65-OR: Autoantibody Levels at Seroconversion Improve Prediction to Type 1 Diabetes Beyond Autoantibody Type and Number

While associations between the type and number of islet autoantibodies and progression to type 1 diabetes (T1D) have been reported, the effect of titer values is less well understood. We aim to quantify the ability of autoantibody titers at seroconversion to improve T1D onset prediction. Prospective cohorts in Finland, Germany, Sweden, and the US have followed 24662 children at increased genetic risk for development of islet autoantibodies and T1D. For the 1400 who seroconverted (523 developed T1D), the titers of insulin autoantibodies (IAA), glutamic acid decarboxylase autoantibodies (GADA), and insulinoma antigen-2 autoantibodies (IA2A) at time of initial and confirmed seroconversion, i.e., the respective first and consecutive second autoantibody-positive serum sample, were normalized (to log multiples of upper limit of normal) and analyzed. Prediction models using multivariate logistic regression with inverse probability censored weighting (IPCW) were trained using 10-fold cross validation. Discriminative power for disease was estimated using the IPCW concordance index (c-index) with 95% confidence intervals estimated via bootstrap. Multivariate Cox proportional hazards models were used to quantify the impact of the autoantibody titers. A baseline model with covariates for data source, sex, HLA-DR/DQ genotype, and age at initial and confirmed seroconversion had a performance of 64 c-index; 95% CI 62-65. Significant improvement was observed after adding IAA, GADA, IA2A positivity indicators at initial and confirmed seroconversion (74; 72-75). Adding the corresponding autoantibody titers resulted in significant additional gains (76; 75-76). Adjusted hazard ratios (HR) from the Cox model showed that autoantibody titers at confirmed seroconversion were predictive of diabetes (HR 1.29; 95% CI 1.20-1.38 for IAA, 1.12; 1.07-1.18 for GADA, and 1.19; 1.15-1.25 for IA2A, all p Islet autoantibody titers at seroconversion improve T1D prediction. Disclosure K. Ng: Employee; Self; IBM. V. Anand: None. R. Veijola: None. M. Maziarz: None. K. Waugh: None. W. Hagopian: None. P. Achenbach: None. T1di study group: n/a. Funding JDRF (1-IND-2019-717-I-X)