Erschienen in:
01.12.2006 | Article
Type 1 diabetes risk assessment: improvement by follow-up measurements in young islet autoantibody-positive relatives
verfasst von:
P. Achenbach, K. Warncke, J. Reiter, A. J. K. Williams, A. G. Ziegler, P. J. Bingley, E. Bonifacio
Erschienen in:
Diabetologia
|
Ausgabe 12/2006
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Abstract
Aims/hypothesis
Combinations of autoantibody characteristics, including antibody number, titre, subclass and epitope have been shown to stratify type 1 diabetes risk in islet autoantibody-positive relatives. The aim of this study was to determine whether autoantibody characteristics change over time, the nature of such changes, and their implications for the development of diabetes.
Methods
Five-hundred and thirteen follow-up samples from 141 islet autoantibody-positive first-degree relatives were tested for islet autoantibody titre, IgG subclass, and GAD and IA-2 antibody epitope. All samples were categorised according to four risk stratification models. Relatives had a median follow-up of 6.8 years and 48 developed diabetes during follow-up. Survival analysis was used to determine the probability of change in risk category and of progression to diabetes.
Results
For each stratification model, the majority of relatives (71–81%) remained in the same risk category throughout follow-up. In the remainder, changes occurred both from lower to higher and from higher to lower risk categories. For all four models, relatives aged < 15 years were more likely to change risk category than those aged >15 years (0.001 < p < 0.03). Relatives whose autoantibody status changed from low- to high-risk categories had a higher risk of diabetes than relatives who remained in low-risk categories, and inclusion of autoantibody status during follow-up improved diabetes risk stratification in Cox proportional hazards models (p < 0.001).
Conclusions/interpretation
Changes in islet autoantibodies are relevant to pathogenesis, and are likely to signal alterations in the disease process. Detection of changes through follow-up measurement will improve diabetes risk stratification, particularly in young individuals.