Peripheral immune circadian variation, synchronisation and possible dysrhythmia in established type 1 diabetes.

AIMS/HYPOTHESIS: The circadian clock influences both diabetes and immunity. Our goal in this study was to characterise more thoroughly the circadian patterns of immune cell populations and cytokines that are particularly relevant to the immune pathology of type 1 diabetes and thus fill in a current gap in our understanding of this disease. METHODS: Ten individuals with established type 1 diabetes (mean disease duration 11 years, age 18-40 years, six female) participated in a circadian sampling protocol, each providing six blood samples over a 24 h period. RESULTS: Daily ranges of population frequencies were sometimes large and possibly clinically significant. Several immune populations, such as dendritic cells, CD4 and CD8 T cells and their effector memory subpopulations, CD4 regulatory T cells, B cells and cytokine IL-6, exhibited statistically significant circadian rhythmicity. In a comparison with historical healthy control individuals, but using shipped samples, we observed that participants with type 1 diabetes had statistically significant phase shifts occurring in the time of peak occurrence of B cells (+4.8 h), CD4 and CD8 T cells (~ +5 h) and their naive and effector memory subsets (~ +3.3 to +4.5 h), and regulatory T cells (+4.1 h). An independent streptozotocin murine experiment confirmed the phase shifting of CD8 T cells and suggests that circadian dysrhythmia in type 1 diabetes might be an effect and not a cause of the disease. CONCLUSIONS/INTERPRETATION: Future efforts investigating this newly described aspect of type 1 diabetes in human participants are warranted. Peripheral immune populations should be measured near the same time of day in order to reduce circadian-related variation.

Efficacy of GAD-alum immunotherapy associated with HLA-DR3-DQ2 in recently diagnosed type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this study was to determine if retention of C-peptide following immunotherapy using recombinant GAD65 conjugated to aluminium hydroxide (GAD-alum) is influenced by HLA risk haplotypes DR3-DQ2 and DR4-DQ8. METHODS: HLA-dependent treatment effect of GAD-alum therapy on C-peptide retention in individuals with recent-onset type 1 diabetes was evaluated using individual-level patient data from three placebo-controlled, randomised clinical trials using a mixed repeated measures model. RESULTS: A significant and dose-dependent effect was observed in individuals positive for the genotypes that include HLA-DR3-DQ2 but not HLA-DR4-DQ8 and in the broader subgroup of individuals positive for all genotypes that include HLA-DR3-DQ2 (i.e. including those also positive for HLA-DR4-DQ8). Higher doses (three or four injections) showed a treatment effect ratio of 1.596 (95% CI 1.132, 2.249; adjusted p = 0.0035) and 1.441 (95% CI 1.188, 1.749; adjusted p = 0.0007) vs placebo for the two respective HLA subgroups. CONCLUSIONS/INTERPRETATION: GAD65-specific immunotherapy has a significant effect on C-peptide retention in individuals with recent-onset type 1 diabetes who have the DR3-DQ2 haplotype. Graphical abstract.

Costimulation Blockade Disrupts CD4+ T Cell Memory Pathways and Uncouples Their Link to Decline in ß-Cell Function in Type 1 Diabetes.

We previously reported that costimulation blockade by abatacept limits the decline of ß-cell function and the frequency of circulating CD4+ central memory T cells (TCM) (CD45RO+CD62L+) in new-onset type 1 diabetes. In human subjects receiving placebo, we found a significant association between an increase in CD4+ TCM cells and the decline of ß-cell function. To extend and refine these findings, we examined changes in human CD4+ and CD8+ naive and memory T cell subsets at greater resolution using polychromatic flow and mass cytometry. In the placebo group, we successfully reproduced the original finding of a significant association between TCM and ß-cell function and extended this to other T cell subsets. Furthermore, we show that abatacept treatment significantly alters the frequencies of a majority of CD4+ conventional and regulatory T cell subsets; in general, Ag-naive subsets increase and Ag-experienced subsets decrease, whereas CD8+ T cell subsets are relatively resistant to drug effects, indicating a lesser reliance on CD28-mediated costimulation. Importantly, abatacept uncouples the relationship between changes in T cell subsets and ß-cell function that is a component of the natural history of the disease. Although these data suggest immunological markers for predicting change in ß-cell function in type 1 diabetes, the finding that abatacept blunts this relationship renders the biomarkers nonpredictive for this type of therapy. In sum, our findings point to a novel mechanism of action for this successful immunotherapy that may guide other disease-modifying approaches for type 1 diabetes.

Synchronization of the Normal Human Peripheral Immune System: A Comprehensive Circadian Systems Immunology Analysis.

In this study, we sought to fill an important gap in fundamental immunology research by conducting a comprehensive systems immunology analysis of daily variation in the normal human peripheral immune system. Although variation due to circadian rhythmicity was not a significant source of variation in daily B-cell levels or any CD4+ functional subset, it accounted for more than 25% of CD4+ regulatory T-cell variation and over 50% of CD8+ central memory variation. Circadian rhythmicity demonstrated phase alignment within functional phenotypes. In addition, we observed that previously-described mechanistic relationships can also appear in the peripheral system as phase shifting in rhythmic patterns. We identified a set of immune factors which are ubiquitously correlated with other factors and further analysis also identified a tightly-correlated "core" set whose relational structure persisted after analytically removing circadian-related variation. This core set consisted of CD8+ and its subpopulations and the NK population. In sum, the peripheral immune system can be conceptualized as a dynamic, interconnected wave-field repeating its pattern on a daily basis. Our data provide a comprehensive inventory of synchronization and correlation within this wave-field and we encourage use of our data to discover unknown mechanistic relationships which can then be tested in the laboratory.

Autoreactive T effector memory differentiation mirrors ß cell function in type 1 diabetes.

In type 1 diabetes, cytotoxic CD8+ T cells with specificity for ß cell autoantigens are found in the pancreatic islets, where they are implicated in the destruction of insulin-secreting ß cells. In contrast, the disease relevance of ß cell-reactive CD8+ T cells that are detectable in the circulation, and their relationship to ß cell function, are not known. Here, we tracked multiple, circulating ß cell-reactive CD8+ T cell subsets and measured ß cell function longitudinally for 2 years, starting immediately after diagnosis of type 1 diabetes. We found that change in ß cell-specific effector memory CD8+ T cells expressing CD57 was positively correlated with C-peptide change in subjects below 12 years of age. Autoreactive CD57+ effector memory CD8+ T cells bore the signature of enhanced effector function (higher expression of granzyme B, killer-specific protein of 37 kDa, and CD16, and reduced expression of CD28) compared with their CD57- counterparts, and network association modeling indicated that the dynamics of ß cell-reactive CD57+ effector memory CD8+ T cell subsets were strongly linked. Thus, coordinated changes in circulating ß cell-specific CD8+ T cells within the CD57+ effector memory subset calibrate to functional insulin reserve in type 1 diabetes, providing a tool for immune monitoring and a mechanism-based target for immunotherapy.

GAD vaccine reduces insulin loss in recently diagnosed type 1 diabetes: findings from a Bayesian meta-analysis.

AIMS/HYPOTHESIS: GAD is a major target of the autoimmune response that occurs in type 1 diabetes mellitus. Randomised controlled clinical trials of a GAD + alum vaccine in human participants have so far given conflicting results. METHODS: In this study, we sought to see whether a clearer answer to the question of whether GAD65 has an effect on C-peptide could be reached by combining individual-level data from the randomised controlled trials using Bayesian meta-analysis to estimate the probability of a positive biological effect (a reduction in C-peptide loss compared with placebo approximately 1 year after the GAD vaccine). RESULTS: We estimate that there is a 98% probability that 20 µg GAD with alum administered twice yields a positive biological effect. The effect is probably a 15-20% reduction in the loss of C-peptide at approximately 1 year after treatment. This translates to an annual expected loss of between -0.250 and -0.235 pmol/ml in treated patients compared with an expected 2 h AUC loss of -0.294 pmol/ml at 1 year for untreated newly diagnosed patients. CONCLUSIONS/INTERPRETATION: The biological effect of this vaccination should be developed further in order to reach clinically desirable reductions in insulin loss in patients recently diagnosed with type 1 diabetes.

Use of Dried Capillary Blood Sampling for Islet Autoantibody Screening in Relatives: A Feasibility Study.

BACKGROUND: Islet autoantibody testing provides the basis for assessment of risk of progression to type 1 diabetes. We set out to determine the feasibility and acceptability of dried capillary blood spot-based screening to identify islet autoantibody-positive relatives potentially eligible for inclusion in prevention trials. MATERIALS AND METHODS: Dried blood spot (DBS) and venous samples were collected from 229 relatives participating in the TrialNet Pathway to Prevention Study. Both samples were tested for glutamic acid decarboxylase, islet antigen 2, and zinc transporter 8 autoantibodies, and venous samples were additionally tested for insulin autoantibodies and islet cell antibodies. We defined multiple autoantibody positive as two or more autoantibodies in venous serum and DBS screen positive if one or more autoantibodies were detected. Participant questionnaires compared the sample collection methods. RESULTS: Of 44 relatives who were multiple autoantibody positive in venous samples, 42 (95.5%) were DBS screen positive, and DBS accurately detected 145 of 147 autoantibody-negative relatives (98.6%). Capillary blood sampling was perceived as more painful than venous blood draw, but 60% of participants would prefer initial screening using home fingerstick with clinic visits only required if autoantibodies were found. CONCLUSIONS: Capillary blood sampling could facilitate screening for type 1 diabetes prevention studies.

Statistical considerations when analyzing biomarker data.

Biomarkers have become, and will continue to become, increasingly important to clinical immunology research. Yet, biomarkers often present new problems and raise new statistical and study design issues to scientists working in clinical immunology. In this paper I discuss statistical considerations related to the important biomarker problems of: 1) The design and analysis of clinical studies which seek to determine whether changes from baseline in a biomarker are associated with changes in a metabolic outcome; 2) The conditions that are required for a biomarker to be considered a "surrogate"; 3) Considerations that arise when analyzing whether or not a predictive biomarker could act as a surrogate endpoint; 4) Biomarker timing relative to the clinical endpoint; 5) The problem of analyzing studies that measure many biomarkers from few subjects; and, 6) The use of statistical models when analyzing biomarker data arising from count data.

The development and utility of a novel scale that quantifies the glycemic progression toward type 1 diabetes over 6 months.

OBJECTIVE: We developed a scale to serve as a potential end point for 6-month glycemic progression (PS6M) toward type 1 diabetes (T1D) in autoantibody-positive relatives of individuals with T1D. RESEARCH DESIGN AND METHODS: The PS6M was developed from Diabetes Prevention Trial-Type 1 (DPT-1) data and tested in the TrialNet Pathway to Prevention Study (PTP). It is the difference between 6-month glucose sum values (30-120 min oral glucose tolerance test values) and values predicted for nonprogressors. RESULTS: The PS6M predicted T1D in the PTP (P < 0.001). The area under the receiver operating chacteristic curve was greater (P < 0.001) for the PS6M than for the baseline-to-6-month difference. PS6M values were higher in those with two or more autoantibodies, 30-0 min C-peptide values <2.00 ng/mL, or DPT-1 Risk Scores >7.00 (P < 0.001 for all). CONCLUSIONS: The PS6M is an indicator of short-term glycemic progression to T1D that could be a useful tool for assessing preventive treatments and biomarkers.

ß cell death and dysfunction during type 1 diabetes development in at-risk individuals.

UNLABELLED: Role of the funding source: Funding from the NIH was used for support of the participating clinical centers and the coordinating center. The funding source did not participate in the collection or the analysis of the data. BACKGROUND: The ß cell killing that characterizes type 1 diabetes (T1D) is thought to begin years before patients present clinically with metabolic decompensation; however, this primary pathologic process of the disease has not been measured. METHODS: Here, we measured ß cell death with an assay that detects ß cell-derived unmethylated insulin (INS) DNA. Using this assay, we performed an observational study of 50 participants from 2 cohorts at risk for developing T1D from the TrialNet Pathway to Prevention study and of 4 subjects who received islet autotransplants. RESULTS: In at-risk subjects, those who progressed to T1D had average levels of unmethylated INS DNA that were elevated modestly compared with those of healthy control subjects. In at-risk individuals that progressed to T1D, the observed increases in unmethylated INS DNA were associated with decreases in insulin secretion, indicating that the changes in unmethylated INS DNA are indicative of ß cell killing. Subjects at high risk for T1D had levels of unmethylated INS DNA that were higher than those of healthy controls and higher than the levels of unmethylated INS DNA in the at-risk progressor and at-risk nonprogressor groups followed for 4 years. Evaluation of insulin secretory kinetics also distinguished high-risk subjects who progressed to overt disease from those who did not. CONCLUSION: We conclude that a blood test that measures unmethylated INS DNA serves as a marker of active ß cell killing as the result of T1D-associated autoimmunity. Together, the data support the concept that ß cell killing occurs sporadically during the years prior to diagnosis of T1D and is more intense in the peridiagnosis period. TRIAL REGISTRATION: Clinicaltrials.gov NCT00097292. FUNDING: Funding was from the NIH, the Juvenile Diabetes Research Foundation, and the American Diabetes Association.

Heterogeneity in recent-onset type 1 diabetes - a clinical trial perspective.

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.

A new approach for diagnosing type 1 diabetes in autoantibody-positive individuals based on prediction and natural history.

OBJECTIVE: We assessed whether type 1 diabetes (T1D) can be diagnosed earlier using a new approach based on prediction and natural history in autoantibody-positive individuals. RESEARCH DESIGN AND METHODS: Diabetes Prevention Trial-Type 1 (DPT-1) and TrialNet Natural History Study (TNNHS) participants were studied. A metabolic index, the T1D Diagnostic Index60 (Index60), was developed from 2-h oral glucose tolerance tests (OGTTs) using the log fasting C-peptide, 60-min C-peptide, and 60-min glucose. OGTTs with Index60 ≥2.00 and 2-h glucose <200 mg/dL (Ind60+Only) were compared with Index60 <2.00 and 2-h glucose ≥200 mg/dL (2hglu+Only) OGTTs as criteria for T1D. Individuals were assessed for C-peptide loss from the first Ind60+Only OGTT to diagnosis. RESULTS: Areas under receiver operating characteristic curves were significantly higher for Index60 than for the 2-h glucose (P < 0.001 for both DPT-1 and the TNNHS). As a diagnostic criterion, sensitivity was higher for Ind60+Only than for 2hglu+Only (0.44 vs. 0.15 in DPT-1; 0.26 vs. 0.17 in the TNNHS) OGTTs. Specificity was somewhat higher for 2hglu+Only OGTTs in DPT-1 (0.97 vs. 0.91) but equivalent in the TNNHS (0.98 for both). Positive and negative predictive values were higher for Ind60+Only OGTTs in both studies. Postchallenge C-peptide levels declined significantly at each OGTT time point from the first Ind60+Only OGTT to the time of standard diagnosis (range -22 to -34% in DPT-1 and -14 to -27% in the TNNHS). C-peptide and glucose patterns differed markedly between Ind60+Only and 2hglu+Only OGTTs. CONCLUSIONS: An approach based on prediction and natural history appears to have utility for diagnosing T1D.

Reduction in CD4 central memory T-cell subset in costimulation modulator abatacept-treated patients with recent-onset type 1 diabetes is associated with slower C-peptide decline.

We previously reported that continuous 24-month costimulation blockade by abatacept significantly slows the decline of ß-cell function after diagnosis of type 1 diabetes. In a mechanistic extension of that study, we evaluated peripheral blood immune cell subsets (CD4, CD8-naive, memory and activated subsets, myeloid and plasmacytoid dendritic cells, monocytes, B lymphocytes, CD4(+)CD25(high) regulatory T cells, and invariant NK T cells) by flow cytometry at baseline and 3, 6, 12, 24, and 30 months after treatment initiation to discover biomarkers of therapeutic effect. Using multivariable analysis and lagging of longitudinally measured variables, we made the novel observation in the placebo group that an increase in central memory (CM) CD4 T cells (CD4(+)CD45R0(+)CD62L(+)) during a preceding visit was significantly associated with C-peptide decline at the subsequent visit. These changes were significantly affected by abatacept treatment, which drove the peripheral contraction of CM CD4 T cells and the expansion of naive (CD45R0(-)CD62L(+)) CD4 T cells in association with a significantly slower rate of C-peptide decline. The findings show that the quantification of CM CD4 T cells can provide a surrogate immune marker for C-peptide decline after the diagnosis of type 1 diabetes and that costimulation blockade may exert its beneficial therapeutic effect via modulation of this subset.

Recommendations for the definition of clinical responder in insulin preservation studies.

Clinical responder studies should contribute to the translation of effective treatments and interventions to the clinic. Since ultimately this translation will involve regulatory approval, we recommend that clinical trials prespecify a responder definition that can be assessed against the requirements and suggestions of regulatory agencies. In this article, we propose a clinical responder definition to specifically assist researchers and regulatory agencies in interpreting the clinical importance of statistically significant findings for studies of interventions intended to preserve ß-cell function in newly diagnosed type 1 diabetes. We focus on studies of 6-month ß-cell preservation in type 1 diabetes as measured by 2-h-stimulated C-peptide. We introduce criteria (bias, reliability, and external validity) for the assessment of responder definitions to ensure they meet U.S. Food and Drug Administration and European Medicines Agency guidelines. Using data from several published TrialNet studies, we evaluate our definition (no decrease in C-peptide) against published alternatives and determine that our definition has minimum bias with external validity. We observe that reliability could be improved by using changes in C-peptide later than 6 months beyond baseline. In sum, to support efficacy claims of ß-cell preservation therapies in type 1 diabetes submitted to U.S. and European regulatory agencies, we recommend use of our definition.

Use of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for improving the accuracy of the risk classification of type 1 diabetes.

OBJECTIVE We studied the utility of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for improving the accuracy of type 1 diabetes (T1D) risk classification in TrialNet Natural History Study (TNNHS) participants. RESEARCH DESIGN AND METHODS The cumulative incidence of T1D was compared between normoglycemic individuals with DPTRS values >7.00 and dysglycemic individuals in the TNNHS (n = 991). It was also compared between individuals with DPTRS values <7.00 or >7.00 among those with dysglycemia and those with multiple autoantibodies in the TNNHS. DPTRS values >7.00 were compared with dysglycemia for characterizing risk in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 670) and TNNHS participants. The reliability of DPTRS values >7.00 was compared with dysglycemia in the TNNHS. RESULTS The cumulative incidence of T1D for normoglycemic TNNHS participants with DPTRS values >7.00 was comparable to those with dysglycemia. Among those with dysglycemia, the cumulative incidence was much higher (P < 0.001) for those with DPTRS values >7.00 than for those with values <7.00 (3-year risks: 0.16 for <7.00 and 0.46 for >7.00). Dysglycemic individuals in DPT-1 were at much higher risk for T1D than those with dysglycemia in the TNNHS (P < 0.001); there was no significant difference in risk between the studies among those with DPTRS values >7.00. The proportion in the TNNHS reverting from dysglycemia to normoglycemia at the next visit was higher than the proportion reverting from DPTRS values >7.00 to values <7.00 (36 vs. 23%). CONCLUSIONS DPTRS thresholds can improve T1D risk classification accuracy by identifying high-risk normoglycemic and low-risk dysglycemic individuals. The 7.00 DPTRS threshold characterizes risk more consistently between populations and has greater reliability than dysglycemia.

The prediction of type 1 diabetes by multiple autoantibody levels and their incorporation into an autoantibody risk score in relatives of type 1 diabetic patients.

OBJECTIVE: We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. RESULTS: The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23-3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78-0.90] at 2 years, 0.81 [0.74-0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88-0.98] at 2 years, 0.91 [0.83-0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). CONCLUSIONS: These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D.

Acceleration of the loss of the first-phase insulin response during the progression to type 1 diabetes in diabetes prevention trial-type 1 participants.

We studied the change in the first-phase insulin response (FPIR) during the progression to type 1 diabetes (T1D). Seventy-four oral insulin trial progressors to T1D from the Diabetes Prevention Trial-Type 1 with at least one FPIR measurement after baseline and before diagnosis were studied. The FPIR was examined longitudinally in 26 progressors who had FPIR measurements during each of the 3 years before diagnosis. The association between the change from the baseline FPIR to the last FPIR and time to diagnosis was studied in the remainder (n = 48). The 74 progressors had lower baseline FPIR values than nonprogressors (n = 270), with adjustments made for age and BMI. In the longitudinal analysis of the 26 progressors, there was a greater decline in the FPIR from 1.5 to 0.5 years before diagnosis than from 2.5 to 1.5 years before diagnosis. This accelerated decline was also evident in a regression analysis of the 48 remaining progressors in whom the rate of decline became more marked with the approaching diagnosis. The patterns of decline were similar between the longitudinal and regression analyses. There is an acceleration of decline in the FPIR during the progression to T1D, which becomes especially marked between 1.5 and 0.5 years before diagnosis.

Prognostic accuracy of immunologic and metabolic markers for type 1 diabetes in a high-risk population: receiver operating characteristic analysis.

OBJECTIVE: To establish and compare the prognostic accuracy of immunologic and metabolic markers in predicting onset of type 1 diabetes in those with high risk in a prospective study. RESEARCH DESIGN AND METHODS: A total of 339 subjects from the Diabetes Prevention Trial-Type 1 (DPT-1) parenteral study, who were islet cell antibody (ICA)-positive, with low first-phase insulin response (FPIR) and/or abnormal glucose tolerance at baseline, were followed until clinical diabetes onset or study end (5-year follow-up). The prognostic performance of biomarkers was estimated using receiver operating characteristic (ROC) curve analysis and compared with nonparametric testing of ROC curve areas. Pearson correlation was used to assess the relationship between the markers. RESULTS: Individually, insulin autoantibody titer, ICA512A titer, peak C-peptide, 2-h glucose, FPIR, and FPIR/homeostasis model assessment of insulin resistance provided modest but significant prognostic values for 5-year risk with a similar level of area under ROC curve ranging between 0.61 and 0.67. The combination of 2-h glucose, peak C-peptide, and area under the curve C-peptide significantly improved the prognostic accuracy compared with any solitary index (P < 0.05) with an area under ROC curve of 0.76 (95% CI 0.70-0.81). The addition of antibody titers and/or intravenous glucose tolerance test (IVGTT) markers did not increase the prognostic accuracy further (P = 0.46 and P = 0.66, respectively). CONCLUSIONS: The combination of metabolic markers derived from the oral glucose tolerance test improved accuracy in predicting progression to type 1 diabetes in a population with ICA positivity and abnormal metabolism. The results indicate that the autoimmune activity may not alter the risk of type 1 diabetes after metabolic function has deteriorated. Future intervention trials may consider eliminating IVGTT measurements as an effective cost-reduction strategy for prognostic purposes.