Bioinformatics analysis and qRT-PCR validation of iron metabolism-related genes in pediatric asthma.

Abstract

Pediatric asthma (PA) is a chronic airway disease with a complex etiology, and iron metabolism disorder is believed to be involved in its pathogenesis. In this study, we integrated three peripheral blood transcriptome datasets from the GEO database (GSE27011, GSE40888, GSE40732), which included 283 samples (155 in the PA group and 128 in the control group), and conducted a comprehensive analysis after normalization and batch effect correction. Differential expression analysis identified 15 iron metabolism-related differentially expressed genes (IMRDEGs), including C19orf12, IREB2, XK, GDF15. Functional enrichment analysis showed that these genes mainly participate in cellular energy metabolism, oxidative stress response, and regulation of iron homeostasis. A discrimination model based on machine learning algorithms isolated four key genes, with an area under the receiver operating characteristic curve of 0.69, indicating moderate diagnostic discrimination. qRT-PCR analysis of independent blood samples showed that C19orf12 expression was upregulated in patients with PA, while IREB2 expression was downregulated, consistent with bioinformatics analysis results. Immune infiltration analysis revealed significant differences in the proportions of memory CD4 + T cells and mast cells between high-risk and low-risk groups, suggesting that iron metabolism imbalance may contribute to asthma development via immune regulatory mechanisms. This study provides combined support from transcriptomic and experimental data for the potential role of IMRGs in PA, serving as a basis for further mechanistic research and clinical validation.