Immunogenetic Divergence in Pediatric Type 1 Diabetes: A Sibling-Controlled Analysis
DOI:
https://doi.org/10.58600/eurjther2993Keywords:
C-Peptide, islet autoantibodies, HLA genotyping, sibling comparison, Type 1 diabetes mellitusAbstract
Objective: Type 1 Diabetes Mellitus (T1DM) is an autoimmune condition characterized by progressive pancreatic β-cell destruction, with high familial clustering rates. Siblings of index cases with T1DM represent a critical population for understanding immunogenetic mechanisms, as they share genetic backgrounds while demonstrating variable disease expression. Islet-specific autoantibodies and human leukocyte antigen (HLA) haplotypes are pivotal markers for early risk identification in at-risk siblings. This study aimed to characterize and compare immunological signatures between pediatric index cases with T1DM and their unaffected siblings, with particular emphasis on the utility of combined autoantibody and HLA profiling for predicting disease risk in the sibling population.
Methods: A retrospective cross-sectional study was conducted with 230 participants (46 index cases with T1DM and 184 unaffected siblings) recruited from a tertiary pediatric endocrinology clinic. Serum levels of anti-glutamic acid decarboxylase antibodies (anti-GAD), anti-islet cell antibodies (anti-ICA), anti-insulin autoantibodies (anti-IAA), insulin, C-peptide, and glycated hemoglobin (HbA1c) were measured. HLA-DR and -DQ loci were genotyped using high-resolution sequence-based typing.
Results: Index cases with T1DM had significantly higher positivity and titers for anti-GAD and anti-ICA (p<0.001), lower C-peptide (0.21 vs. 0.99 ng/mL) and insulin levels (2.87 vs. 4.37 µIU/mL), and elevated HbA1c (11.6% vs. 5.5%) compared to controls. Decision tree analysis identified specific HLA alleles (e.g., DR3-DQ2 and DR4-DQ8) associated with disease status.
Conclusion: This study suggests that combined autoantibody profiling and HLA genotyping may be useful for risk stratification in siblings of index cases with T1DM and supports further evaluation of their role in early monitoring strategies.
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