Bioinformatics Analysis of T-cell Exhaustion Genes in Pediatric Allergic Rhinitis and their Clinical Diagnostic Significance.

BACKGROUND

Pediatric Allergic Rhinitis (PAR) is a chronic inflammatory condition. TCell Exhaustion (TCE) contributes to immune dysfunction. This study explored TCE-related genes in PAR and constructed a diagnostic model.

METHODS

Differential expression analysis was performed on GSE19187 data (14 PAR, 11 controls). Intersection with TCE-associated genes yielded TCE-related Differentially Expressed Genes (TCERDEGs). Functional enrichment, logistic regression, the Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO) were applied to build a diagnostic model and identify hub genes. Immune infiltration was also analyzed.

RESULTS

Twenty-two TCERDEGs were identified. IFNG and CD96 showed the strongest positive correlation (r = 0.89), while FSTL3 and MTOR showed the strongest negative correlation (r = -0.70). Many TCERDEGs localized to chromosomes 3 and 9. A diagnostic model was established with three hub genes: CD96, CD200R1, and TRAF1. Immune analysis revealed strong positive correlations between activated CD4 memory T cells and resting dendritic cells (r = 1), and negative correlations between resting and activated NK cells (r = -0.78). CD96 positively correlated with naive B cells (r = 0.58), while TRAF1 negatively correlated with resting mast cells (r = -0.57).

DISCUSSION: This study developed a PAR diagnostic signature consisting of CD96, CD200R1, and TRAF1 from T‑cell‑exhaustion‑related genes, highlighting the vital role of T‑cell exhaustion‑mediated immune dysregulation in pediatric allergic rhinitis. The distinct correlations between hub genes and multiple infiltrated immune cells further suggested that these biomarkers might contribute to PAR pathogenesis by modulating the local immune microenvironment. Nevertheless, these results are derived from public transcriptomic datasets, and prospective clinical samples are required to verify the diagnostic performance and biological function of the three candidate genes.

CONCLUSION

Aberrant expression of CD96, CD200R1, and TRAF1, linked to immune infiltration, suggests TCE-related immune changes may underlie PAR pathogenesis. These genes show potential as diagnostic biomarkers, though further clinical validation is needed. Our findings provide a useful diagnostic model and insights into PAR immune status.