Objectives. Previous genome-wide association studies (GWAS) have reported significant association of the single nucleotide polymorphism (SNP) rs8044769 in the fat mass and obesity-associated gene (FTO) with osteoarthritis (OA) risk in European populations. However, these findings have not been confirmed in Chinese populations. Methods. We systematically genotyped rs8044769 and evaluated the association between the genetic variants and
Introduction. Osteoarthritis (OA) is a progressively debilitating disease that
affects mostly cartilage, with associated changes in the bone. The
increasing incidence of
Osteoarthritis (OA) is mainly caused by ageing, strain, trauma, and congenital joint abnormalities, resulting in articular cartilage degeneration. During the pathogenesis of
Aims. To assess the incidence of radiological lateral osteoarthritis (OA) at 15 years after medial unicompartmental knee arthroplasty (UKA) and assess the relationship of lateral
Aims. Osteoarthritis (OA) is a common degenerative joint disease worldwide, which is characterized by articular cartilage lesions. With more understanding of the disease,
Aims. This study examined windswept deformity (WSD) of the knee, comparing prevalence and contributing factors in healthy and osteoarthritic (OA) cohorts. Methods. A case-control radiological study was undertaken comparing 500 healthy knees (250 adults) with a consecutive sample of 710
Aims. 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
Aims. Circular RNA (circRNA) is involved in the regulation of articular cartilage degeneration induced by inflammatory factors or oxidative stress. In a previous study, we found that the expression of circStrn3 was significantly reduced in chondrocytes of osteoarthritis (OA) patients and
Aims. Osteoarthritis (OA) is the most common chronic pathema of human joints. The pathogenesis is complex, involving physiological and mechanical factors. In previous studies, we found that ferroptosis is intimately related to
Aims. Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of
Aims. 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
Aims. Therapeutic agents that prevent chondrocyte loss, extracellular matrix (ECM) degradation, and osteoarthritis (OA) progression are required. The expression level of epidermal growth factor (EGF)-like repeats and discoidin I-like domains-containing protein 3 (EDIL3) in damaged human cartilage is significantly higher than in undamaged cartilage. However, the effect of EDIL3 on cartilage is still unknown. Methods. We used human cartilage plugs (ex vivo) and mice with spontaneous
Aims. This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating
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
Aims. cAMP response element binding protein (CREB1) is involved in the progression of osteoarthritis (OA). However, available findings about the role of CREB1 in
Aims. This study aimed to investigate the role and mechanism of meniscal cell lysate (MCL) in fibroblast-like synoviocytes (FLSs) and osteoarthritis (OA). Methods. Meniscus and synovial tissue were collected from 14 patients with and without
Aims. This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. Methods. 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
Aims. 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
Aims. Pellino1 (Peli1) has been reported to regulate various inflammatory diseases. This study aims to explore the role of Peli1 in the occurrence and development of osteoarthritis (OA), so as to find new targets for the treatment of
Aims. With up to 40% of patients having patellofemoral joint osteoarthritis (PFJ OA), the two arthroplasty options are to replace solely the patellofemoral joint via patellofemoral arthroplasty (PFA), or the entire knee via total knee arthroplasty (TKA). The aim of this study was to assess postoperative success of second-generation PFAs compared to TKAs for patients treated for PFJ