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
Methods
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
Methods
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
Methods
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
Methods
This study investigates the effects of intra-articular injection of adipose-derived mesenchymal stem cells (AdMSCs) and platelet-rich plasma (PRP) on lameness, pain, and quality of life in osteoarthritic canine patients. With informed owner consent, adipose tissue collected from adult dogs diagnosed with degenerative joint disease was enzymatically digested and cultured to passage 1. A small portion of cells (n = 4) surplus to clinical need were characterized using flow cytometry and tri-lineage differentiation. The impact and degree of osteoarthritis (OA) was assessed using the Liverpool Osteoarthritis in Dogs (LOAD) score, Modified Canine Osteoarthritis Staging Tool (mCOAST), kinetic gait analysis, and diagnostic imaging. Overall, 28 joints (25 dogs) were injected with autologous AdMSCs and PRP. The patients were followed up at two, four, eight, 12, and 24 weeks. Data were analyzed using two related-samples Wilcoxon signed-rank or Mann-Whitney U tests with statistical significance set at p < 0.05.Aims
Methods
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). 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.Aims
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