International Journal of General Medicine (Feb 2022)
Identification of Hub Genes and Biological Pathways in Inclusion Body Myositis Using Bioinformatics Analysis
Abstract
Yue Wu,1,2,* Zijun Zhao,3,* Jinru Zhang,1,2 Yaye Wang,1,2 Xueqin Song1,2 1Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000, People’s Republic of China; 2Neurological Laboratory of Hebei Province, Shijiazhuang, Hebei, People’s Republic of China; 3Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Heibei, 050000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xueqin SongDepartment of Neurology, The Second Hospital of Hebei Medical University, 215 Heping West Road, Shijiazhuang, Hebei, 050000, People’s Republic of China, Tel/Fax +86-318-2187209, Email [email protected]: Inclusion body myositis (IBM) is a unique idiopathic inflammatory myopathy with unclear pathogenesis and poor prognosis. Although previous publications have identified some molecular biomarkers, the value of these biomarkers is unknown.Objective: To identify hub genes and signaling pathways related to IBM for understanding the IBM-related mechanisms and providing guidance for therapy development.Methods: Two microarray datasets (GSE3112 and GSE128470) were downloaded from the Gene Expression Omnibus (GEO) database. GEO2R was used to detect differentially expressed genes (DEGs) between IBM and normal muscle tissues. The hub genes were determined using protein–protein interaction (PPI) network in Cytoscape. The specific signaling pathways and biological functions of IBM were identified using GO, KEGG, and GSEA enrichment analyses. Moreover, CIBERSORT was applied to estimate the expression level of 22 immune cell types in IBM and normal muscle tissue. The relationship between the immune cell types and hub genes was then explored.Results: A total of 219 DEGs and 10 hub genes were identified. Enrichment analyses revealed that the chemokine signaling pathway, cellular response to interferon-gamma, and P53 pathway have crucial roles in IBM. Immune infiltration analyses showed that IBM was associated with high level of CD8 T cells, Tregs, and macrophages. Finally, five potential drugs were predicted for IBM patients through CMap (connectivity map) database.Conclusion: In this study, the underlying molecular mechanisms and immunological landscape of IBM were investigated, and thus may provide new directions for future research on IBM pathogenesis.Keywords: bioinformatic analysis, inclusion body myositis, differentially expressed genes, biological pathways, immune infiltrating cell
