Bioinformatics analysis identifying key genes and signaling pathways involved in the egg allergy in young children: a retrospective study.

Objective. Identify key genes and signaling pathways involved in IgE-mediated food allergy in young children using bioinformatics analysis.
Materials and Methods. The GSE114065 dataset from GEO was utilized for bioinformatic analysis. DEGs were identified using the GEO2R web tool. GO, KEGG, and Reactome functional analyses were performed using the Enrichr platform. The PPI network for DEGs was constructed with the STRING website and visualized in Cytoscape. The cytoHubba plugin was used to identify hub genes. Nonparametric Mann-Whitney test was employed to compare groups.
Results. Of the 490 DEGs identified, 402 were upregulated and 88 were downregulated. Dowregulated DEGs showed no significant enrichment in biological processes or molecular functions but were associated with Golgi apparatus-related cellular components. In contrast, upregulated DEGs exhibited pronounced enrichment in biological processes linked to antiviral defense, immune regulation, and IL-27 signaling, alongside extracellular matrix-related cellular components. Molecular functions included cytokine activity, receptor ligand binding. KEGG and Reactome analyses highlighted significant pathways involved in cytokine signaling, immune response, and antiviral defense. 10 DEGs were identified as hub genes, including USP18, OAS3, IFIH1, MX1, DDX58, OAS1, IFIT2, OAS2, IFI35, and IFIT3.
Conclusion.   The results demonstrate that the aberrant activation of genes related to the interferon response and antiviral defense plays a central role in the pathogenesis of IgE-mediated food allergy. The 10 identified hub genes are key regulators of innate immunity, significantly influencing inflammatory and antiviral pathways. Our findings suggest that the upregulation of these genes contributes to the immune imbalance characteristic of food allergy, opening new avenues for understanding disease mechanisms and identifying innovative diagnostic and therapeutic targets.
Key words: bioinformatics analysis, food allergies, hub genes, young children