Osteoarthritis (OA) is a degenerative disease resulting from progressive joint destruction caused by many factors. Its pathogenesis is complex and has not been elucidated to date. Advanced glycation end products (AGEs) are a series of irreversible and stable macromolecular complexes formed by reducing sugar with protein, lipid, and nucleic acid through a non-enzymatic glycosylation reaction (Maillard reaction). They are an important indicator of the degree of ageing. Currently, it is considered that AGEs accumulation in vivo is a molecular basis of age-induced OA, and AGEs production and accumulation in vivo is one of the important reasons for the induction and acceleration of the pathological changes of OA. In recent years, it has been found that AGEs are involved in a variety of pathological processes of OA, including extracellular matrix degradation, chondrocyte apoptosis, and autophagy. Clearly, AGEs play an important role in regulating the expression of OA-related genes and maintaining the chondrocyte phenotype and the stability of the intra-articular environment. This article reviews the latest research results of AGEs in a variety of pathological processes of OA, to provide a new direction for the study of OA pathogenesis and a new target for prevention and treatment. Cite this article:
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
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