Abstract
BackgroundOsteoarthritis (OA) is the most common chronic joint disease worldwide. It is characterized by pain and limited mobility in the affected joints and may even cause disability. Effective clinical options for its prevention and treatment are still unavailable. This study aimed to identify differences in gene signatures between tissue samples from OA and normal knee joints and to explore potential gene targets for OA.MethodsFive gene datasets, namely GSE55457, GSE55235, GSE12021, GSE10575, and GSE1919, were selected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the R programming software. The functions of these DEGs were analyzed, and a protein–protein interaction (PPI) network was constructed. Subsequently, the most relevant biomarker genes were screened using a receiver operating characteristic (ROC) curve analysis. Finally, the expression of the protein encoded by the core gene PTHLH was evaluated in clinical samples.ResultsEleven upregulated and 9 downregulated DEGs were shared between the five gene expression datasets. Based on the PPI network and the ROC curves of upregulated genes, PTHLH was identified as the most relevant gene for OA and was selected for further validation. Immunohistochemistry confirmed significantly higher PTHLH expression in OA tissues than in normal tissues. Moreover, similar PTHLH levels were detected in the plasma and knee synovial fluid of OA patients.ConclusionThe bioinformatics analysis and preliminary experimental verification performed in this study identified PTHLH as a potential target for the treatment of OA.
Highlights
Osteoarthritis (OA) is the most prevalent chronic joint disease affecting adults [1,2,3]
Identification of 20 Differentially expressed genes (DEGs) shared between five Gene Expression Omnibus (GEO) profiles We first analyzed the DEGs in the five GEO gene datasets and identified 1334, 1521, 1384, 3393, and 732 DEGs, Table 3 Patient information of blood samples and synovial fluid samples
Gene Ontology (GO) functional enrichment analysis a GO functional enrichment analysis was performed using the R package clusterProfiler to identify the functions of the DEGs, which were classified into the groups of biological processes (BP), cellular component (CC), and molecular function (MF) (Fig. 2)
Summary
Osteoarthritis (OA) is the most prevalent chronic joint disease affecting adults [1,2,3]. It causes chronic pain, restricted joint mobility, and disability [4]. Considerable research attention has been directed toward the identification of effective biomarkers and potential therapeutic targets for OA. Osteoarthritis (OA) is the most common chronic joint disease worldwide. It is characterized by pain and limited mobility in the affected joints and may even cause disability.
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