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Bone & Joint Research
Vol. 13, Issue 6 | Pages 261 - 271
1 Jun 2024
Udomsinprasert W Mookkhan N Tabtimnark T Aramruang T Ungsudechachai T Saengsiwaritt W Jittikoon J Chaikledkaew U Honsawek S

Aims. This study aimed to determine the expression and clinical significance of a cartilage protein, cartilage oligomeric matrix protein (COMP), in knee osteoarthritis (OA) patients. Methods. A total of 270 knee OA patients and 93 healthy controls were recruited. COMP messenger RNA (mRNA) and protein levels in serum, synovial fluid, synovial tissue, and fibroblast-like synoviocytes (FLSs) of knee OA patients were determined using enzyme-linked immunosorbent assay, real-time polymerase chain reaction, and immunohistochemistry. Results. COMP protein levels were significantly elevated in serum and synovial fluid of knee OA patients, especially those in the advanced stages of the disease. Serum COMP was significantly correlated with radiological severity as well as measures of body composition, physical performance, knee pain, and disability. Receiver operating characteristic curve analysis unveiled a diagnostic value of serum COMP as a biomarker of knee OA (41.64 ng/ml, area under the curve (AUC) = 1.00), with a sensitivity of 99.6% and a specificity of 100.0%. Further analysis uncovered that COMP mRNA expression was markedly upregulated in the inflamed synovium of knee OA, consistent with immunohistochemical staining revealing localization of COMP protein in the lining and sub-lining layers of knee OA inflamed synovium. Most notably, relative COMP mRNA expression in knee OA synovium was positively associated with its protein levels in serum and synovial fluid of knee OA patients. In human knee OA FLSs activated with tumour necrosis factor-alpha, COMP mRNA expression was considerably up-regulated in a time-dependent manner. Conclusion. All results indicate that COMP might serve as a supportive diagnostic marker for knee OA in conjunction with the standard diagnostic methods. Cite this article: Bone Joint Res 2024;13(6):261–271


Bone & Joint Research
Vol. 12, Issue 2 | Pages 121 - 132
1 Feb 2023
Mo H Wang Z He Z Wan J Lu R Wang C Chen A Cheng P

Aims

Pellino1 (Peli1) has been reported to regulate various inflammatory diseases. This study aims to explore the role of Peli1 in the occurrence and development of osteoarthritis (OA), so as to find new targets for the treatment of OA.

Methods

After inhibiting Peli1 expression in chondrocytes with small interfering RNA (siRNA), interleukin (IL)-1β was used to simulate inflammation, and OA-related indicators such as synthesis, decomposition, inflammation, and apoptosis were detected. Toll-like receptor (TLR) and nuclear factor-kappa B (NF-κB) signalling pathway were detected. After inhibiting the expression of Peli1 in macrophages Raw 264.7 with siRNA and intervening with lipopolysaccharide (LPS), the polarization index of macrophages was detected, and the supernatant of macrophage medium was extracted as conditioned medium to act on chondrocytes and detect the apoptosis index. The OA model of mice was established by destabilized medial meniscus (DMM) surgery, and adenovirus was injected into the knee cavity to reduce the expression of Peli1. The degree of cartilage destruction and synovitis were evaluated by haematoxylin and eosin (H&E) staining, Safranin O/Fast Green staining, and immunohistochemistry.


Bone & Joint Research
Vol. 7, Issue 4 | Pages 298 - 307
1 Apr 2018
Zhang X Bu Y Zhu B Zhao Q Lv Z Li B Liu J

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.