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Comprehensive Bioinformatics Analysis Reveals Hub Genes and Inflammation State of Rheumatoid Arthritis
Joint Authors
Ren, Conglin
Li, Mingshuang
Du, Weibin
Lü, Jianlan
Zheng, Yang
Xu, Haipeng
Quan, Renfu
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-04
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Rheumatoid arthritis (RA) is an autoimmune disease characterized by erosive arthritis, which has not been thoroughly cured yet, and standardized treatment is helpful for alleviating clinical symptoms.
Here, various bioinformatics analysis tools were comprehensively utilized, aiming to identify critical biomarkers and possible pathogenesis of RA.
Three gene expression datasets profiled by microarray were obtained from GEO database.
Dataset GSE55235 and GSE55457 were merged for subsequent analyses.
We identified differentially expressed genes (DEGs) in RStudio with limma package, performing functional enrichment analysis based on GSEA software and clusterProfiler package.
Next, protein-protein interaction (PPI) network was set up through STRING database and Cytoscape.
Moreover, CIBERSORT website was used to assess the inflammatory state of RA.
Finally, we validated the candidate hub genes with dataset GSE77298.
As a result, we identified 106 DEGs (72 upregulated and 34 downregulated genes).
Through GO, KEGG, and GSEA analysis, we found that DEGs were mainly involved in immune response and inflammatory signaling pathway.
With the help of Cytoscape software and MCODE plug-in, the most prominent subnetwork was screened out, containing 14 genes and 45 edges.
For ROC curve analysis, eight genes with AUC >0.80 were considered as hub genes of RA.
In conclusion, compared with healthy controls, the DEGs and their closely related biological functions were analyzed, and we held that chemokines and immune cells infiltration promote the progression of rheumatoid arthritis.
Targeting the eight biomarkers we identified may be useful for the diagnosis and treatment of rheumatoid arthritis.
American Psychological Association (APA)
Ren, Conglin& Li, Mingshuang& Du, Weibin& Lü, Jianlan& Zheng, Yang& Xu, Haipeng…[et al.]. 2020. Comprehensive Bioinformatics Analysis Reveals Hub Genes and Inflammation State of Rheumatoid Arthritis. BioMed Research International،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1136349
Modern Language Association (MLA)
Ren, Conglin…[et al.]. Comprehensive Bioinformatics Analysis Reveals Hub Genes and Inflammation State of Rheumatoid Arthritis. BioMed Research International No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1136349
American Medical Association (AMA)
Ren, Conglin& Li, Mingshuang& Du, Weibin& Lü, Jianlan& Zheng, Yang& Xu, Haipeng…[et al.]. Comprehensive Bioinformatics Analysis Reveals Hub Genes and Inflammation State of Rheumatoid Arthritis. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1136349
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136349