Subtyping children with asthma by clustering analysis of mRNA expression data - Wang, Ting; He, Changhui; Hu, Ming; Wu, Honghua; Ou, Shuteng; Li, Yuke; Fan, Chuping (Frontiers in Genetics, 2022)
Background Asthma is recognized as being heterogeneous disease. Although there are several phenotypic classifications for childhood asthma. Methods Unsupervised consensus cluster analysis was used to classify 36 children with persistent asthma from the GSE65204 dataset. And then differentially expressed genes (DEGs) between different asthma subtypes was screened, and weighted gene co-expression network analysis (WGCNA) was carried out. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed for DEGs and critical gene modules. Protein–protein interaction (PPI) was constructed to obtain hub genes. Finally, differences in the immune microenvironment were analyzed between different subtypes. Results The 2 subtypes (C1, C2) were identified by unsupervised consensus clustering. The DEGs between different asthma subtypes are mainly enriched in immune regulation and the release of inflammatory mediators. The important modular genes screened by WGCNA are mainly enriched in aspects of flammatory mediators regulation. PPI analysis found 10 hub genes (DRC1, TTC25, DNALI1, DNAI1, DNAI2, PIH1D3, ARMC4, RSPH1, DNAAF3, DNAH5), and ROC analysis demonstrated that 10 hub genes had a reliably ability to distinguish C1 from C2. And we observed differences between C1 and C2 in their immune microenvironment. Conclusions Based on the gene expression profiles of children's nasal epithelium. we identified two asthma subtypes that have differences in gene expression patterns, biological characteristics, and immune microenvironments. This will provide a reference point for future childhood asthma typing and personalized therapy.