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
Aims. Mendelian randomization (MR) is considered to overcome the bias of observational studies, but there is no current meta-analysis of MR studies on rheumatoid arthritis (RA). The purpose of this study was to summarize the relationship between potential pathogenic factors and RA risk
Aims. Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method. Methods. We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap)
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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To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment. Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue.Aims
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To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design. Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics.Aims
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cAMP response element binding protein (CREB1) is involved in the progression of osteoarthritis (OA). However, available findings about the role of CREB1 in OA are inconsistent. 666-15 is a potent and selective CREB1 inhibitor, but its role in OA is unclear. This study aimed to investigate the precise role of CREB1 in OA, and whether 666-15 exerts an anti-OA effect. CREB1 activity and expression of a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) in cells and tissues were measured by immunoblotting and immunohistochemical (IHC) staining. The effect of 666-15 on chondrocyte viability and apoptosis was examined by cell counting kit-8 (CCK-8) assay, JC-10, and terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling (TUNEL) staining. The effect of 666-15 on the microstructure of subchondral bone, and the synthesis and catabolism of cartilage, in anterior cruciate ligament transection mice were detected by micro-CT, safranin O and fast green (S/F), immunohistochemical staining, and enzyme-linked immunosorbent assay (ELISA).Aims
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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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Rheumatoid arthritis (RA) is a common chronic immune disease. Berberine, as its main active ingredient, was also contained in a variety of medicinal plants such as Berberaceae, Buttercup, and Rutaceae, which are widely used in digestive system diseases in traditional Chinese medicine with anti-inflammatory and antibacterial effects. The aims of this article were to explore the therapeutic effect and mechanism of berberine on rheumatoid arthritis. Cell Counting Kit-8 was used to evaluate the effect of berberine on the proliferation of RA fibroblast-like synoviocyte (RA-FLS) cells. The effect of berberine on matrix metalloproteinase (MMP)-1, MMP-3, receptor activator of nuclear factor kappa-Β ligand (RANKL), tumour necrosis factor alpha (TNF-α), and other factors was determined by enzyme-linked immunoassay (ELISA) kit. Transcriptome technology was used to screen related pathways and the potential targets after berberine treatment, which were verified by reverse transcription-polymerase chain reaction (RT-qPCR) and Western blot (WB) technology.Aims
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This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. 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.Aims
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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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Osteoarthritis (OA) is a common degenerative joint disease characterized by chronic inflammatory articular cartilage degradation. Long noncoding RNAs (lncRNAs) have been previously indicated to play an important role in inflammation-related diseases. Herein, the current study set out to explore the involvement of lncRNA H19 in OA. Firstly, OA mouse models and interleukin (IL)-1β-induced mouse chondrocytes were established. Expression patterns of IL-38 were determined in the synovial fluid and cartilage tissues from OA patients. Furthermore, the targeting relationship between lncRNA H19, tumour protein p53 (TP53), and IL-38 was determined by means of dual-luciferase reporter gene, chromatin immunoprecipitation, and RNA immunoprecipitation assays. Subsequent to gain- and loss-of-function assays, the levels of cartilage damage and proinflammatory factors were further detected using safranin O-fast green staining and enzyme-linked immunosorbent assay (ELISA) in vivo, respectively, while chondrocyte apoptosis was measured using Terminal deoxynucleotidyl transferase dUTP Nick-End Labeling (TUNEL) in vitro.Aims
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Osteoarthritis (OA) is a highly prevalent degenerative joint disorder characterized by joint pain and physical disability. Aberrant subchondral bone induces pathological changes and is a major source of pain in OA. In the subchondral bone, which is highly innervated, nerves have dual roles in pain sensation and bone homeostasis regulation. The interaction between peripheral nerves and target cells in the subchondral bone, and the interplay between the sensory and sympathetic nervous systems, allow peripheral nerves to regulate subchondral bone homeostasis. Alterations in peripheral innervation and local transmitters are closely related to changes in nociception and subchondral bone homeostasis, and affect the progression of OA. Recent literature has substantially expanded our understanding of the physiological and pathological distribution and function of specific subtypes of neurones in bone. This review summarizes the types and distribution of nerves detected in the tibial subchondral bone, their cellular and molecular interactions with bone cells that regulate subchondral bone homeostasis, and their role in OA pain. A comprehensive understanding and further investigation of the functions of peripheral innervation in the subchondral bone will help to develop novel therapeutic approaches to effectively prevent OA, and alleviate OA pain. Cite this article:
Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA. Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.Aims
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Aims. 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. Methods. 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
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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Osteoarthritis (OA) is the most prevalent systemic musculoskeletal disorder, characterized by articular cartilage degeneration and subchondral bone (SCB) sclerosis. Here, we sought to examine the contribution of accelerated growth to OA development using a murine model of excessive longitudinal growth. Suppressor of cytokine signalling 2 (SOCS2) is a negative regulator of growth hormone (GH) signalling, thus mice deficient in SOCS2 ( We examined vulnerability of Aims
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Circular RNA (circRNA) S-phase cyclin A-associated protein in the endoplasmic reticulum (ER) (circSCAPER, ID: hsa_circ_0104595) has been found to be highly expressed in osteoarthritis (OA) patients and has been associated with the severity of OA. Hence, the role and mechanisms underlying circSCAPER in OA were investigated in this study. In vitro cultured human normal chondrocyte C28/I2 was exposed to interleukin (IL)-1β to mimic the microenvironment of OA. The expression of circSCAPER, microRNA (miR)-140-3p, and enhancer of zeste homolog 2 (EZH2) was detected using quantitative real-time polymerase chain reaction and Western blot assays. The extracellular matrix (ECM) degradation, proliferation, and apoptosis of chondrocytes were determined using Western blot, cell counting kit-8, and flow cytometry assays. Targeted relationships were predicted by bioinformatic analysis and verified using dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. The levels of phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) pathway-related protein were detected using Western blot assays.Aims
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Deciphering the genetic relationships between major depressive disorder (MDD) and osteoarthritis (OA) may facilitate an understanding of their biological mechanisms, as well as inform more effective treatment regimens. We aim to investigate the mechanisms underlying relationships between MDD and OA in the context of common genetic variations. Linkage disequilibrium score regression was used to test the genetic correlation between MDD and OA. Polygenic analysis was performed to estimate shared genetic variations between the two diseases. Two-sample bidirectional Mendelian randomization analysis was used to investigate causal relationships between MDD and OA. Genomic loci shared between MDD and OA were identified using cross-trait meta-analysis. Fine-mapping of transcriptome-wide associations was used to prioritize putatively causal genes for the two diseases.Aims
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