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

  1. the Type 1 Diabetes TrialNet and the Diabetes Prevention Trial-Type 1 Study Groups*
  1. 1Division of Endocrinology, University of Miami, Miami, Florida
  2. 2VA Puget Sound Health Care System, Division of Endocrinology, Metabolism, and Nutrition, University of Washington, Seattle, Washington
  3. 3Division of Informatics and Biostatistics, University of South Florida, Tampa, Florida
  4. 4HLA/DNA Laboratory, Barbara Davis Center for Childhood Diabetes, Denver, Colorado
  5. 5Department of Epidemiology and Biostatistics, University of Western Ontario, London, Canada
  6. 6Division of Endocrinology, University of Florida, Gainesville, Florida
  1. Corresponding author: Jay M. Sosenko, jsosenko{at}med.miami.edu.
  • Deceased.

Abstract

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.

Footnotes

  • * A complete list of the Type 1 Diabetes TrialNet and the Diabetes Prevention Trial–Type 1 Study Groups can be found in the Supplementary Data.

  • Received February 20, 2013.
  • Accepted May 9, 2013.

Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

This Article

  1. Diabetes Care
  1. Supplementary Data
  2. All Versions of this Article:
    1. dc13-0425v1
    2. 36/9/2615 most recent