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Clinical Rheumatology

Erschienen in:

05.07.2021 | Original Article

Identification of differential key biomarkers in the synovial tissue between rheumatoid arthritis and osteoarthritis using bioinformatics analysis

verfasst von: Runrun Zhang, Xinpeng Zhou, Yehua Jin, Cen Chang, Rongsheng Wang, Jia Liu, Junyu Fan, Dongyi He

Erschienen in: Clinical Rheumatology | Ausgabe 12/2021

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Abstract

Introduction/objectives

Rheumatoid arthritis (RA) and osteoarthritis (OA) are two common joint diseases with similar clinical manifestations. Our study aimed to identify differential gene biomarkers in the synovial tissue between RA and OA using bioinformatics analysis and validation.

Method

GSE36700, GSE1919, GSE12021, GSE55235, GSE55584, and GSE55457 datasets were downloaded from the Gene Expression Omnibus database. A total of 57 RA samples and 46 OA samples were included. The differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. Protein–protein interaction (PPI) network of DEGs and the hub genes were constructed and visualized via Search Tool for the Retrieval of Interacting Genes/Proteins, Cytoscape, and R. Selected hub genes were validated via reverse transcription-polymerase chain reaction.

Results

A total of 41 DEGs were identified. GO functional enrichment analysis showed that DEGs were enriched in immune response, signal transduction, regulation of immune response for biological process, in plasma membrane and extracellular region for cell component, and antigen binding and serine-type endopeptidase activity for molecular function. KEGG pathway analysis showed that DEGs were enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. PPI network analysis established 70 nodes and 120 edges and 15 hub genes were identified. The expression of CXCL13, CXCL10, and ADIPOQ was statistically different between RA and OA synovial tissue.

Conclusion

Differential expression of CXCL13, CXCL10, and ADIPOQ between RA and OA synovial tissue may provide new insights for understanding the RA development and difference between RA and OA.

Key Points

• Bioinformatics analysis was used to identify the differentially expressed genes in the synovial tissue between rheumatoid arthritis and osteoarthritis.

• CXCL13, CXCL10, and ADIPOQ might provide new insight for understanding the differences between RA and OA.

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Titel: Identification of differential key biomarkers in the synovial tissue between rheumatoid arthritis and osteoarthritis using bioinformatics analysis
verfasst von: Runrun Zhang
Xinpeng Zhou
Yehua Jin
Cen Chang
Rongsheng Wang
Jia Liu
Junyu Fan
Dongyi He
Publikationsdatum: 05.07.2021
Verlag: Springer International Publishing
Erschienen in: Clinical Rheumatology / Ausgabe 12/2021
Print ISSN: 0770-3198
Elektronische ISSN: 1434-9949
DOI: https://doi.org/10.1007/s10067-021-05825-1

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Abstract

Introduction/objectives

Method

Results

Conclusion

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