Bioinformatics Analysis and Experimental Validation to Identify Key Glycosylation-Related Genes in Asthma

Yue Li,* Ruhao Wu,* Xiaoying Tian, Mengting Zhang, Zhe Cheng* Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhe Cheng, Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, People’s Republic of China, Email fccchengzhe@zzu.edu.cnPurpose: Asthma is a chronic inflammatory disease influenced by complex genetic and environmental factors. Despite extensive research, the intricate pathophysiology of asthma remains incompletely understood. Furthermore, the effects of glycosylation on asthma remain unclear. Considering that glycosylation-related genes have not been reported in patients with asthma, we aimed in this study to identify key glycosylation-related genes involved in asthma and their potential as therapeutic targets.Material and Methods: In the GSE63142 microarray dataset, we performed weighted gene co-expression network, protein–protein interaction network, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and CIBERSORT analyses to identify glycosylation-related genes associated with asthma. Subsequently, these key genes were validated in the GSE67472 microarray dataset and BEAS-2B cells. Correlation analysis of key gene expression and clinical characteristics of asthma patients were performed using Spearman correlation analysis.Results: Six key glycosylation-related genes related to asthma were identified: FUT5, FUT3, HCRT, B3GNT6, KDELR3, and SCGB1A1. Expression of FUT5, FUT3, B3GNT6, and KDELR3 was significantly upregulated and that of HCRT and SCGB1A1 significantly downregulated in BEAS-2B cells stimulated with IL-13/IL-4. Moreover, expression of key glycosylation-related genes in the peripheral blood of asthma patients correlated strongly with lung function and eosinophils.Conclusion: Our findings have implications for identifying potential therapeutic targets and prognostic markers for asthma.Keywords: asthma, glycosylation, gene, bioinformatics, biomarker