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
Methods
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
Methods
Osteoarthritis (OA) is the most prevalent joint disease. However, the specific and definitive genetic mechanisms of OA are still unclear. Tissue-related transcriptome-wide association studies (TWAS) of hip OA and knee OA were performed utilizing the genome-wide association study (GWAS) data of hip OA and knee OA (including 2,396 hospital-diagnosed hip OA patients versus 9,593 controls, and 4,462 hospital-diagnosed knee OA patients versus 17,885 controls) and gene expression reference to skeletal muscle and blood. The OA-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the messenger RNA (mRNA) expression profiles of hip OA and knee OA. Functional enrichment and annotation analysis of identified genes was performed by the DAVID and FUMAGWAS tools.Aims
Methods
