HOMA-IR and the Matsuda Index as predictors of progression to type 1 diabetes in autoantibody-positive relatives.

AIM/HYPOTHESIS: We assessed whether HOMA-IR and the Matsuda Index are associated with transitions through stages of type 1 diabetes. METHODS: Autoantibody (AAb)-positive relatives of individuals with type 1 diabetes (n=6256) from the TrialNet Pathway to Prevention were studied. Associations of indicators of insulin resistance (HOMA-IR) and insulin sensitivity (Matsuda Index) with BMI percentile (BMIp) and age were assessed with adjustments for measures of insulin secretion, Index60 and insulinogenic index (IGI). Cox regression was used to determine if tertiles of HOMA-IR and Matsuda Index predicted transitions from Not Staged (<2 AAbs) to Stage 1 (≥2 AAbs and normoglycaemia), from Stage 1 to Stage 2 (≥2 AAbs with dysglycaemia), and progression to Stage 3 (diabetes as defined by WHO/ADA criteria). RESULTS: There were strong associations of HOMA-IR (positive) and Matsuda Index (inverse) with baseline age and BMIp (p<0.0001). After adjustments for Index60, transitioning from Stage 1 to Stage 2 was associated with higher HOMA-IR and lower Matsuda Index (HOMA-IR: HR=1.71, p<0.0001; Matsuda Index, HR=0.40, p<0.0001), as with progressing from Stages 1 or 2 to Stage 3 (HOMA-IR: HR=1.98, p<0.0001; Matsuda Index: HR=0.46, p<0.0001). Without adjustments, associations of progression to Stage 3 were inverse for HOMA-IR and positive for Matsuda Index, opposite in directionality with adjustments. When IGI was used in place of Index60, the findings were similar. CONCLUSIONS/INTERPRETATION: Progression to Stages 2 and 3 of type 1 diabetes increases with HOMA-IR and decreases with the Matsuda Index after adjustments for insulin secretion. Indicators of insulin secretion appear helpful for interpreting associations of progression to type 1 diabetes with HOMA-IR or the Matsuda Index in AAb-positive relatives.

Index60 as an additional diagnostic criterion for type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both. METHODS: We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165]. RESULTS: Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%). CONCLUSIONS/INTERPRETATION: Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.

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

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

Associations of HbA1c with the timing of C-peptide responses during the oral glucose tolerance test at the diagnosis of type 1 diabetes.

BACKGROUND: In new onset type 1 diabetes (T1D), overall C-peptide measures such as area under the curve (AUC) C-peptide and peak C-peptide are useful for estimating the extent of ß-cell dysfunction, and for assessing responses to intervention therapy. However, measures of the timing of C-peptide responsiveness could have additional value. OBJECTIVES: We assessed the contribution of the timing of C-peptide responsiveness during oral glucose tolerance tests (OGTTs) to hemoglobin A1c (HbA1c) variation at T1D diagnosis. METHODS: We analyzed data from 85 individuals <18 years with OGTTs and HbA1c measurements at diagnosis. Overall [AUC and peak C-peptide] and timing measures [30-0 minute C-peptide (early); 60 to 120 minute C-peptide sum-30 minutes (late); 120/30 C-peptide; time to peak C-peptide] were utilized. RESULTS: At diagnosis, the mean (±SD) age was 11.2 ± 3.3 years, body mass index (BMI)-z was 0.4 ± 1.1, 51.0% were male. The average HbA1c was 43.54 ± 8.46 mmol/mol (6.1 ± 0.8%). HbA1c correlated inversely with the AUC C-peptide (P < 0.001), peak C-peptide (P < 0.001), early and late C-peptide responses (P < 0.001 each), and 120/30 C-peptide (P < 0.001). Those with a peak C-peptide occurring at ≤60 minutes had higher HbA1c values than those with peaks later (P = 0.003). HbA1c variance was better explained with timing measures added to regression models (R2 = 11.6% with AUC C-peptide alone; R2 = 20.0% with 120/30 C-peptide added; R2 = 13.7% with peak C-peptide alone, R2 = 20.4% with timing of the peak added). Similar associations were seen between the 2-hour glucose and the C-peptide measures. CONCLUSIONS: These findings show that the addition of timing measures of C-peptide responsiveness better explains HbA1c variation at diagnosis than standard measures alone.

The shape of the glucose concentration curve during an oral glucose tolerance test predicts risk for type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to examine: (1) whether specific glucose-response curve shapes during OGTTs are predictive of type 1 diabetes development; and (2) the extent to which the glucose-response curve is influenced by insulin secretion. METHODS: Autoantibody-positive relatives of people with type 1 diabetes whose baseline OGTT met the definition of a monophasic or biphasic glucose-response curve were followed for the development of type 1 diabetes (n = 2627). A monophasic curve was defined as an increase in OGTT glucose between 30 and 90 min followed by a decline of ≥ 0.25 mmol/l between 90 and 120 min. A biphasic response curve was defined as a decrease in glucose after an initial increase, followed by a second increase of ≥ 0.25 mmol/l. Associations of type 1 diabetes risk with glucose curve shapes were examined using cumulative incidence curve comparisons and proportional hazards regression. C-peptide responses were compared with and without adjustments for potential confounders. RESULTS: The majority of participants had a monophasic curve at baseline (n = 1732 [66%] vs n = 895 [34%]). The biphasic group had a lower cumulative incidence of type 1 diabetes (p < 0.001), which persisted after adjustments for age, sex, BMI z score and number of autoantibodies (p < 0.001). Among the monophasic group, the risk of type 1 diabetes was greater for those with a glucose peak at 90 min than for those with a peak at 30 min; the difference persisted after adjustments (p < 0.001). Compared with the biphasic group, the monophasic group had a lower early C-peptide (30-0 min) response, a lower C-peptide index (30-0 min C-peptide/30-0 min glucose), as well as a greater 2 h C-peptide level (p < 0.001 for all). CONCLUSIONS/INTERPRETATION: Those with biphasic glucose curves have a lower risk of progression to type 1 diabetes than those with monophasic curves, and the risk among the monophasic group is increased when the glucose peak occurs at 90 min than at 30 min. Differences in glucose curve shapes between the monophasic and biphasic groups appear to be related to C-peptide responses.

The Effect of Age on the Progression and Severity of Type 1 Diabetes: Potential Effects on Disease Mechanisms.

PURPOSE OF REVIEW: To explore the impact of age on type 1 diabetes (T1D) pathogenesis. RECENT FINDINGS: Children progress more rapidly from autoantibody positivity to T1D and have lower C-peptide levels compared to adults. In histological analysis of post-mortem pancreata, younger age of diagnosis is associated with reduced numbers of insulin containing islets and a hyper-immune CD20hi infiltrate. Moreover compared to adults, children exhibit decreased immune regulatory function and increased engagement and trafficking of autoreactive CD8+ T cells, and age-related differences in ß cell vulnerability may also contribute to the more aggressive immune phenotype observed in children. To account for some of these differences, HLA and non-HLA genetic loci that influence multiple disease characteristics, including age of onset, are being increasingly characterized. The exception of T1D as an autoimmune disease more prevalent in children than adults results from a combination of immune, metabolic, and genetic factors. Age-related differences in T1D pathology have important implications for better tailoring of immunotherapies.

The influence of body mass index and age on C-peptide at the diagnosis of type 1 diabetes in children who participated in the diabetes prevention trial-type 1.

BACKGROUND/OBJECTIVE: The extent of influence of BMI and age on C-peptide at the diagnosis of type 1 diabetes (T1D) is unknown. We thus studied the impact of body mass index Z-scores (BMIZ) and age on C-peptide measures at and soon after the diagnosis of T1D. METHODS: Data from Diabetes Prevention Trial-Type 1 (DPT-1) participants <18.0 years at diagnosis was analyzed. Analyses examined associations of C-peptide measures with BMIZ and age in 2 cohorts: oral glucose tolerance tests (OGTTs) at diagnosis (n = 99) and mixed meal tolerance tests (MMTTs) <6 months after diagnosis (n = 80). Multivariable linear regression was utilized. RESULTS: Fasting and area under the curve (AUC) C-peptide from OGTTs (n = 99) at diagnosis and MMTTs (n = 80) after diagnosis were positively associated with BMIZ and age (P < .001 for all). Associations persisted when BMIZ and age were included as independent variables in regression models (P < .001 for all). BMIZ and age explained 31%-47% of the variance of C-peptide measures. In an example, 2 individuals with identical AUC C-peptide values had an approximate 5-fold difference in values after adjustments for BMIZ and age. The association between fasting glucose and C-peptide decreased markedly when fasting C-peptide values were adjusted (r = 0.30, P < .01 to r = 0.07, n.s.). CONCLUSIONS: C-peptide measures are strongly and independently related to BMIZ and age at and soon after the diagnosis of T1D. Adjustments for BMIZ and age cause substantial changes in C-peptide values, and impact the association between glycemia and C-peptide. Such adjustments can improve assessments of ß-cell impairment at diagnosis.

The relationship between BMI and insulin resistance and progression from single to multiple autoantibody positivity and type 1 diabetes among TrialNet Pathway to Prevention participants.

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.

The development, validation, and utility of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS).

This report details the development, validation, and utility of the Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score (DPTRS) for type 1 diabetes (T1D). Proportional hazards regression was used to develop the DPTRS model which includes the glucose and C-peptide sums from oral glucose tolerance tests at 30, 60, 90, and 120 min, the log fasting C-peptide, age, and the log BMI. The DPTRS was externally validated in the TrialNet Natural History Study cohort (TNNHS). In a study of the application of the DPTRS, the findings showed that it could be used to identify normoglycemic individuals who were at a similar risk for T1D as those with dysglycemia. The DPTRS could also be used to identify lower risk dysglycemic individuals. Risk estimates of individuals deemed to be at higher risk according to DPTRS values did not differ significantly between the DPT-1 and the TNNHS; whereas, the risk estimates for those with dysglycemia were significantly higher in DPT-1. Individuals with very high DPTRS values were found to be at such marked risk for T1D that they could reasonably be considered to be in a pre-diabetic state. The findings indicate that the DPTRS has utility in T1D prevention trials and for identifying pre-diabetic individuals.

Early Metabolic Endpoints Identify Persistent Treatment Efficacy in Recent-Onset Type 1 Diabetes Immunotherapy Trials.

OBJECTIVE: Mixed-meal tolerance test-stimulated area under the curve (AUC) C-peptide at 12-24 months represents the primary end point for nearly all intervention trials seeking to preserve ß-cell function in recent-onset type 1 diabetes. We hypothesized that participant benefit might be detected earlier and predict outcomes at 12 months posttherapy. Such findings would support shorter trials to establish initial efficacy. RESEARCH DESIGN AND METHODS: We examined data from six Type 1 Diabetes TrialNet immunotherapy randomized controlled trials in a post hoc analysis and included additional stimulated metabolic indices beyond C-peptide AUC. We partitioned the analysis into successful and unsuccessful trials and analyzed the data both in the aggregate as well as individually for each trial. RESULTS: Among trials meeting their primary end point, we identified a treatment effect at 3 and 6 months when using C-peptide AUC (P = 0.030 and P < 0.001, respectively) as a dynamic measure (i.e., change from baseline). Importantly, no such difference was seen in the unsuccessful trials. The use of C-peptide AUC as a 6-month dynamic measure not only detected treatment efficacy but also suggested long-term C-peptide preservation (R2 for 12-month C-peptide AUC adjusted for age and baseline value was 0.80, P < 0.001), and this finding supported the concept of smaller trial sizes down to 54 participants. CONCLUSIONS: Early dynamic measures can identify a treatment effect among successful immune therapies in type 1 diabetes trials with good long-term prediction and practical sample size over a 6-month period. While external validation of these findings is required, strong rationale and data exist in support of shortening early-phase clinical trials.

Phenotypes Associated With Zones Defined by Area Under the Curve Glucose and C-peptide in a Population With Islet Autoantibodies.

OBJECTIVE: Metabolic zones were developed to characterize heterogeneity of individuals with islet autoantibodies. RESEARCH DESIGN AND METHODS: Baseline 2-h oral glucose tolerance test data from 6,620 TrialNet Pathway to Prevention Study (TNPTP) autoantibody-positive participants (relatives of individuals with type 1 diabetes) were used to form 25 zones from five area under the curve glucose (AUCGLU) rows and five area under the curve C-peptide (AUCPEP) columns. Zone phenotypes were developed from demographic, metabolic, autoantibody, HLA, and risk data. RESULTS: As AUCGLU increased, changes of glucose and C-peptide response curves (from mean glucose and mean C-peptide values at 30, 60, 90, and 120 min) were similar within the five AUCPEP columns. Among the zones, 5-year risk for type 1 diabetes was highly correlated with islet antigen 2 antibody prevalence (r = 0.96, P < 0.001). Disease risk decreased markedly in the highest AUCGLU row as AUCPEP increased (0.88-0.41; P < 0.001 from lowest AUCPEP column to highest AUCPEP column). AUCGLU correlated appreciably less with Index60 (an indicator of insulin secretion) in the highest AUCPEP column (r = 0.33) than in other columns (r ≥ 0.78). AUCGLU was positively related to "fasting glucose × fasting insulin" and to "fasting glucose × fasting C-peptide" (indicators of insulin resistance) before and after adjustments for Index60 (P < 0.001). CONCLUSIONS: Phenotypes of 25 zones formed from AUCGLU and AUCPEP were used to gain insights into type 1 diabetes heterogeneity. Zones were used to examine GCRC changes with increasing AUCGLU, associations between risk and autoantibody prevalence, the dependence of glucose as a predictor of risk according to C-peptide, and glucose heterogeneity from contributions of insulin secretion and insulin resistance.

Index60 Is Superior to HbA1c for Identifying Individuals at High Risk for Type 1 Diabetes.

CONTEXT: HbA1c from ≥ 5.7% to < 6.5% (39-46 mmol/mol) indicates prediabetes according to American Diabetes Association guidelines, yet its identification of prediabetes specific for type 1 diabetes has not been assessed. A composite glucose and C-peptide measure, Index60, identifies individuals at high risk for type 1 diabetes. OBJECTIVE: We compared Index60 and HbA1c thresholds as markers for type 1 diabetes risk. METHODS: TrialNet Pathway to Prevention study participants with ≥ 2 autoantibodies (GADA, IAA, IA-2A, or ZnT8A) who had oral glucose tolerance tests and HbA1c measurements underwent 1) predictive time-dependent modeling of type 1 diabetes risk (n = 2776); and 2) baseline comparisons between high-risk mutually exclusive groups: Index60 ≥ 2.04 (n = 268) vs HbA1c ≥ 5.7% (n = 268). The Index60 ≥ 2.04 threshold was commensurate in ordinal ranking with the standard prediabetes threshold of HbA1c ≥ 5.7%. RESULTS: In mutually exclusive groups, individuals exceeding Index60 ≥ 2.04 had a higher cumulative incidence of type 1 diabetes than those exceeding HbA1c ≥ 5.7% (P < 0.0001). Appreciably more individuals with Index60 ≥ 2.04 were at stage 2, and among those at stage 2, the cumulative incidence was higher for those with Index60 ≥ 2.04 (P = 0.02). Those with Index60 ≥ 2.04 were younger, with lower BMI, greater autoantibody number, and lower C-peptide than those with HbA1c ≥ 5.7% (P < 0.0001 for all comparisons). CONCLUSION: Individuals with Index60 ≥ 2.04 are at greater risk for type 1 diabetes with features more characteristic of the disorder than those with HbA1c ≥ 5.7%. Index60 ≥ 2.04 is superior to the standard HbA1c ≥ 5.7% threshold for identifying prediabetes in autoantibody-positive individuals. These findings appear to justify using Index60 ≥ 2.04 as a prediabetes criterion in this population.

Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes.

OBJECTIVE: We assessed whether Index60, a composite measure of fasting C-peptide, 60-min C-peptide, and 60-min glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody-positive (Ab+) individuals with normal 2-h glucose values (<140 mg/dL). RESEARCH DESIGN AND METHODS: We analyzed 3,058 Type 1 Diabetes TrialNet Pathway to Prevention participants with 2-h glucose <140 mg/dL and Index60 <1.00 values from baseline oral glucose tolerance tests. Characteristics associated with type 1 diabetes (younger age, greater Ab+, higher HLA DR3-DQ2/DR4-DQ8 prevalence, and lower C-peptide) were compared among four mutually exclusive groups: top 2-h glucose quartile only (HI-2HGLU), top Index60 quartile only (HI-IND60), both top quartiles (HI-BOTH), and neither top quartile (LO-BOTH). Additionally, within the 2-h glucose distribution of <140 mg/dL and separately within the Index60 <1.00 distribution, comparisons were made between those above or below the medians. RESULTS: HI-IND60 and HI-BOTH were younger, with greater frequency of more than two Ab+, and lower C-peptide levels, than either HI-2HGLU or LO-BOTH (all P < 0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than for either HI-2HGLU or LO-BOTH (all P < 0.001). Those with Index60 values above the median were younger and had higher frequency of two or more Ab+ (P < 0.001) and DR3-DQ2/DR4-DQ8 prevalence (P < 0.001) and lower area under the curve (AUC) C-peptide levels (P < 0.001) than those below. Those above the 2-h glucose median had higher AUC C-peptide levels (P < 0.001), but otherwise did not differ from those below. CONCLUSIONS: Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-h glucose staging criteria.

Persistence of ß-Cell Responsiveness for Over Two Years in Autoantibody-Positive Children With Marked Metabolic Impairment at Screening.

OBJECTIVE: We studied longitudinal differences between progressors and nonprogressors to type 1 diabetes with similar and substantial baseline risk. RESEARCH DESIGN AND METHODS: Changes in 2-h oral glucose tolerance test indices were used to examine variability in diabetes progression in the Diabetes Prevention Trial-Type 1 (DPT-1) study (n = 246) and Type 1 Diabetes TrialNet Pathway to Prevention study (TNPTP) (n = 503) among autoantibody (Ab)+ children (aged <18.0 years) with similar baseline metabolic impairment (DPT-1 Risk Score [DPTRS] of 6.5-7.5), as well as in TNPTP Ab- children (n = 94). RESULTS: Longitudinal analyses revealed annualized area under the curve (AUC) of C-peptide increases in nonprogressors versus decreases in progressors (P ≤ 0.026 for DPT-1 and TNPTP). Vector indices for AUC glucose and AUC C-peptide changes (on a two-dimensional grid) also differed significantly (P < 0.001). Despite marked baseline metabolic impairment of nonprogressors, changes in AUC C-peptide, AUC glucose, AUC C-peptide-to-AUC glucose ratio (AUC ratio), and Index60 did not differ from Ab- relatives during follow-up. Divergence between nonprogressors and progressors occurred by 6 months from baseline in both cohorts (AUC glucose, P ≤ 0.007; AUC ratio, P ≤ 0.034; Index60, P < 0.001; vector indices of change, P < 0.001). Differences in 6-month change were positively associated with greater diabetes risk (respectively, P < 0.001, P ≤ 0.019, P < 0.001, and P < 0.001) in DPT-1 and TNPTP, except AUC ratio, which was inversely associated with risk (P < 0.001). CONCLUSIONS: Novel findings show that even with similarly abnormal baseline risk, progressors had appreciably more metabolic impairment than nonprogressors within 6 months and that the measures showing impairment were predictive of type 1 diabetes. Longitudinal metabolic patterns did not differ between nonprogressors and Ab- relatives, suggesting persistent ß-cell responsiveness in nonprogressors.

A comparison of the baseline metabolic profiles between Diabetes Prevention Trial-Type 1 and TrialNet Natural History Study participants.

OBJECTIVE: We assessed whether differing autoantibody screening criteria for type 1 diabetes (T1D) prevention trials result in different baseline metabolic profiles of those who screen positive. METHODS: Diabetes Prevention Trial-Type 1 (DPT-1) participants were screened for islet cell autoantibodies, whereas TrialNet Natural History Study (TNNHS) participants were screened for biochemical autoantibodies. In both studies, those determined to be autoantibody positive underwent baseline oral glucose tolerance tests (OGTTs) in which glucose and C-peptide were measured. RESULTS: The percentage of those with an OGTT in the diabetic range was higher among the DPT-1 participants (10.0% of 956 vs. 6.4% of 645, p < 0.01). In a logistic regression analysis with adjustments for age and gender, the difference persisted (p < 0.01). Among those in the non-diabetic range (n = 860 for DPT-1 and n = 604 for the TNNHS), glucose levels were similar at all time points, except for higher fasting glucose levels in the TNNHS participants (p < 0.001). There was a higher percentage of impaired fasting glucose (IFG) in the TNNHS participants (10.9 vs. 6.7%, p < 0.01); however, with adjustments for age and gender, there was no longer a significant difference. There was no significant difference in the percentages with impaired glucose tolerance. C-peptide levels were much lower in the DPT-1 cohort at all OGTT time points (p < 0.001 for all). DISCUSSION: Differing criteria for autoantibody screening can result in marked differences in the baseline metabolic profiles of prospective participants of T1D prevention trials.

The Deterrence of Rapid Metabolic Decline Within 3 Months After Teplizumab Treatment in Individuals at High Risk for Type 1 Diabetes.

End points that provide an early identification of treatment effects are needed to implement type 1 diabetes prevention trials more efficiently. To this end, we assessed whether metabolic end points can be used to detect a teplizumab effect on rapid ß-cell decline within 3 months after treatment in high-risk individuals in the TrialNet teplizumab trial. Glucose and C-peptide response curves (GCRCs) were constructed by plotting mean glucose and C-peptide values from 2-h oral glucose tolerance tests on a two-dimensional grid. Groups were compared visually for changes in GCRC shape and movement. GCRC changes reflected marked metabolic deterioration in the placebo group within 3 months of randomization. By 6 months, GCRCs resembled typical GCRCs at diagnosis. In contrast, GCRC changes in the teplizumab group suggested metabolic improvement. Quantitative comparisons, including two novel metabolic end points that indicate GCRC changes, the within-quadrant end point and the ordinal directional end point, were consistent with visual impressions of an appreciable treatment effect at the 3- and 6-month time points. In conclusion, an analytic approach combining visual evidence with novel end points demonstrated that teplizumab delays rapid metabolic decline and improves the metabolic state within 3 months after treatment; this effect extends for at least 6 months.

TCF7L2 Genetic Variants Do Not Influence Insulin Sensitivity or Secretion Indices in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes.

OBJECTIVE: We aimed to test whether type 2 diabetes (T2D)-associated TCF7L2 genetic variants affect insulin sensitivity or secretion in autoantibody-positive relatives at risk for type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: We studied autoantibody-positive TrialNet Pathway to Prevention study participants (N = 1,061) (mean age 16.3 years) with TCF7L2 single nucleotide polymorphism (SNP) information and baseline oral glucose tolerance test (OGTT) to calculate indices of insulin sensitivity and secretion. With Bonferroni correction for multiple comparisons, P values < 0.0086 were considered statistically significant. RESULTS: None, one, and two T2D-linked TCF7L2 alleles were present in 48.1%, 43.9%, and 8.0% of the participants, respectively. Insulin sensitivity (as reflected by 1/fasting insulin [1/IF]) decreased with increasing BMI z score and was lower in Hispanics. Insulin secretion (as measured by 30-min C-peptide index) positively correlated with age and BMI z score. Oral disposition index was negatively correlated with age, BMI z score, and Hispanic ethnicity. None of the indices were associated with TCF7L2 SNPs. In multivariable analysis models with age, BMI z score, ethnicity, sex, and TCF7L2 alleles as independent variables, C-peptide index increased with age, while BMI z score was associated with higher insulin secretion (C-peptide index), lower insulin sensitivity (1/IF), and lower disposition index; there was no significant effect of TCF7L2 SNPs on any of these indices. When restricting the analyses to participants with a normal OGTT (n = 743; 70%), the results were similar. CONCLUSIONS: In nondiabetic autoantibody-positive individuals, TCF7L2 SNPs were not related to insulin sensitivity or secretion indices after accounting for BMI z score, age, sex, and ethnicity.

Time to Peak Glucose and Peak C-Peptide During the Progression to Type 1 Diabetes in the Diabetes Prevention Trial and TrialNet Cohorts.

OBJECTIVE: To assess the progression of type 1 diabetes using time to peak glucose or C-peptide during oral glucose tolerance tests (OGTTs) in autoantibody-positive relatives of people with type 1 diabetes. RESEARCH DESIGN AND METHODS: We examined 2-h OGTTs of participants in the Diabetes Prevention Trial Type 1 (DPT-1) and TrialNet Pathway to Prevention (PTP) studies. We included 706 DPT-1 participants (mean ± SD age, 13.84 ± 9.53 years; BMI Z-score, 0.33 ± 1.07; 56.1% male) and 3,720 PTP participants (age, 16.01 ± 12.33 years; BMI Z-score, 0.66 ± 1.3; 49.7% male). Log-rank testing and Cox regression analyses with adjustments (age, sex, race, BMI Z-score, HOMA-insulin resistance, and peak glucose/C-peptide levels, respectively) were performed. RESULTS: In each of DPT-1 and PTP, higher 5-year diabetes progression risk was seen in those with time to peak glucose >30 min and time to peak C-peptide >60 min (P < 0.001 for all groups), before and after adjustments. In models examining strength of association with diabetes development, associations were greater for time to peak C-peptide versus peak C-peptide value (DPT-1: χ2 = 25.76 vs. χ2 = 8.62; PTP: χ2 = 149.19 vs. χ2 = 79.98; all P < 0.001). Changes in the percentage of individuals with delayed glucose and/or C-peptide peaks were noted over time. CONCLUSIONS: In two independent at-risk populations, we show that those with delayed OGTT peak times for glucose or C-peptide are at higher risk of diabetes development within 5 years, independent of peak levels. Moreover, time to peak C-peptide appears more predictive than the peak level, suggesting its potential use as a specific biomarker for diabetes progression.

One-Hour Oral Glucose Tolerance Tests for the Prediction and Diagnostic Surveillance of Type 1 Diabetes.

CONTEXT: Once islet autoantibody-positive individuals are identified, predicting which individuals are at highest risk for type 1 diabetes (T1D) is important. A metabolic risk score derived from 2-hour oral glucose tolerance test (OGTT) data, the Diabetes Prevention Trial-Type 1 risk score (DPTRS), can accurately predict T1D. However, 2-hour OGTTs are time-consuming and costly. OBJECTIVE: We aimed to determine whether a risk score derived from 1-hour OGTT data can predict T1D as accurately as the DPTRS. Secondarily, we evaluated whether a 1-hour glucose value can be used for diagnostic surveillance. METHODS: The DPTRS was modified to derive a 1-hour OGTT risk score (DPTRS60) using fasting C-peptide, 1-hour glucose and C-peptide, age, and body mass index. Areas under receiver operating curves (ROCAUCs) were used to compare prediction accuracies of DPTRS60 with DPTRS in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 654) and TrialNet Pathway to Prevention (TNPTP) (n = 4610) participants. Negative predictive values (NPV) for T1D diagnosis were derived for 1-hour glucose thresholds. RESULTS: ROCAUCs for T1D prediction 5 years from baseline were similar between DPTRS60 and DPTRS (DPT-1: 0.805 and 0.794; TNPTP: 0.832 and 0.847, respectively). DPTRS60 predicted T1D significantly better than 2-hour glucose (P < .001 in both cohorts). A 1-hour glucose of less than 180 mg/dL had a similar NPV, positive predictive value, and specificity for T1D development before the next 6-month visit as the standard 2-hour threshold of less than 140 mg/dL (both ≥ 98.5%). CONCLUSION: A 1-hour OGTT can predict T1D as accurately as a 2-hour OGTT with minimal risk of missing a T1D diagnosis before the next visit.