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. 2021 Sep 28;158(1):37.
doi: 10.1186/s41065-021-00201-0.

Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

Yanzhi Ge #  1 , Zuxiang Chen #  1 , Yanbin Fu #  2 , Xiujuan Xiao #  3 , Haipeng Xu  4 , Letian Shan  5 , Peijian Tong  6 , Li Zhou  7
Affiliations

Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

Yanzhi Ge et al. Hereditas. .

Abstract

Background: Osteoarthritis (OA) and rheumatoid arthritis (RA) were two major joint diseases with similar clinical phenotypes. This study aimed to determine the mechanistic similarities and differences between OA and RA by integrated analysis of multiple gene expression data sets.

Methods: Microarray data sets of OA and RA were obtained from the Gene Expression Omnibus (GEO). By integrating multiple gene data sets, specific differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interaction (PPI) network analysis of DEGs were conducted to determine hub genes and pathways. The "Cell Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)" algorithm was employed to evaluate the immune infiltration cells (IICs) profiles in OA and RA. Moreover, mouse models of RA and OA were established, and selected hub genes were verified in synovial tissues with quantitative polymerase chain reaction (qPCR).

Results: A total of 1116 DEGs were identified between OA and RA. GO functional enrichment analysis showed that DEGs were enriched in regulation of cell morphogenesis involved in differentiation, positive regulation of neuron differentiation, nuclear speck, RNA polymerase II transcription factor complex, protein serine/threonine kinase activity and proximal promoter sequence-specific DNA binding. KEGG pathway analysis showed that DEGs were enriched in EGFR tyrosine kinase inhibitor resistance, ubiquitin mediated proteolysis, FoxO signaling pathway and TGF-beta signaling pathway. Immune cell infiltration analysis identified 9 IICs with significantly different distributions between OA and RA samples. qPCR results showed that the expression levels of the hub genes (RPS6, RPS14, RPS25, RPL11, RPL27, SNRPE, EEF2 and RPL19) were significantly increased in OA samples compared to their counterparts in RA samples (P < 0.05).

Conclusion: This large-scale gene analyses provided new insights for disease-associated genes, molecular mechanisms as well as IICs profiles in OA and RA, which may offer a new direction for distinguishing diagnosis and treatment between OA and RA.

Keywords: Bioinformatics analysis; Differentially expressed genes; Immune infiltration; Osteoarthritis; Rheumatoid arthritis.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Schematic diagram of the whole study
Fig. 2
Fig. 2
Flow chart of GEO series accession screening
Fig. 3
Fig. 3
The process of DEGs screening. A Venn diagram of shared DEGs between OA, RA and NC. The yellow circle represents DEGs in NC and OA, the blue circle represents DEGs in health and RA, and the red circle represents DEGs in OA and RA. B Volcano plot of all DEGs between health and OA. C Volcano plot of all DEGs between health and RA. D Volcano plot of all DEGs between OA and RA. E Heatmap of DEGs. The row represents the expression of DEG, and the column represents the samples. The different color scale represents the different expression levels. F Before and after normalization of DEGs in three groups
Fig. 4
Fig. 4
GO enrichment, KEGG terms and GSEA pathway analysis of DEGs. A GO terms in the OA-related enrichment analysis of DEGs. B GO terms in the RA-related enrichment analysis of DEGs. C OA-related pathway enrichment analysis of DEGs. D RA-related pathway enrichment analysis of DEGs. E GSEA analysis of DEGs between OA and RA
Fig. 5
Fig. 5
Hub genes of OA-specific and RA-specific PPI networks. A OA relative PPI network. B RA relative PPI network. C PPI network constructed by DEGs between OA and RA. D Three groups of top 20 connections in PPI network. The red and blue rectangles represent the proteins encoded by up or down-regulated DEGs, respectively. The larger rectangles indicate the higher degree in networks
Fig. 6
Fig. 6
The profiles of immune infiltration between OA and RA. A The percentage of 22 subpopulations of IICs. B Violin plot showing the difference of immune infiltration between OA (Marked as blue color on the left) and RA (Marked as red color on the right). Adjusted-P values < 0.05 were considered as statistical significance. C The correlation analysis of the 22 immune cells. The red color represents the positive relationship between two immune cells and the blue color represents the negative relationship between two immune cells. The darker color indicates the stronger correlation
Fig. 7
Fig. 7
Animal experiments. A Assessing the OA model using the mechanical allodynia. B Arthritis index score to assess RA model. C Relative mRNA expressions of target genes in synovial membrane from NC, OA and RA mice. Values are presented as mean ± SD. #P < 0.05 or ##P < 0.01 vs. NC group; **P < 0.01 vs. OA group
See this image and copyright information in PMC

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