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  • Title: A novel signature of autophagy-related immunophenotyping biomarkers in osteoarthritis.
    Author: Yang L, Liu J, Yu Y, Liu S.
    Journal: Life Sci; 2023 May 15; 321():121599. PubMed ID: 36966915.
    Abstract:
    AIMS: We aimed to provide an autophagy-related signature to seek immunophenotyping biomarkers in osteoarthritis (OA). MATERIALS AND METHODS: Microarray expression profiling of OA subchondral bone samples and screening of an autophagy database for autophagy-related differentially expressed genes (au-DEGs) between OA and normal samples were performed. A weighted gene co-expression network analysis (WGCNA) was constructed using au-DEGs to identify key modules significantly associated with clinical information of OA samples. OA-related autophagy hub genes were identified based on the connectivity with the phenotypes of genes in key modules and the protein-protein interaction (PPI) network in which the genes in the modules are involved, followed by feasibility verification of autophagy hub genes by bioinformatics analysis and biological experiments. KEY FINDINGS: We screened 754 au-DEGs between OA and control samples, and co-expression networks were constructed using au-DEGs. Three OA-related autophagy hub genes (HSPA5, HSP90AA1, and ITPKB) were identified. Based on the hub gene expression profiles, OA samples were divided into two clusters with significantly different expression profiles and distinct immunological features, and the three hub genes were significantly differentially expressed between the clusters. Differences in hub genes between OA and control samples regarding sex, age, and grades of OA were examined using external datasets and experimental validation. SIGNIFICANCE: Three autophagy-related markers of OA were identified using bioinformatics methods, and these markers may be useful for the autophagy-related immunophenotyping of OA. The present data may facilitate the diagnosis of OA, as well as the design of immunotherapies and individualized medical treatments.
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