Identification and Validation of Hub Genes in Children Asthma and Wheeze by Bioinformatics methods

Abstract

Abstract Background The pathogenic mechanisms of children asthma and the relationship between children asthma and children wheeze are complex and not fully understood. The purpose of this study was to identify the pathways and hub genes along with common differentially expressed genes (DEGs) between children asthma and children wheeze, and to explore the specific insights for the clinical asthma and wheeze therapies in children. Methods The GSE123750 dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the children asthma and children wheeze groups were identified using the “Limma” package in the R language. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, along with Gene Set Enrichment Analysis (GSEA), were performed to explore potential signaling pathways associated with the DEGs. Weighted Gene Co-expression Network Analysis (WGCNA) was conducted to identify gene network modules associated with children asthma using microarray data. Functional enrichment analysis was performed on the co-expression genes within specific highlighted modules. Results A total of 334 DEGs were identified in children with asthma compared to those with wheezing. Furthermore, five KEGG pathways, namely Ribosome, Oocyte meiosis, p53 signaling pathway, B cell receptor signaling pathway, and Cellular senescence, exhibited significant enrichment. The protein-protein interaction (PPI) network analysis in Cytoscape highlighted four hub genes: TOP2A, CDK1, CENPA, and KIF11. GSEA results indicated a positive correlation between asthma and down-regulation of early-stage progenitor T lymphocyte genes, up-regulation of plasma cell genes in bone marrow and blood, deadenylation-dependent mRNA decay, and down-regulation of genes in monocytes. The WGCNA analysis identified the pink module as being highly associated with asthma. Genes within this key module were primarily associated with organ or tissue-specific immune response, mucosal immune response, and the ribosome signaling pathway according to GO and KEGG pathway enrichment analyses. Furthermore, a protein-protein interaction (PPI) network analysis using STRING and Cytoscape revealed one hub gene, IMPA1, among the key genes. Conclusions In conclusion, our study not only advances the current understanding of childhood asthma but also provides valuable insights for identifying potential biomarkers to improve early diagnosis of asthma in preschool children with wheezing. These findings can assist clinicians in making informed decisions regarding early treatment interventions.