Aims. To explore key stakeholder views around feasibility and acceptability of
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 based on existing MR studies. PubMed, Web of Science, and Embase were searched for MR studies on influencing factors in relation to RA up to October 2022. Meta-analyses of MR studies assessing correlations between various potential pathogenic factors and RA were conducted. Random-effect and fixed-effect models were used to synthesize the odds ratios of various pathogenic factors and RA. The quality of the study was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines.Aims
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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.Aims
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Insufficient treatment response in rheumatoid arthritis (RA) patients requires novel treatment strategies to halt disease progression. The potential benefit of combination of cytokine-inhibitors in RA is still unclear and needs further investigation. To explore the impact of combined deficiency of two major cytokines, namely interleukin (IL)-1 and IL-6, in this study double deficient mice for IL-1αβ and IL-6 were investigated in different tumour necrosis factor (TNF)-driven inflammatory bone disorders, namely peripheral arthritis and sacroiliitis, as well as systemic bone loss. Disease course, histopathological features of arthritis, and micro-CT (µCT) bone analysis of local and systemic bone loss were assessed in 15-week-old 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:
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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Rheumatoid arthritis (RA) is an autoimmune disease characterized by symmetrical and chronic polyarthritis. Fibroblast-like synoviocytes are mainly involved in joint inflammation and cartilage and bone destruction by inflammatory cytokines and matrix-degrading enzymes in RA. Approaches that induce various cellular growth alterations of synoviocytes are considered as potential strategies for treating RA. However, since synoviocytes play a critical role in RA, the mechanism and hyperplastic modulation of synoviocytes and their motility need to be addressed. In this review, we focus on the alteration of synoviocyte signalling and cell fate provided by signalling proteins, various antioxidant molecules, enzymes, compounds, clinical candidates, to understand the pathology of the synoviocytes, and finally to achieve developed therapeutic strategies of RA. Cite this article:
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. Results. PLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model. Conclusion. SF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy
The aim of this study was to systematically review the literature for evidence of the effect of a high-fat diet (HFD) on the onset or progression of osteoarthritis (OA) in mice. A literature search was performed in PubMed, Embase, Web of Science, and Scopus to find all studies on mice investigating the effects of HFD or Western-type diet on OA when compared with a control diet (CD). The primary outcome was the determination of cartilage loss and alteration. Secondary outcomes regarding local and systemic levels of proteins involved in inflammatory processes or cartilage metabolism were also examined when reported.Aims
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