negative for anti-GAD and anti-IA-2 antibodies and had C-peptide levels >0.3 nmol/l; in this group, 68% were insulin independent at 12 months and 37% at 5 years after diagnosis. The presence of acanthosis nigricans was strongly associated with insulin independence (OR 27.1 [95% CI 7.2, 102.2]; p<0.001); a positive antibody status was associated with a lower likelihood of insulin independence at 12 months (OR 0.10 [95% CI 0.03, 0.36]; p<0.001). On multivariable analysis only acanthosis (OR 11.5 [95% CI 2.5, 53.2]; p=0.004) was predictive of insulin independence 5 years after diagnosis. CONCLUSIONS/INTERPRETATION: The predominant phenotype of adults presenting with a first episode of DKA in Cape Town, South Africa, was that of ketosis-prone type 2 diabetes. These individuals presented with obesity, acanthosis nigricans, negative antibodies and normal C-peptide and could potentially be weaned off insulin at follow-up. Classic type 1 diabetes (lower weight, antibody positivity, low or unrecordable C-peptide levels and long-term insulin dependence) was less common. The simple clinical sign of acanthosis nigricans is a strong predictor of insulin independence at 12 months and 5 years after initial presentation.

Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes.

AIMS/HYPOTHESIS: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed. RESULTS: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%. CONCLUSIONS/INTERPRETATION: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

The metabolome as a diagnostic for maximal aerobic capacity during exercise in type 1 diabetes.

AIMS/HYPOTHESIS: Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined by V ˙ O 2peak . METHODS: Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (<3 pmol/l), low (3-200 pmol/l) or high (>200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed by V ˙ O 2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60% V ˙ O 2peak ) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity ( V ˙ O 2peak ) during exercise in health and type 1 diabetes. RESULTS: Maximal aerobic capacity ( V ˙ O 2peak ) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23×10-5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity ( V ˙ O 2peak ) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]). CONCLUSIONS/INTERPRETATION: The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes.

C-peptide in diabetes: A player in a dual hormone disorder?

C-peptide, a byproduct of insulin synthesis believed to be biologically inert, is emerging as a multifunctional molecule. C-peptide serves an anti-inflammatory and anti-atherogenic role in type 1 diabetes mellitus (T1DM) and early T2DM. C-peptide protects endothelial cells by activating AMP-activated protein kinase α, thus suppressing the activity of NAD(P)H oxidase activity and reducing reactive oxygen species (ROS) generation. It also prevents apoptosis by regulating hyperglycemia-induced p53 upregulation and mitochondrial adaptor p66shc overactivation, as well as reducing caspase-3 activity and promoting expression of B-cell lymphoma-2. Additionally, C-peptide suppresses platelet-derived growth factor (PDGF)-beta receptor and p44/p42 mitogen-activated protein (MAP) kinase phosphorylation to inhibit vascular smooth muscle cells (VSMC) proliferation. It also diminishes leukocyte adhesion by virtue of its capacity to abolish nuclear factor kappa B (NF-kB) signaling, a major pro-inflammatory cascade. Consequently, it is envisaged that supplementation of C-peptide in T1DM might ameliorate or even prevent end-organ damage. In marked contrast, C-peptide increases monocyte recruitment and migration through phosphoinositide 3-kinase (PI-3 kinase)-mediated pathways, induces lipid accumulation via peroxisome proliferator-activated receptor γ upregulation, and stimulates VSMC proliferation and CD4+ lymphocyte migration through Src-kinase and PI-3K dependent pathways. Thus, it promotes atherosclerosis and microvascular damage in late T2DM. Indeed, C-peptide is now contemplated as a potential biomarker for insulin resistance in T2DM and linked to increased coronary artery disease risk. This shift in the understanding of the pathophysiology of diabetes from being a single hormone deficiency to a dual hormone disorder warrants a careful consideration of the role of C-peptide as a unique molecule with promising diagnostic, prognostic, and therapeutic applications.

Inverse Peptide Synthesis Using Transient Protected Amino Acids.

Peptide therapeutics have experienced a rapid resurgence over the past three decades. While a few peptide drugs are biologically produced, most are manufactured via chemical synthesis. The cycle of prior protection of the amino group of an α-amino acid, activation of its carboxyl group, aminolysis with the free amino group of a growing peptide chain, and deprotection of the N-terminus constitutes the principle of conventional C → N peptide chemical synthesis. The mandatory use of the Nα-protecting group invokes two additional operations for incorporating each amino acid, resulting in poor step- and atom-economy. The burgeoning demand in the peptide therapeutic market necessitates cost-effective and environmentally friendly peptide manufacturing strategies. Inverse peptide chemical synthesis using unprotected amino acids has been proposed as an ideal and appealing strategy. However, it has remained unsuccessful for over 60 years due to severe racemization/epimerization during N → C peptide chain elongation. Herein, this challenge has been successfully addressed by ynamide coupling reagent employing a transient protection strategy. The activation, transient protection, aminolysis, and in situ deprotection were performed in one pot, thus offering a practical peptide chemical synthesis strategy formally using unprotected amino acids as the starting material. Its robustness was exemplified by syntheses of peptide active pharmaceutical ingredients. It is also amenable to fragment condensation and inverse solid-phase peptide synthesis. The compatibility to green solvents further enhances its application potential in large-scale peptide production. This study offered a cost-effective, operational convenient, and environmentally benign approach to peptides.

Comparison of an oral mixed meal plus arginine and intravenous glucose, GLP-1 plus arginine to unmask residual islet function in longstanding type 1 diabetes.

Residual beta cells are present in most patients with longstanding type 1 diabetes but it is unknown whether these beta cells react normally to different stimuli. Moreover a defect in proinsulin conversion and abnormal alpha cell response are also part of the islet dysfunction. A three-phase [euglycemia, hyperglycemia, and hyperglycemia + glucagon-like peptide 1 (GLP-1)] clamp was performed in patients with longstanding type 1 diabetes. Intravenous arginine boluses were administered at the end of each phase. On another day, a mixed meal stimulation test with a subsequent intravenous arginine bolus was performed. C-peptide was detectable in a subgroup of subjects at baseline (2/15) or only after stimulation (3/15). When detectable, C-peptide increased 2.9-fold [95% CI: 1.2-7.1] during the hyperglycemia phase and 14.1-fold [95% CI: 3.1-65.2] during the hyperglycemia + GLP-1 phase, and 22.3-fold [95% CI: 5.6-89.1] during hyperglycemia + GLP-1 + arginine phase when compared with baseline. The same subset of patients with a C-peptide response were identified during the mixed meal stimulation test as during the clamp. There was an inhibition of glucagon secretion (0.72-fold, [95% CI: 0.63-0.84]) during the glucose clamp irrespective of the presence of detectable beta cell function. Proinsulin was only present in a subset of subjects with detectable C-peptide (3/15) and proinsulin mimicked the C-peptide response to the different stimuli when detectable. Residual beta cells in longstanding type 1 diabetes respond adequately to different stimuli and could be of clinical benefit.NEW & NOTEWORTHY If beta cell function is detectable, the beta cells react relatively normal to the different stimuli except for the first phase response to intravenous glucose. An oral mixed meal followed by an intravenous arginine bolus can identify residual beta cell function/mass as well as the more commonly used glucose potentiated arginine-induced insulin secretion during a hyperglycemic clamp.

The Prostate Cancer Active Lifestyle Study (PALS): A randomized controlled trial of diet and exercise in overweight and obese men on active surveillance.

BACKGROUND: Active surveillance (AS) is increasingly used to monitor patients with lower risk prostate cancer (PCa). The Prostate Cancer Active Lifestyle Study (PALS) was a randomized controlled trial to determine whether weight loss improves obesity biomarkers on the causal pathway to progression in patients with PCa on AS. METHODS: Overweight/obese men (body mass index >25 kg/m2) diagnosed with PCa who elected AS were recruited. The intervention was a 6-month, individually delivered, structured diet and exercise program adapted from the Diabetes Prevention Program with a 7% weight loss goal from baseline. Control participants attended one session reviewing the US Dietary and Physical Activity Guidelines. The primary outcome was change in glucose regulation from baseline to the end of the 6-month intervention, which was measured by fasting plasma glucose, C-peptide, insulin, insulin-like growth factor 1, insulin-like growth factor binding protein-3, adiponectin, and homeostatic model assessment for insulin resistance. RESULTS: Among 117 men who were randomized, 100 completed the trial. The mean percentage weight loss was 7.1% and 1.8% in the intervention and control arms, respectively (adjusted between-group mean difference, -6.0 kg; 95% confidence interval, -8.0, -4.0). Mean percentage changes from baseline for insulin, C-peptide, and homeostatic model assessment for insulin resistance in the intervention arm were -23%, -16%, and -25%, respectively, compared with +6.9%, +7.5%, and +6.4%, respectively, in the control arm (all p for intervention effects ≤ .003). No significant between-arm differences were detected for the other biomarkers. CONCLUSIONS: Overweight/obese men with PCa undergoing AS who participated in a lifestyle-based weight loss intervention successfully met weight loss goals with this reproducible lifestyle intervention and experienced improvements in glucose-regulation biomarkers associated with PCa progression.

Neonatal islets from human PD-L1 transgenic pigs reduce immune cell activation and cellular rejection in humanized nonobese diabetic-scid IL2rγnull mice.

Strong xenorejection limits the clinical application of porcine islet transplantation in type 1 diabetes. Targeting T cell-mediated rejection is one of the main approaches to improve long-term graft survival. Here we study engraftment and survival of porcine islet cells expressing human programmed cell death ligand-1 (hPD-L1) in a humanized mouse model. Neonatal islet-like clusters (NPICCs) from transgenic hPD-L1 (hPD-L1-Tg) and wild-type (Wt) pigs were transplanted into nonobese diabetic-scid IL2rγnull mice stably reconstituted with human immune cells (hPD-L1 n = 10; Wt n = 6). Primary endpoint was development of normoglycemia during a 16-week observation period after transplantation. Secondary endpoints were porcine C-peptide levels and immune cell infiltration. Animals transplanted with hPD-L1-Tg neonatal islet-like clusters achieved a superior normoglycemic rate (50% versus 0%) and significantly higher plasma C-peptide levels as compared to the Wt group, indicating long-term beta cell function. Intracytoplasmic fluorescence-activated cell sorting analysis and immunohistochemistry revealed significantly decreased frequencies of interferonγ-expressing splenic hCD8-positive T cells and reduced intragraft-infiltrating immune cells. We here demonstrate that expression of hPD-L1 provides strong islet xenograft protection without administration of immunosuppressive drugs. These findings support the hypothesis that hPD-L1 has the capacity to control cellular rejection and therefore represents a very promising transgene candidate for clinical porcine islet xenotransplantation.