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
This study aimed to investigate the role and mechanism of meniscal cell lysate (MCL) in fibroblast-like synoviocytes (FLSs) and osteoarthritis (OA). Meniscus and synovial tissue were collected from 14 patients with and without OA. MCL and FLS proteins were extracted and analyzed by liquid chromatography‒mass spectrometry (LC‒MS). The roles of MCL and adenine nucleotide translocase 3 (ANT3) in FLSs were examined by enzyme-linked immunosorbent assay (ELISA), flow cytometry, immunofluorescence, and transmission electron microscopy. Histological analysis was performed to determine ANT3 expression levels in a male mouse model.Aims
Methods
Aims. To explore the synovial expression of mucin 1 (MUC1) and its role in rheumatoid arthritis (RA), as well as the possible downstream mechanisms. Methods. Patients with qualified synovium samples were recruited from a RA
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
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
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
