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Cohort study demonstrates beta-cell dysfunction predicts type 1 diabetes progression in single-autoantibody carriers, suggesting value for targeted surveillance and intervention.
OBJECTIVE Individuals with single islet autoantibody positivity exhibit a highly variable risk for type 1 diabetes progression. We evaluated whether metabolic measures identify those at higher progression risk. RESEARCH DESIGN AND METHODS Among first- and second-degree relatives of persons with type 1 diabetes who screened and confirmed positive for a single autoantibody in the TrialNet Pathway to Prevention Natural History study, we used Cox proportional hazards models to assess associations between metabolic measures and time to progression, defined as the development of multiple autoantibody–positive or stage 3 type 1 diabetes. Random forest models were used to estimate the relative importance of each variable. Analyses were conducted in the overall cohort and stratified by age (0–8, ≥8–16, and ≥16 years). RESULTS Individuals with single autoantibody positivity exhibited wide variation in metabolic function. Measures incorporating both oral glucose tolerance test–stimulated glucose and C-peptide to assess β-cell dysfunction showed strong and consistent associations with progression across age-groups and antibody profiles. Associations for traditional risk factors, isolated glucose or C-peptide measures, or indices of insulin resistance differed by age and autoantibody type. Data-driven cutoffs for combined metabolic measures identified small subsets at very high risk (>50% 2-year progression) and large low-risk groups with <10% 5-year progression. CONCLUSIONS β-Cell dysfunction is present in many individuals with single autoantibody positivity and is associated with an increased risk of disease progression. Incorporating stimulated measures of β-cell function alongside age and autoantibody profiles may enable more personalized monitoring, help identify persons most likely to benefit from disease-modifying therapies, and delineate lower-risk individuals who require less intensive surveillance.
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