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Bone & Joint Research
Vol. 12, Issue 12 | Pages 702 - 711
1 Dec 2023
Xue Y Zhou L Wang J

Aims

Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA.

Methods

First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers.


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.


Bone & Joint Research
Vol. 11, Issue 9 | Pages 669 - 678
1 Sep 2022
Clement RGE Hall AC Wong SJ Howie SEM Simpson AHRW

Aims

Staphylococcus aureus is a major cause of septic arthritis, and in vitro studies suggest α haemolysin (Hla) is responsible for chondrocyte death. We used an in vivo murine joint model to compare inoculation with wild type S. aureus 8325-4 with a Hla-deficient strain DU1090 on chondrocyte viability, tissue histology, and joint biomechanics. The aim was to compare the actions of S. aureus Hla alone with those of the animal’s immune response to infection.

Methods

Adult male C57Bl/6 mice (n = 75) were randomized into three groups to receive 1.0 to 1.4 × 107 colony-forming units (CFUs)/ml of 8325-4, DU1090, or saline into the right stifle joint. Chondrocyte death was assessed by confocal microscopy. Histological changes to inoculated joints were graded for inflammatory responses along with gait, weight changes, and limb swelling.


Bone & Joint Research
Vol. 9, Issue 11 | Pages 789 - 797
2 Nov 2020
Seco-Calvo J Sánchez-Herráez S Casis L Valdivia A Perez-Urzelai I Gil J Echevarría E

Aims. To analyze the potential role of synovial fluid peptidase activity as a measure of disease burden and predictive biomarker of progression in knee osteoarthritis (KOA). Methods. A cross-sectional study of 39 patients (women 71.8%, men 28.2%; mean age of 72.03 years (SD 1.15) with advanced KOA (Ahlbäck grade ≥ 3 and clinical indications for arthrocentesis) recruited through the (Orthopaedic Department at the Complejo Asistencial Universitario de León, Spain (CAULE)), measuring synovial fluid levels of puromycin-sensitive aminopeptidase (PSA), neutral aminopeptidase (NAP), aminopeptidase B (APB), prolyl endopeptidase (PEP), aspartate aminopeptidase (ASP), glutamyl aminopeptidase (GLU) and pyroglutamyl aminopeptidase (PGAP). Results. Synovial fluid peptidase activity varied significantly as a function of clinical signs, with differences in levels of PEP (p = 0.020), ASP (p < 0.001), and PGAP (p = 0. 003) associated with knee locking, PEP (p = 0.006), ASP (p = 0.001), GLU (p = 0.037), and PGAP (p = 0.000) with knee failure, and PEP (p = 0.006), ASP (p = 0.001), GLU (p = 0.037), and PGAP (p < 0.001) with knee effusion. Further, patients with the greatest functional impairment had significantly higher levels of APB (p = 0.005), PEP (p = 0.005), ASP (p = 0.006), GLU (p = 0.020), and PGAP (p < 0.001) activity, though not of NAP or PSA, indicating local alterations in the renin-angiotensin system. A binary logistic regression model showed that PSA was protective (p = 0.005; Exp (B) 0.949), whereas PEP (p = 0.005) and GLU were risk factors (p = 0.012). Conclusion. These results suggest synovial fluid peptidase activity could play a role as a measure of disease burden and predictive biomarker of progression in KOA. Cite this article: Bone Joint Res 2020;9(11):789–797


Bone & Joint Research
Vol. 9, Issue 9 | Pages 623 - 632
5 Sep 2020
Jayadev C Hulley P Swales C Snelling S Collins G Taylor P Price A

Aims

The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA).

Methods

Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.