Osteoarthritis (OA) is a common degenerative joint disease worldwide, which is characterized by articular cartilage lesions. With more understanding of the disease, OA is considered to be a disorder of the whole joint. However, molecular communication within and between tissues during the disease process is still unclear. In this study, we used transcriptome data to reveal crosstalk between different tissues in OA. We used four groups of transcription profiles acquired from the Gene Expression Omnibus database, including articular cartilage, meniscus, synovium, and subchondral bone, to screen differentially expressed genes during OA. Potential crosstalk between tissues was depicted by ligand-receptor pairs.Aims
Methods
Activation of the leptin pathway is closely correlated with human knee cartilage degeneration. However, the role of the long form of the leptin receptor (Ob-Rb) in cartilage degeneration needs further study. The aim of this study was to determine the effect of increasing the expression of Ob-Rb on chondrocytes using a lentiviral vector containing Ob-Rb. The medial and lateral cartilage samples of the tibial plateau from 12 osteoarthritis (OA) patients were collected. Ob-Rb messenger RNA (mRNA) was detected in these samples. The Ob-Rb-overexpressing chondrocytes and controls were treated with different doses of leptin for two days. The activation of the p53/p21 pathway and the number of senescence-associated β-galactosidase (SA-β-gal)-positive cells were evaluated. The mammalian target of rapamycin (mTOR) signalling pathway and autophagy were detected after the chondrocytes were treated with a high dose of leptin.Objectives
Methods
The aim of this study was to identify key pathological genes in osteoarthritis (OA). We searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis.Objectives
Methods
