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. 2019 Jun;42(6):1051-1060.
doi: 10.2337/dc18-2282. Epub 2019 Apr 9.

Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report

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Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report

Jeffrey P Krischer et al. Diabetes Care. 2019 Jun.

Abstract

Objective: Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D).

Research design and methods: A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D.

Results: HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden's index J = 0.117) and single nucleotide polymorphism rs2476601, in PTPN22, was the best predictor for insulin autoantibodies (IAA) appearing first (IAA-first) (J = 0.123). For GAD autoantibodies (GADA)-first, weight at 1 year was the best predictor (J = 0.114). In a multivariate model, the area under the ROC curve (AUC) was 0.678 (95% CI 0.655, 0.701), 0.707 (95% CI 0.676, 0.739), and 0.686 (95% CI 0.651, 0.722) for IA, IAA-first, and GADA-first, respectively, at 6 years. The AUC of the prediction model for T1D at 3 years after the appearance of multiple autoantibodies reached 0.706 (95% CI 0.649, 0.762).

Conclusions: Prediction modeling statistics are valuable tools, when applied in a time-until-event setting, to evaluate the ability of risk factors to discriminate between those who will and those who will not get disease. Although significantly associated with IA and T1D, the TEDDY risk factors individually contribute little to prediction. However, in combination, these factors increased IA and T1D prediction substantially.

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Figures

Figure 1
Figure 1
Se vs. 1 − Sp of each TEDDY-identified risk factor to predict IA, IAA-first, and GADA-first (AC) at age 6 years and to predict progression to T1D at 3 years from the appearance of multiple autoantibodies (D).
Figure 2
Figure 2
ROC curves with associated AUC of prediction models with TEDDY-identified risk factors selected by forward selection to predict IA, IAA-first, and GADA-first (AC) at ages 2, 6, and 10 years and predict T1D at 1, 3, and 5 years from the appearance of multiple autoantibodies (D).

References

    1. TEDDY Study Group The Environmental Determinants of Diabetes in the Young (TEDDY) Study. Ann N Y Acad Sci 2008;1150:1–13 - PMC - PubMed
    1. Törn C, Hadley D, Lee HS, et al. .; TEDDY Study Group . Role of type 1 diabetes-associated SNPs on risk of autoantibody positivity in the TEDDY study. Diabetes 2015;64:1818–1829 - PMC - PubMed
    1. Krischer JP, Liu X, Lernmark Å, et al. .; TEDDY Study Group . The influence of type 1 diabetes genetic susceptibility regions, age, sex, and family history on the progression from multiple autoantibodies to type 1 diabetes: a TEDDY study report. Diabetes 2017;66:3122–3129 - PMC - PubMed
    1. Hummel S, Beyerlein A, Tamura R, et al. .; TEDDY Study Group . First infant formula type and risk of islet autoimmunity in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Diabetes Care 2017;40:398–404 - PMC - PubMed
    1. Uusitalo U, Liu X, Yang J, et al. .; TEDDY Study Group . Association of early exposure of probiotics and islet autoimmunity in the TEDDY study. JAMA Pediatr 2016;170:20–28 - PMC - PubMed

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