Analysis of differentially expressed genes and biological information between rheumatoid arthritis and osteoarthritis based on the GEO database

In the present study, we investigated the relationship between rheumatoid arthritis (RA) and knee osteoarthritis (OA) using bioinformatics, aiming to identify the differentially expressed genes (DEGs) of RA and explore the possible mechanism of RA. The GSE55584 and GSE153015 microarray datasets for RA and OA gene expression profiles were acquired from the Gene Expression Omnibus (GEO) database. The DEGs of the two datasets were obtained by R language processing and analysis. The intersecting DEGs were obtained using the Venny 2.1 platform. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genome (KEGG) enrichment analyses were performed using the DAVID platform, and the microbubble map was drawn online by importing the microbubble generation platform. All the obtained DEGs and the intersecting DEGs were imported into the STRING platform to obtain a protein-protein interaction network (PPI) and then into Cytoscape 3.9.1 software to screen core genes (hub genes). A total of 665 DEGs were obtained from the GSE55584 and GSE153015 datasets, including 324 upregulated and 341 downregulated DEGs. GO enrichment analysis showed that the biological processes in which DEGs were mainly enriched included signal transduction, immune response, inflammatory response, adaptive immune response, and G protein-coupled receptor signalling pathway. KEGG enrichment analysis of the DEGs identified the following enriched pathways: cytokine-cytokine receptor interaction; chemokine signalling pathway; viral protein interaction with cytokines and cytokine receptors; and apoptosis. Ten core genes (hub genes) were screened out, namely, CD3D, CD27, KLRB1, CCL5, GZMB, GZMA, GZMK, GNLY, CD2, and NKG7. Among them, CD3D, CD27, KLRB1, CCL5, and GZMB were most significantly correlated with the occurrence and development of RA. In the present study, bioinformatics analysis provided supporting evidence for the biological process and key genes of RA.

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Journal
Nucleosides Nucleotides & Nucleic Acids
Published
2025-08-20
DOI
https://doi.org/10.1080/15257770.2025.2540414
Primary Topic
Rheumatoid Arthritis Research and Therapies
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article
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0.00
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article

Analysis of differentially expressed genes and biological information between rheumatoid arthritis and osteoarthritis based on the GEO database

Siying Wang, Qianwen Xiong, Jietong Zhang, Guohai Li et al.
Nucleosides Nucleotides & Nucleic Acids
Rheumatoid Arthritis Research and Therapies
article

Analysis of differentially expressed genes and biological information between rheumatoid arthritis and osteoarthritis based on the GEO database

Siying Wang, Qianwen Xiong, Jietong Zhang, Guohai Li, Jiuhong He, Zhicheng Li, Shuwen Li, Zeli Li
article en

Abstract

In the present study, we investigated the relationship between rheumatoid arthritis (RA) and knee osteoarthritis (OA) using bioinformatics, aiming to identify the differentially expressed genes (DEGs) of RA and explore the possible mechanism of RA. The GSE55584 and GSE153015 microarray datasets for RA and OA gene expression profiles were acquired from the Gene Expression Omnibus (GEO) database. The DEGs of the two datasets were obtained by R language processing and analysis. The intersecting DEGs were obtained using the Venny 2.1 platform. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genome (KEGG) enrichment analyses were performed using the DAVID platform, and the microbubble map was drawn online by importing the microbubble generation platform. All the obtained DEGs and the intersecting DEGs were imported into the STRING platform to obtain a protein-protein interaction network (PPI) and then into Cytoscape 3.9.1 software to screen core genes (hub genes). A total of 665 DEGs were obtained from the GSE55584 and GSE153015 datasets, including 324 upregulated and 341 downregulated DEGs. GO enrichment analysis showed that the biological processes in which DEGs were mainly enriched included signal transduction, immune response, inflammatory response, adaptive immune response, and G protein-coupled receptor signalling pathway. KEGG enrichment analysis of the DEGs identified the following enriched pathways: cytokine-cytokine receptor interaction; chemokine signalling pathway; viral protein interaction with cytokines and cytokine receptors; and apoptosis. Ten core genes (hub genes) were screened out, namely, CD3D, CD27, KLRB1, CCL5, GZMB, GZMA, GZMK, GNLY, CD2, and NKG7. Among them, CD3D, CD27, KLRB1, CCL5, and GZMB were most significantly correlated with the occurrence and development of RA. In the present study, bioinformatics analysis provided supporting evidence for the biological process and key genes of RA.

Nucleosides Nucleotides & Nucleic Acids
Guangzhou University of Chinese Medicine (CN), Dongguan People’s Hospital (CN)
Openalex Percentile: Top 67%
Rheumatoid Arthritis Research and Therapies
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