Center |
![]() |
Award Year | 2024 |
Pilot Study | Combination of high-affinity ECL-based autoantibodies and genetic risk scores enhances Type 1 Diabetes prediction in single-antibody positive individuals |
Awardee | Xiaofan Jia MD PhD |
Abstract |
Individuals with a single islet autoantibody (IAb) positivity is dominant but understudied in type 1 diabetes (T1D) mass screening studies. Most of single IAb positivity detected by the current "gold standard" radio-binding assay were found to be low-affinity IAbs with low predictive value of T1D risk in T1D screening studies. Differentiation of single IAb positivity for improving T1D risk prediction is critical and urgent for early prediction and better prevention of T1D. Recently, an electrochemiluminescence (ECL) antibody assay and T1D genetic risk scores (GRS) have both demonstrated the enhanced prediction power in individuals with a single IAb. In this proposal, we aim to further verify the prediction power of ECL-based single IAb positivity in a large cohort from the national T1D clinical trial, explore the associations between GRS and ECL-based IAb in individuals with single IAb positive, and evaluate the overall enhancement in T1D predictive capabilities achieved by integrating ECL-based IAbs and T1D GRS into a comprehensive model. The study will advance our understanding of ECL-based high-affinity IAbs and T1D GRS for T1D prediction, enhance screening efficacy for T1D mass screening studies, and facilitate early intervention/prevention strategies tailored to this overlooked population. |