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

Abstract

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.

Keywords: Gene expression; Osteoarthritis; Protein-protein interaction network; Transcriptional factors.

Fig. 1

CapChart showing the top 15 significant enrichment molecular functions of differentially expressed genes (DEGs). The x-axis shows support/reference numbers and false discovery rate (FDR) value of DEGs; the y-axis shows different molecular functions.

Fig. 2

Chart showing the top 15 significant enrichment biological processes of differentially expressed genes (DEGs). The x-axis shows support/reference numbers and false discovery rate (FDR) value of DEGs; the y-axis shows different biological processes.

Fig. 3

Chart showing the top 15 significant enrichment cellular components of differentially expressed genes (DEGs). The x-axis shows support/reference numbers and false discovery rate (FDR) value of DEGs; the y-axis shows different cellular components.

Fig. 4

Chart showing the top 15 Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of differentially expressed genes (DEGs). The x-axis shows support/reference numbers and false discovery rate (FDR) value of DEGs; the y-axis shows different signal pathways.

Fig. 5

The protein-protein interaction (PPI) networks of the top 20 upregulated differentially expressed genes (DEGs). All the nodes are proteins encoded by DEGs and the red borders represent proteins encoded by the top 20 upregulated DEGs; purple borders represent proteins encoded by other genes that interacted with proteins encoded by these DEGs.

Fig. 6

The protein-protein interaction (PPI) networks of the top 20 downregulated differentially expressed genes (DEGs). All the nodes are proteins encoded by DEGs and the green borders represent proteins encoded by top 20 downregulated DEGs; purple borders represent proteins encoded by other genes interacted with proteins encoded by these DEGs.

Fig. 7

The established transcriptional regulatory network of osteoarthritis. Red- and green-coloured nodes represent products of up- and downregulated differentially expressed genes (DEGs), respectively. The purple nodes denote products of transcriptional factors (TFs) predicted to interact with the corresponding DEGs.

Fig. 8

The validation of the expression levels of selected DEGs in OA based on GSE89408 database. The x-axis shows the case and normal groups and y-axis shows expression reads counts.

Fig. 9

Receiver operator characteristic (ROC) curves of selected differentially expressed genes (DEGs) between osteoarthritic patients and healthy controls. The ROC curves were used to show the diagnostic ability of these selected DEGs with 1-specificity (the proportion of false positive) and sensitivity (the proportion of true positive).