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Eosinophilic asthma (EA) is one of the most important asthma phenotypes with distinct features. However, its genetic characteristics are not fully understood. This study aimed to investigate the transcriptome features and to identify hub genes of EA. Differentially expressed genes (DEGs) analysis, weighted gene coexpression network analysis (WGCNA) and protein–protein interaction (PPI) network analysis were performed to construct gene networks and to identify hub genes. Enrichment analyses were performed to investigate the biological processes, pathways and immune status of EA. The hub genes were validated in another dataset. The diagnostic value of the identified hub genes was assessed by receiver operator characteristic curve (ROC) analysis. Compared with NEA, EA had a different gene expression pattern, in which 81 genes were differentially expressed. WGCNA identified two gene modules significantly associated with EA. Intersections of the DEGs and the genes in the modules associated with EA were mainly enriched in chemotaxis and signal transduction by GO and KEGG enrichment analyses. Single-sample gene set enrichment analysis (ssGSEA) indicated that EA had different immune infiltration and functions compared with NEA. Seven hub genes of EA were identified and validated, including  CCL17 ,  CCL26 ,  CD1C ,  CXCL11 ,  CXCL10 ,  CCL22 , and  CCR7 , all of which have diagnostic values for distinguishing EA from NEA (All AUC &gt; 0.7). This study demonstrated the distinct gene expression patterns, biological processes, and immune status of EA. Hub genes of EA were identified and validated. Our study could provide a framework of co-expression gene modules and potential therapeutic targets for EA.

Identification of key modules and hub genes for eosinophilic asthma by weighted gene co-expression network analysis