CCAAT/enhancer binding protein β (C/EBPβ) regulates the transcription of growth arrest and DNA damage-inducible protein 45 β (GADD45β) in articular chondrocytes

Candidate Marker Genes for Diagnosis of Osteoarthritis and Prediction of Their Regulatory Mechanisms

We have screened candidate marker genes for the diagnosis of osteoarthritis and predicted their regulatory mechanisms. Six expression chips of tissue samples and one expression chip of peripheral blood mononuclear cell (PMBC) samples were obtained from the GEO database. Differential analysis, GSEA, and WGCNA were performed on the integra-ted tissue sample data with batch correction. Can-didate genes were obtained from the intersection of the genes significantly related to osteoarthritis in the WGCNA and the differentially expressed genes. ROC analysis was performed on the candidate genes in the tissue and PMBC samples. Genes with AUC values greater than 0.6 were retained as final candidates, and their upstream regulatory miRNAs were predicted. A total of 106 genes with differential expression were found in osteoarthritis tissue samples, which were mainly enriched in cell cycle and p53 signalling pathways. WGCNA selected a gene module significantly correlated with the occurrence of osteoarthritis. Fourteen candidate genes were obtained from the intersection of the genes in the module and the differentially expressed genes. ROC analysis showed that among these 14 candidate genes, only ADM, CX3CR1 and GADD45A had AUC values greater than 0.6 in both tissue and PMBC samples. The AUC values of the gene set of these three genes were greater than 0.7. Multiple miRNAs were predicted to be regulators of these three genes. ADM, CX3CR1 and GADD45A have potential as diagnostic marker genes for osteoarthritis and may be regulated by multiple miRNAs.

Global transcriptome analysis to identify critical genes involved in the pathology of osteoarthritis

Objectives

The aim of this study was to identify key pathological genes in osteoarthritis (OA).

Methods

We searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis.

Results

A total of 1085 DEGs were identified. KEGG pathway analysis displayed that Wnt was a significantly enriched signalling pathway. Some hub genes with high interactions such as USP46, CPVL, FKBP5, FOSL2, GADD45B, PTGS1, and ZNF423 were identified in the PPI and TFs network. The results of qRT-PCR showed that GADD45B, ADAMTS1, and TFAM were down-regulated in joint synovial tissues of OA, which was consistent with the bioinformatics analysis. The expression levels of USP46, CPVL, FOSL2, and PTGS1 in electronic validation were compatible with the bio-informatics result. CPVL and TFAM had a potential diagnostic value for OA based on the ROC analysis.

Conclusion

The deregulated genes including USP46, CPVL, FKBP5, FOSL2, GADD45B, PTGS1, ZNF423, ADAMTS1, and TFAM might be involved in the pathology of OA.

Cite this article: X. Zhang, Y. Bu, B. Zhu, Q. Zhao, Z. Lv, B. Li, J. Liu. Global transcriptome analysis to identify critical genes involved in the pathology of osteoarthritis. Bone Joint Res 2018;7:298–307. DOI: 10.1302/2046-3758.74.BJR-2017-0245.R1.