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. 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
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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
The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA. Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database.Aims
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Osteoarthritis (OA) is a chronic degenerative joint disease characterized by progressive cartilage degradation, synovial membrane inflammation, osteophyte formation, and subchondral bone sclerosis. Pathological changes in cartilage and subchondral bone are the main processes in OA. In recent decades, many studies have demonstrated that activin-like kinase 3 (ALK3), a bone morphogenetic protein receptor, is essential for cartilage formation, osteogenesis, and postnatal skeletal development. Although the role of bone morphogenetic protein (BMP) signalling in articular cartilage and bone has been extensively studied, many new discoveries have been made in recent years around ALK3 targets in articular cartilage, subchondral bone, and the interaction between the two, broadening the original knowledge of the relationship between ALK3 and OA. In this review, we focus on the roles of ALK3 in OA, including cartilage and subchondral bone and related cells. It may be helpful to seek more efficient drugs or treatments for OA based on ALK3 signalling in future.
To explore the synovial expression of mucin 1 (MUC1) and its role in rheumatoid arthritis (RA), as well as the possible downstream mechanisms. Patients with qualified synovium samples were recruited from a RA cohort. Synovium from patients diagnosed as non-inflammatory orthopaedic arthropathies was obtained as control. The expression and localization of MUC1 in synovium and fibroblast-like synoviocytes were assessed by immunohistochemistry and immunofluorescence. Small interfering RNA and MUC1 inhibitor GO-203 were adopted for inhibition of MUC1. Lysophosphatidic acid (LPA) was used as an activator of Rho-associated pathway. Expression of inflammatory cytokines, cell migration, and invasion were evaluated using quantitative real-time polymerase chain reaction (PCR) and Transwell chamber assay.Aims
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Exosomes (exo) are involved in the progression of osteoarthritis (OA). This study aimed to investigate the function of dysfunctional chondrocyte-derived exo (DC-exo) on OA in rats and rat macrophages. Rat-derived chondrocytes were isolated, and DCs induced with interleukin (IL)-1β were used for exo isolation. Rats with OA (n = 36) or macrophages were treated with DC-exo or phosphate-buffered saline (PBS). Macrophage polarization and autophagy, and degradation and chondrocyte activity of cartilage tissues, were examined. RNA sequencing was used to detect genes differentially expressed in DC-exo, followed by RNA pull-down and ribonucleoprotein immunoprecipitation (RIP). Long non-coding RNA osteoarthritis non-coding transcript (OANCT) and phosphoinositide-3-kinase regulatory subunit 5 (PIK3R5) were depleted in DC-exo-treated macrophages and OA rats, in order to observe macrophage polarization and cartilage degradation. The PI3K/AKT/mammalian target of rapamycin (mTOR) pathway activity in cells and tissues was measured using western blot.Aims
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Post-traumatic osteoarthritis (PTOA) is a subset of osteoarthritis (OA). The gut microbiome is shown to be involved in OA. However, the effect of exercise on gut microbiome in PTOA remains elusive. A total of 18 eight-week Sprague-Dawley rats were assigned into three groups: Sham/sedentary (Sham/Sed), PTOA/sedentary (PTOA/Sed), and PTOA/treadmill-walking (PTOA/TW). PTOA model was induced by transection of the anterior cruciate ligament (ACLT) and the destabilization of the medial meniscus (DMM). Treadmill-walking (15 m/min, 30 min/d, five days/week for eight weeks) was employed in the PTOA/TW group. The response of cartilage, subchondral bone, serology, and gut microbiome and their correlations were assessed.Aims
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The aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA). Based on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls.Aims
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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). 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).Aims
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Parathyroid hormone (PTH) (1-34) exhibits potential in preventing degeneration in both cartilage and subchondral bone in osteoarthritis (OA) development. We assessed the effects of PTH (1-34) at different concentrations on bone and cartilage metabolism in a collagenase-induced mouse model of OA and examined whether PTH (1-34) affects the JAK2/STAT3 signalling pathway in this process. Collagenase-induced OA was established in C57Bl/6 mice. Therapy with PTH (1-34) (10 μg/kg/day or 40 μg/kg/day) was initiated immediately after surgery and continued for six weeks. Cartilage pathology was evaluated by gross visual, histology, and immunohistochemical assessments. Cell apoptosis was analyzed by TUNEL staining. Microcomputed tomography (micro-CT) was used to evaluate the bone mass and the microarchitecture in subchondral bone.Aims
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This study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network. Expression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs.Aims
Methods
Osteoarthritis (OA) is the most prevalent joint disease. However, the specific and definitive genetic mechanisms of OA are still unclear. Tissue-related transcriptome-wide association studies (TWAS) of hip OA and knee OA were performed utilizing the genome-wide association study (GWAS) data of hip OA and knee OA (including 2,396 hospital-diagnosed hip OA patients versus 9,593 controls, and 4,462 hospital-diagnosed knee OA patients versus 17,885 controls) and gene expression reference to skeletal muscle and blood. The OA-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the messenger RNA (mRNA) expression profiles of hip OA and knee OA. Functional enrichment and annotation analysis of identified genes was performed by the DAVID and FUMAGWAS tools.Aims
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