ATF3 as a potential diagnostic marker of early-stage osteoarthritis and its correlation with immune infiltration through bioinformatics analysis

Abstract

Aims: This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue.

Methods: The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.

Results: A total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018).

Conclusion: ATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression.Cite this article: Bone Joint Res 2022;11(9):679-689.

Keywords: Bioinformatics analysis; CXCL8; Differentially expressed genes; Early osteoarthritis; Gene Expression; Immune infiltration; Osteoarthritis (OA); Synovial tissue; biomarkers; early osteoarthritis; genes expression profiles; interleukin; interleukin 6; rheumatoid arthritis; synovial tissues.

Fig. 1

Differentially expressed genes (DEGs) of synovial tissue between osteoarthritis (OA) and normal controls. a) Heatmap of DEGs. Red rectangles represent high expression, and blue rectangles represent low expression. b) Volcano plot of DEGs. Red spots represent upregulated genes, and blue spots represent downregulated genes.

Fig. 2

Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and disease ontology (DO) analyses of differentially expressed genes (DEGs) between osteoarthritis (OA) and normal controls. a) Bubble plot showing the top ten GO terms, including four biological processes, two cell components, and four molecular functions. b) KEGG pathway analysis of DEGs between OA and normal controls: the bubble plot shows the top ten enriched KEGG pathways of DEGs. c) Bar plot showing the DO enrichment analysis, where the horizontal axis represents the number of DEGs under the DO terms. IL-17, interleukin 17; NF-kappa B, nuclear factor kappa B; TNF, tumour necrosis factor.

Fig. 3

Protein-protein interaction network of differentially expressed genes (DEGs). The interaction network between proteins coded by DEGs was constructed based on STRING database and Cytoscape software. ARC, activity regulated cytoskeleton associated protein; APOLD1, apolipoprotein L domain containing 1; ATF3, activating transcription factor 3; CCL20, C-C motif chemokine ligand 20; CDKN1A, cyclin dependent kinase inhibitor 1A; CSN1S1, casein alpha s1; CXCL8, C-X-C motif chemokine ligand 8; CXCL2, C-X-C motif chemokine ligand 2; CXCL3, C-X-C motif chemokine ligand 3; CX3CR1, C-X3-C motif chemokine receptor 1; CYR61, as known as CCN1, cellular communication network factor 1; DDIT4, DNA damage inducible transcript 4; DUOX2, dual oxidase 2; DUSP2, dual specificity phosphatase 2; FOSB, FosB proto-oncogene, AP-1 transcription factor subunit; FOSL1, FOS like 1, AP-1 transcription factor subunit; FOSL2, FOS like 2, AP-1 transcription factor subunit; FKBP5, FKBP prolyl isomerase 5; GADD45B, growth arrest and DNA damage inducible beta; HTR2B, 5-hydroxytryptamine receptor 2B; IL1R2, interleukin 1 receptor type 2; IL6, interleukin 6; JUN, Jun proto-oncogene, AP-1 transcription factor subunit; KLF9, KLF transcription factor 9; MAFF, MAF bZIP transcription factor F; MMP1, matrix metallopeptidase 1; MYC, MYC proto-oncogene, bHLH transcription factor; NAMPT, nicotinamide phosphoribosyltransferase; NFIL3, nuclear factor, interleukin 3 regulated; NR4A1, nuclear receptor subfamily 4 group A member 1; NR4A2, nuclear receptor subfamily 4 group A member 2; PTGS2, prostaglandin-endoperoxide synthase 2; RGS1, regulator of G protein signaling 1; SELE, selectin E; SIK1, salt inducible kinase 1; SLC16A7, solute carrier family 16 member 7; SLC18A2, solute carrier family 18 member A2; SLC2A3, solute carrier family 2 member 3; SLC7A5, solute carrier family 7 member 5; SOCS3, suppressor of cytokine signaling 3; TAC1, tachykinin precursor 1; TLR7, toll like receptor 7; TNFSF11, TNF superfamily member 11; TNFRSF11B, TNF receptor superfamily member 11b; TREM2, triggering receptor expressed on myeloid cells 2; WIF1, WNT inhibitory factor 1; WNT5B, Wnt family member 5B; ZFP36, ZFP36 ring finger protein.

Fig. 4

Verification of the six hub genes by two datasets of the Gene Ontology database. a) Verification by GSE12021 (GPL96). Compared with normal controls, all hub genes were downregulated in osteoarthritis (OA) with significance. b) Verification by GSE32317 (GPL570). Compared with early OA, activating transcription factor 3 (ATF3) was downregulated in end-stage OA with significance, while others had no significance. ***p < 0.001; *p < 0.05; ns, no significant difference. CXCL2, C-X-C motif ligand 2; FOSB, FosB proto-oncogene, AP-1 transcription factor subunit; IL6, interleukin-6; JUN, Jun proto-oncogene; AP-1 transcription factor subunit.

Fig. 5

Evaluation and visualization of the landscape of immune infiltration between early-stage osteoarthritis (OA) and end-stage OA. The difference of immune cell infiltration between early-stage OA and end-stage OA. The red marks represent the significant difference in infiltration between the two groups of samples. p < 0.05 was considered statistically significant. NK cells, natural killer cells. ‘Fraction’ refers to the proportion of each immune cell.

Fig. 6

Correlation between activating transcription factor 3 (ATF3) and immune infiltrating cells. The size of the dots represents the strength of the correlation between ATF3 and immune cells: the larger the dots, the stronger the correlation. The colour of the dots represents the p-value: the brighter shade of blue indicates a lower p-value. p < 0.05 was considered statistically significant.