Predictors of Transitions From Glutamic Acid Decarboxylase Autoantibody (GADA) as the Initial Autoantibody to Multiple Autoantibodies of Type 1 Diabetes in Children at Risk by a Dynamic Prediction Model
Authors' conclusion
The dynamic prediction model presented an individual time-specific risk of transition from a single GADA to multiple autoantibodies and type 1 diabetes.
Study context
- Population
- GADA-positive children at risk of T1D in the The Environmental Determinants of Diabetes in the Young (TEDDY) study, followed for additional autoantibodies (IAA, IA-2A, ZnT8A) and T1D
- Participants
- 379 children
- Outcome
- Time of progression from single GADA to multiple islet autoantibodies and T1D
Methodological detailsdynamic prediction model, longitudinal risk variables
- Dynamic prediction model
- Longitudinal risk variables
Main finding
As reported in the abstract
Transition from GADA to multiple autoantibodies
- Increased risk with lower age
- p < 0.001
- Increased risk with increased GADA titers during follow-up
- p < 0.001
- Less likely with HLA DQ2/X but not DQ2/8
- p=0.004
Observational data: associations, not effects.
Further findings
Transition from multiple autoantibodies without IA-2A to IA-2A positivity
- Associated with increased 2 h glucose after oral glucose tolerance test (OGTT)
- P < 0.001
- Associated with increased ZnT8A titers
- P < 0.001
Transition from GADA only to T1D
- Increased risk with increasing HbA1c
- P < 0.001
- Increased risk with increasing GADA titers
- P < 0.001
Transition from multiple autoantibodies to T1D
- Associated with increasing HbA1c
- P < 0.001
- Transition from multiple autoantibodies incl. IA-2A to T1D associated with 2 h glucose
- P < 0.001
Original publication
Predictors of Transitions From GADA as the Initial Autoantibody to Multiple Autoantibodies of Type 1 Diabetes in Children at Risk by a Dynamic Prediction Model. Pediatr Diabetes. Published 16 September 2025. doi:10.
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