Fall in C-peptide during first 2 years from diagnosis: evidence of at least two distinct phases from composite Type 1 Diabetes TrialNet data.
ABSTRACT: Interpretation of clinical trials to alter the decline in ?-cell function after diagnosis of type 1 diabetes depends on a robust understanding of the natural history of disease. Combining data from the Type 1 Diabetes TrialNet studies, we describe the natural history of ?-cell function from shortly after diagnosis through 2 years post study randomization, assess the degree of variability between patients, and investigate factors that may be related to C-peptide preservation or loss. We found that 93% of individuals have detectable C-peptide 2 years from diagnosis. In 11% of subjects, there was no significant fall from baseline by 2 years. There was a biphasic decline in C-peptide; the C-peptide slope was -0.0245 pmol/mL/month (95% CI -0.0271 to -0.0215) through the first 12 months and -0.0079 (-0.0113 to -0.0050) from 12 to 24 months (P < 0.001). This pattern of fall in C-peptide over time has implications for understanding trial results in which effects of therapy are most pronounced early and raises the possibility that there are time-dependent differences in pathophysiology. The robust data on the C-peptide obtained under clinical trial conditions should be used in planning and interpretation of clinical trials.
Project description:Type 1 diabetes is an autoimmune disease arising from the destruction of pancreatic insulin-producing beta cells. The disease represents a continuum, progressing sequentially at variable rates through identifiable stages prior to the onset of symptoms, through diagnosis and into the critical periods that follow, culminating in a variable depth of beta cell depletion. The ability to identify the very earliest of these presymptomatic stages has provided a setting in which prevention strategies can be trialled, as well as furnishing an unprecedented opportunity to study disease evolution, including intrinsic and extrinsic initiators and drivers. This niche opportunity is occupied by Type 1 Diabetes TrialNet, an international consortium of clinical trial centres that leads the field in intervention and prevention studies, accompanied by deep longitudinal bio-sampling. In this review, we focus on discoveries arising from this unique bioresource, comprising more than 70,000 samples, and outline the processes and science that have led to new biomarkers and mechanistic insights, as well as identifying new challenges and opportunities. We conclude that via integration of clinical trials and mechanistic studies, drawing in clinicians and scientists and developing partnership with industry, TrialNet embodies an enviable and unique working model for understanding a disease that to date has no cure and for designing new therapeutic approaches.
Project description:OBJECTIVE:To explore whether electrochemiluminescence (ECL) assays can help improve prediction of time to type 1 diabetes in the TrialNet autoantibody-positive population. RESEARCH DESIGN AND METHODS:TrialNet subjects who were positive for one or more autoantibodies (microinsulin autoantibody, GAD65 autoantibody [GADA], IA-2A, and ZnT8A) with available ECL-insulin autoantibody (IAA) and ECL-GADA data at their initial visit were analyzed; after a median follow-up of 24 months, 177 of these 1,287 subjects developed diabetes. RESULTS:Univariate analyses showed that autoantibodies by radioimmunoassays (RIAs), ECL-IAA, ECL-GADA, age, sex, number of positive autoantibodies, presence of HLA DR3/4-DQ8 genotype, HbA1c, and oral glucose tolerance test (OGTT) measurements were all significantly associated with progression to diabetes. Subjects who were ECL positive had a risk of progression to diabetes within 6 years of 58% compared with 5% for the ECL-negative subjects (P < 0.0001). Multivariate Cox proportional hazards models were compared, with the base model including age, sex, OGTT measurements, and number of positive autoantibodies by RIAs. The model with positivity for ECL-GADA and/or ECL-IAA was the best, and factors that remained significantly associated with time to diabetes were area under the curve (AUC) C-peptide, fasting C-peptide, AUC glucose, number of positive autoantibodies by RIAs, and ECL positivity. Adding ECL to the Diabetes Prevention Trial risk score (DPTRS) improved the receiver operating characteristic curves with AUC of 0.83 (P < 0.0001). CONCLUSIONS:ECL assays improved the ability to predict time to diabetes in these autoantibody-positive relatives at risk for developing diabetes. These findings might be helpful in the design and eligibility criteria for prevention trials in the future.
Project description:What will it take to bring disease-modifying therapy to clinical use in type 1 diabetes? Coordinated efforts of investigators involved in discovery, translational, and clinical research operating in partnership with funders and industry and in sync with regulatory agencies are needed. This Perspective describes one such effort, Type 1 Diabetes TrialNet, a National Institutes of Health-funded and JDRF-supported international clinical trials network that emerged from the Diabetes Prevention Trial-Type 1 (DPT-1). Through longitudinal natural history studies, as well as trials before and after clinical onset of disease combined with mechanistic and ancillary investigations to enhance scientific understanding and translation to clinical use, TrialNet is working to bring disease-modifying therapies to individuals with type 1 diabetes. Moreover, TrialNet uses its expertise and experience in clinical studies to increase efficiencies in the conduct of trials and to reduce the burden of participation on individuals and families. Herein, we highlight key contributions made by TrialNet toward a revised understanding of the natural history of disease and approaches to alter disease course and outline the consortium's plans for the future.
Project description:OBJECTIVE:We aimed to describe the natural history of residual insulin secretion in Type 1 Diabetes TrialNet participants over 4 years from diagnosis and relate this to previously reported alternative clinical measures reflecting β-cell secretory function. RESEARCH DESIGN AND METHODS:Data from 407 subjects from 5 TrialNet intervention studies were analyzed. All subjects had baseline stimulated C-peptide values of ≥0.2 nmol/L from mixed-meal tolerance tests (MMTTs). During semiannual visits, C-peptide values from MMTTs, HbA1c, and insulin doses were obtained. RESULTS:The percentage of individuals with stimulated C-peptide of ≥0.2 nmol/L or detectable C-peptide of ≥0.017 nmol/L continued to diminish over 4 years; this was markedly influenced by age. At 4 years, only 5% maintained their baseline C-peptide secretion. The expected inverse relationships between C-peptide and HbA1c or insulin doses varied over time and with age. Combined clinical variables, such as insulin-dose adjusted HbA1c (IDAA1C) and the relationship of IDAA1C to C-peptide, also were influenced by age and time from diagnosis. Models using these clinical measures did not fully predict C-peptide responses. IDAA1C ≤9 underestimated the number of individuals with stimulated C-peptide ≥0.2 nmol/L, especially in children. CONCLUSIONS:Current trials of disease-modifying therapy for type 1 diabetes should continue to use C-peptide as a primary end point of β-cell secretory function. Longer duration of follow-up is likely to provide stronger evidence of the effect of disease-modifying therapy on preservation of β-cell function.
Project description:BACKGROUND:The duration and patterns of ? cell dysfunction during type 1 diabetes (T1D) development have not been fully defined. METHODS:Metabolic measures derived from oral glucose tolerance tests (OGTTs) were compared between autoantibody-positive (aAb+) individuals followed in the TrialNet Pathway to Prevention study who developed diabetes after 5 or more years or less than 5 years of longitudinal follow-up (Progressors?5, n = 75; Progressors<5, n = 474) and 144 aAb-negative (aAb-) relatives. RESULTS:Mean age at study entry was 15.0 ± 12.6 years for Progressors?5; 12.0 ± 9.1 for Progressors<5; and 16.3 ± 10.4 for aAb- relatives. At baseline, Progressors?5 already exhibited significantly lower fasting C-peptide (P < 0.01), C-peptide AUC (P < 0.001), and early C-peptide responses (30- to 0-minute C-peptide; P < 0.001) compared with aAb- relatives, while 2-hour glucose (P = 0.03), glucose AUC (<0.001), and Index60 (<0.001) were all higher. Despite significant baseline impairment, metabolic measures in Progressors?5 were relatively stable until 2 years prior to T1D diagnosis, when there was accelerated C-peptide decline and rising glycemia from 2 years until diabetes diagnosis. Remarkably, patterns of progression within 3 years of diagnosis were nearly identical between Progressors?5 and Progressors<5. CONCLUSION:These data provide insight into the chronicity of ? cell dysfunction in T1D and indicate that ? cell dysfunction may precede diabetes diagnosis by more than 5 years in a subset of aAb+ individuals. Even among individuals with varying lengths of aAb positivity, our findings indicate that patterns of metabolic decline are uniform within the last 3 years of progression to T1D. TRIAL REGISTRATION:Clinicaltrials.gov NCT00097292. FUNDING:The Type 1 Diabetes TrialNet Study Group is a clinical trials network currently funded by the NIH through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Juvenile Diabetes Research Foundation.
Project description:We assessed the accuracy of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS), developed from the Diabetes Prevention Trial-Type 1 (DPT-1), in the TrialNet Natural History Study (TNNHS).Prediction accuracy of the DPTRS was assessed with receiver-operating characteristic curve areas. The type 1 diabetes cumulative incidence within the DPTRS intervals was compared between the TNNHS and DPT-1 cohorts.Receiver-operating characteristic curve areas for the DPTRS were substantial in the TNNHS (P < 0.001 at both 2 and 3 years). The type 1 diabetes cumulative incidence did not differ significantly between the TNNHS and DPT-1 cohorts within DPTRS intervals. In the TNNHS, 2-year and 3-year risks were low for DPTRS intervals <6.50 (<0.10 and <0.20, respectively). Thresholds ?7.50 were indicative of high risk in both cohorts (2-year risks: 0.49 in the TNNHS and 0.51 in DPT-1).The DPTRS is an accurate and robust predictor of type 1 diabetes in autoantibody-positive populations.
Project description:AIMS/HYPOTHESIS:The incidence of type 1 diabetes is increasing at a rate of 3-5% per year. Genetics cannot fully account for this trend, suggesting an influence of environmental factors. The accelerator hypothesis proposes an effect of metabolic factors on type 1 diabetes risk. To test this in the TrialNet Pathway to Prevention (PTP) cohort, we analysed the influence of BMI, weight status and insulin resistance on progression from single to multiple islet autoantibodies (Aab) and progression from normoglycaemia to diabetes. METHODS:HOMA1-IR was used to estimate insulin resistance in Aab-positive PTP participants. Cox proportional hazards models were used to evaluate the effects of BMI, BMI percentile (BMI%), weight status and HOMA1-IR on the progression of autoimmunity or the development of diabetes. RESULTS:Data from 1,310 single and 1,897 multiple Aab-positive PTP participants were included. We found no significant relationships between BMI, BMI%, weight status or HOMA1-IR and the progression from one to multiple Aabs. Similarly, among all Aab-positive participants, no significant relationships were found between BMI, weight status or HOMA1-IR and progression to diabetes. Diabetes risk was modestly increased with increasing BMI% among the entire cohort, in obese participants 13-20 years of age and with increasing HOMA1-IR in adult Aab-positive participants. CONCLUSIONS/INTERPRETATION:Analysis of the accelerator hypothesis in the TrialNet PTP cohort does not suggest a broad influence of metabolic variables on diabetes risk. Efforts to identify other potentially modifiable environmental factors should continue.
Project description:This study aimed to examine the associations of body mass index (BMI) across adult life with cognitive function in 2,637 participants aged 60 years or over from NHANES 2011-2014. The primary outcome was a composite score based on test scores on word list learning, animal naming, and digit symbol substitution. Exposures of interest included BMI at age 25, BMI 10 years before the survey, BMI at the survey (current BMI), and BMI burden calculated from age 25 to age at survey. BMI at age 25 was inversely associated with the composite score (?=-0.0271±0.0130 per kg/m2, P=0.038) and positively with low cognitive performance (odd ratio=1.04, 95% confidence interval: 1.01-1.07, P=0.010), defined as below 20 percentile of the composite score. Similar results were observed for BMI 10 years before the survey and BMI burden. Current BMI was positively associated with the composite score (?=0.0369±0.0113, P=0.001) and inversely associated with low cognitive performance (odd ratio=0.96, 95% confidence interval: 0.94-0.99, P=0.004). In conclusion, high BMI in early adult life is associated with low cognitive function in late life, which underscores the importance of a healthy body weight across the life course. The association between BMI and cognitive function at late life requires further investigation.
Project description:BACKGROUND:Type 1 diabetes (T1D) TrialNet is a National Institutes of Health-sponsored clinical trial network aimed at altering the disease course of T1D. The purpose of this study is to evaluate age-dependent heterogeneity in clinical, metabolic and immunologic characteristics of individuals with recent-onset T1D, to identify cohorts of interest and to aid in planning of future studies. METHODS:Eight hundred eighty-three individuals with recent-onset T1D involved in five TrialNet studies were categorized by age as follows: ?18 years, 12-17 years, 8-12 years and <8 years. Data were compared with healthy age-matched subjects in the National Health and Nutrition Examination Survey. RESULTS:Only 2.0% of the individuals overall were excluded from trial participation because of insufficient C-peptide values (<0.2?pmol/mL). A disproportionate number of these subjects were <8?years old. Leukopenia was present in 21.2% of individuals and lymphopenia in 11.6%; these frequencies were markedly higher than age-matched healthy National Health and Nutrition Examination Survey population. Of the cohort, 24.5% were overweight or obese. Neither high-risk human leukocyte antigen type DR3 nor DR4 was present in 31% of adults and 21% of children. CONCLUSIONS:The ability of recent-onset T1D patients to meet key entry criteria for TrialNet studies, including C-peptide >0.2?pmol/mL, varies by age. Lower C-peptide level requirements for younger participants and other aspects of heterogeneity of recent-onset T1D patients, such as white blood cell count abnormalities and body mass index should be considered in the design of future clinical studies.