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OBJECTIVE To define the relationship between glucose and C-peptide during the progression to type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS We longitudinally studied glucose and C-peptide response curves (GCRCs), area under curve (AUC) for glucose, and AUC C-peptide from oral glucose tolerance tests (OGTTs), and Index60 (which integrates OGTT glucose and C-peptide values) in Diabetes Prevention Trial–Type 1 (DPT-1) (n = 72) and TrialNet Pathway to Prevention Study (TNPTP) (n = 82) participants who had OGTTs at baseline and follow-up time points before diagnosis. RESULTS Similar evolutions of GCRC configurations were evident between DPT-1 and TNPTP from baseline to 0.5 years prediagnosis. Whereas AUC glucose increased throughout from baseline to 0.5 years prediagnosis, AUC C-peptide increased from baseline until 1.5 years prediagnosis (DPT-1, P = 0.004; TNPTP, P = 0.012) and then decreased from 1.5 to 0.5 years prediagnosis (DPT-1, P = 0.017; TNPTP, P = 0.093). This change was mostly attributable to change in the late AUC C-peptide response (i.e., 60- to 120-min AUC C-peptide). Median Index60 values of DPT-1 (1.44) and TNPTP (1.05) progressors to T1D 1.5 years prediagnosis (time of transition from increasing to decreasing AUC C-peptide) were used as thresholds to identify individuals at high risk for T1D in the full cohort at baseline (5-year risk of 0.75–0.88 for those above thresholds). CONCLUSIONS A transition from an increase to a decrease in AUC C-peptide ∼1.5 years prediagnosis was validated in two independent cohorts. The median Index60 value at that time point can be used as a pathophysiologic-based threshold for identifying individuals at high risk for T1D.

Even after stratification based on established risk factors, the progression to T1D is variable. Thus, we aimed to examine differences in metabolic patterns of change between NP and P to T1D, and identify non-metabolic factors contributing to the differences. Specifically, we analyzed OGTT and autoantibody (Aab) data from children In conclusion, when NP and P have a similar degree of metabolic abnormality, IA-2A titers are greater in P. Moreover, as AUC ratio declines in P and improves in NP, IA-2A titers increase more in P than in NP. These findings suggest that IA-2A is a sensitive indicator of active β-cell pathology. Disclosure E.K.Sims: Other Relationship; Medscape, Patent. D.D.Cuthbertson: None. L.M.Jacobsen: None. H.M.Ismail: n/a. B.M.Nathan: None. M.J.Redondo: Advisory Panel; Provention Bio, Inc. J.Sosenko: None.

C-peptide area under the curve (AUC) at ≥1 year, a standard endpoint of recent-onset T1D clinical trials, is derived from a 120-minute mixed meal tolerance test (MMTT) . We analyzed whether composite glucose and C-peptide endpoints, useful in post hoc analyses of prevention trials, could detect treatment effects as early as 3 months between the combined treated and placebo groups from 3 TrialNet recent-onset T1D trials that met their primary endpoint. Comparisons were made between treated and placebo groups after adjustments for age, sex, and BMI Z-score using AUC C-peptide (standard measure) , AUC C-peptide/AUC glucose (AUC ratio) , and a new measure, the centroid ratio. Centroids, geometric central points of shapes, were derived from MMTT shapes formed from mean glucose and C-peptide values at 30, 60, 90, and 120 minutes. The centroid ratio is the C-peptide coordinate/glucose coordinate of the centroid. A treatment effect at 3 months was evident for centroid and AUC ratios (p In conclusion, composite glucose and C-peptide endpoints appear to identify early treatment efficacy and should be considered in future new-onset pilot studies and trials. Disclosure L.M.Jacobsen: None. A.Pugliese: Advisory Panel; Provention Bio, Inc., Consultant; Quell Tx. P.Gottlieb: Advisory Panel; Janssen Research & Development, LLC, ViaCyte, Inc., Other Relationship; IM Therapeutics, Research Support; Caladrius Biosciences, Inc., Immune Tolerance Network, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Precigen, Inc., Tolerion, Inc. J.Sosenko: None. D.D.Cuthbertson: None. M.J.Haller: Advisory Panel; SAB Biotherapeutics , Consultant; MannKind Corporation, Sanofi. H.M.Ismail: n/a. E.K.Sims: Other Relationship; Medscape, Patent. S.E.Gitelman: Advisory Panel; Abata Therapeutics, Avotres Inc., Biolojic Design, Ltd., Provention Bio, Inc., Rubius, SAB Biotherapeutics, Inc., Tolerion, Inc. D.K.Wherrett: n/a. A.Moran: Advisory Panel; Dompé, Other Relationship; Novo Nordisk, Research Support; Abbott Diabetes, Provention Bio, Inc. M.A.Atkinson: None.

Context Decreased first-phase insulin response (FPIR) during intravenous glucose tolerance testing (IVGTT) is an early indicator of β-cell dysfunction and predictor of type 1 diabetes (T1D). Objective Assess whether oral glucose tolerance test (OGTT) measures could serve as FPIR alternatives in their ability to predict T1D in autoantibody positive (Aab+) subjects. Design OGTT and IVGTT were performed within 30 days of each other. Eleven OGTT variables were evaluated for (1) correlation with FPIR and (2) T1D prediction. Setting Type 1 Diabetes TrialNet “Oral Insulin for Prevention of Diabetes in Relatives at Risk for T1D” (TN-07) and Diabetes Prevention Trial-Type 1 Diabetes (DPT-1) studies clinical sites. Patients TN-07 (n = 292; age 9.4 ± 6.1 years) and DPT-1 (n = 194; age 15.1 ± 10.0 years) Aab + relatives of T1D individuals. Main outcome measures (1) Correlation coefficients of OGTT measures with FPIR and (2) T1D prediction at 2 years using area under receiver operating characteristic (ROCAUC) curves. Results Index60 showed the strongest correlation in DPT-1 (r = -0.562) but was weaker in TN-07 (r = -0.378). C-peptide index consistently showed good correlation with FPIR across studies (TN-07, r = 0.583; DPT-1, r = 0.544; P Conclusions C-peptide index was the strongest measure to correlate with FPIR in both studies. Index60 and C-peptide index had the highest predictive accuracy for T1D and were comparable. OGTTs could be considered instead of IVGTTs for subject stratification in T1D prevention trials.

Type 1 diabetes is an autoimmune disease resulting in severely impaired insulin secretion. We investigated whether circulating microRNAs (miRNAs) are associated with residual insulin secretion at diagnosis and predict the severity of its future decline. We studied 53 newly diagnosed subjects enrolled in placebo groups of TrialNet clinical trials. We measured serum levels of 2,083 miRNAs using RNAseq technology, in fasting samples from the baseline visit (

To examine the current extent of the obesity problem in 2 large pediatric clinical registries in the US and Europe and to examine the hypotheses that increased body mass index (BMI) z-scores (BMIz) are associated with greater hemoglobin A1c (HbA1c) and increased frequency of severe hypoglycemia in youth with type 1 diabetes (T1D).International (World Health Organization) and national (Centers for Disease Control and Prevention/German Health Interview and Examination Survey for Children and Adolescents) BMI references were used to calculate BMIz in participants (age 2-18 years and ≥ 1 year duration of T1D) enrolled in the T1D Exchange (n = 11,435) and the Diabetes Prospective Follow-up (n = 21,501). Associations between BMIz and HbA1c and severe hypoglycemia were assessed.Participants in both registries had median BMI values that were greater than international and their respective national reference values. BMIz was significantly greater in the T1D Exchange vs the Diabetes Prospective Follow-up (P.001). After stratification by age-group, no differences in BMI between registries existed for children 2-5 years, but differences were confirmed for 6- to 9-, 10- to 13-, and 14- to 17-year age groups (all P.001). Greater BMIz were significantly related to greater HbA1c levels and more frequent occurrence of severe hypoglycemia across the registries, although these associations may not be clinically relevant.Excessive weight is a common problem in children with T1D in Germany and Austria and, especially, in the US. Our data suggest that obesity contributes to the challenges in achieving optimal glycemic control in children and adolescents with T1D.