已发表论文

使用生物信息学分析鉴定包涵体肌炎中的枢纽基因和生物途径

 

Authors Wu Y, Zhao Z, Zhang J, Wang Y, Song X

Received 24 November 2021

Accepted for publication 12 January 2022

Published 9 February 2022 Volume 2022:15 Pages 1281—1293

DOI https://doi.org/10.2147/IJGM.S346965

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Scott Fraser


Background: 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