Lisa E. Rafkin

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.

Trends of earlier and later responses of C-peptide to oral glucose challenges with progression to type 1 diabetes in diabetes prevention trial-type 1 participants.

OBJECTIVE We studied the C-peptide response to oral glucose with progression to type 1 diabetes in Diabetes Prevention Trial–Type 1 (DPT-1) participants. RESEARCH DESIGN AND METHODS Among 504 DPT-1 participants <15 years of age, longitudinal analyses were performed in 36 progressors and 80 nonprogressors. Progressors had oral glucose tolerance tests (OGTTs) at baseline and every 6 months from 2.0 to 0.5 years before diagnosis; nonprogressors had OGTTs over similar intervals before their last visit. Sixty-six progressors and 192 nonprogressors were also studied proximal to and at diagnosis. RESULTS The 30–0 min C-peptide difference from OGTTs performed 2.0 years before diagnosis in progressors was lower than the 30–0 min C-peptide difference from OGTTs performed 2.0 years before the last visit in nonprogressors (P < 0.01) and remained lower over time. The 90–60 min C-peptide difference was positive at every OGTT before diagnosis in progressors, whereas it was negative at every OGTT before the last visit in nonprogressors (P < 0.01 at 2.0 years). The percentage whose peak C-peptide occurred at 120 min was higher in progressors at 2.0 years (P < 0.05); this persisted over time (P < 0.001 at 0.5 years). However, the peak C-peptide levels were only significantly lower at 0.5 years in progressors (P < 0.01). The timing of the peak C-peptide predicted type 1 diabetes (P < 0.001); peak C-peptide levels were less predictive (P < 0.05). CONCLUSIONS A decreased early C-peptide response to oral glucose and an increased later response occur at least 2 years before the diagnosis of type 1 diabetes.

Validation of the Diabetes Prevention Trial–Type 1 Risk Score in the TrialNet Natural History Study

OBJECTIVE 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). RESEARCH DESIGN AND METHODS 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. RESULTS 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). CONCLUSIONS The DPTRS is an accurate and robust predictor of type 1 diabetes in autoantibody-positive populations.

The Application of the Diabetes Prevention Trial–Type 1 Risk Score for Identifying a Preclinical State of Type 1 Diabetes

OBJECTIVE We assessed the utility of the Diabetes Prevention Trial–Type 1 Risk Score (DPTRS) for identifying individuals who are highly likely to progress to type 1 diabetes (T1D) within 2 years. RESEARCH DESIGN AND METHODS The DPTRS was previously developed from Diabetes Prevention Trial–Type 1 (DPT-1) data and was subsequently validated in the TrialNet Natural History Study (TNNHS). DPTRS components included C-peptide and glucose indexes from oral glucose tolerance testing, along with age and BMI. The cumulative incidence of T1D was determined after DPTRS thresholds were first exceeded and after the first occurrences of glucose abnormalities. RESULTS The 2-year risks after the 9.00 DPTRS threshold was exceeded were 0.88 and 0.77 in DPT-1 (n = 90) and the TNNHS (n = 69), respectively. In DPT-1, the 2-year risks were much lower after dysglycemia first occurred (0.37; n = 306) and after a 2-h glucose value between 190 and 199 mg/dL was first reached (0.64; n = 59). Among those who developed T1D in DPT-1, the 9.00 threshold was exceeded 0.81 ± 0.53 years prior to the conventional diagnosis. Postchallenge C-peptide levels were substantially higher (P = 0.001 for 30 min; P < 0.001 for other time points) when the 9.00 threshold was first exceeded compared with the levels at diagnosis. CONCLUSIONS A DPTRS threshold of 9.00 identifies individuals who are very highly likely to progress to the conventional diagnosis of T1D within 2 years and, thus, are essentially in a preclinical diabetic state. The 9.00 threshold is exceeded well before diagnosis, when stimulated C-peptide levels are substantially higher.

Glucose excursions between states of glycemia with progression to type 1 diabetes in the Diabetes Prevention Trial-Type 1 (DPT-1)

OBJECTIVE We characterized fluctuations between states of glycemia in progressors to type 1 diabetes and studied whether those fluctuations are related to the early C-peptide response to oral glucose. RESEARCH DESIGN AND METHODS Oral glucose tolerance tests (OGTTs) from differing states of glycemia were compared within individuals for glucose and C-peptide. Dysglycemic OGTTs (DYSOGTTs) were compared with normal OGTTs (NLOGTT), while transient diabetic OGTTs (TDOGTTs) were compared with subsequent nondiabetic OGTTs and with OGTTs performed at diagnosis. RESULTS Of 135 progressors with four or more OGTTs, 30 (22%) went from NLOGTTs to DYSOGTTs at least twice. Area under the curve (AUC) glucose values from the second NLOGTT were higher (P < 0.001) than values from the first NLOGTT. Among 98 progressors whose DYSOGTTs and NLOGTTs were synchronized for the time before diagnosis, despite higher glucose levels (P < 0.01 at all time points) in the DYSOGTTs, 30- to 0-min C-peptide difference values changed little. Likewise, 30- to 0-min C-peptide difference values did not differ between TDOGTTs and subsequent (within 3 months) nondiabetic OGTTs in 55 progressors. In contrast, as glucose levels increased overall from the first to last OGTTs before diagnosis (P < 0.001 at every time point, n = 207), 30- to 0-min C-peptide difference values decreased (P < 0.001). CONCLUSIONS Glucose levels fluctuate widely as they gradually increase overall with progression to type 1 diabetes. As glucose levels increase, the early C-peptide response declines. In contrast, glucose fluctuations are not related to the early C-peptide response. This suggests that changes in insulin sensitivity underlie the glucose fluctuations.

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.

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.

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.

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

Sosenko JM, Mahon J, Rafkin L, Lachin JM, Krause‐Steinrauf H, Krischer JP, Cuthbertson D, Palmer JP, Thompson C, Greenbaum CJ, Skyler JS, the Diabetes Prevention Trial‐Type 1 and TrialNet Study Groups. A comparison of the baseline metabolic profiles between Diabetes Prevention Trial‐Type 1 and TrialNet Natural History Study participants.