Dysregulated IL-6, IL-10, and IL-17 expression in Iraqi children with type 1 diabetes: correlation with clinical parameters and diagnostic potential.
case_control · Level III
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- Record sourced from PubMed, PMID 42135559.
- Also identified by DOI 10.1038/s41390-026-05068-3.
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Abstract
Diabetes triggering autoimmune mechanisms in populations with specific environmental contacts remain partially explored. This study aimed to determine expression levels of three interleukins (IL-6, IL-10, IL-17) in T1DM Iraqi children and their associations with clinical parameters. A case-control study compared 188 T1DM patients with 250 healthy children. Quantitative real-time PCR assessed gene expression of IL-6, IL-10, and IL-17 in peripheral blood mononuclear cells (PBMCs). ELISA assays quantified serum cytokines. Genetic haplotype mapping was performed in silico for polymorphisms of selected interleukin genes. T1DM patients showed strong expression of pro-inflammatory IL-6 (fold change 3.42, p < 0.001) and IL-17 (fold change 2.87, p < 0.001) with diminished anti-inflammatory IL-10 expression (fold change 0.38, p < 0.001). Associations were noted with HbA1c, disease duration, and age at diagnosis. Increased T1DM susceptibility was linked with haplotypes GCAA-IL-6, ATA-IL-10, AGT-IL-17. Combined interleukin expression score showed good diagnostic sensitivity (AUC = 0.924). Iraqi children with T1DM exhibited a pro-inflammatory cytokine profile creating immunological imbalance. This contributes to T1DM immunopathology understanding in this population and could aid in developing population-specific diagnostic and treatment approaches. Iraqi children with T1DM exhibit dysregulated cytokine expression with elevated pro-inflammatory IL-6 and IL-17, and suppressed anti-inflammatory IL-10. Population-specific genetic haplotypes (GCAA-IL-6, ATA-IL-10, AGT-IL-17) increase T1DM susceptibility in Iraqi children. First comprehensive study characterizing interleukin gene expression profiles in Iraqi pediatric T1DM population. Enables development of population-specific diagnostic biomarkers for T1DM in resource-limited settings.