Exploration of effective biomarkers and infiltrating Immune cells in Osteoarthritis based on bioinformatics analysis

Abstract

AbstractOsteoarthritis (OA) is a multi-factorial chronic joint disease mainly identified by synovial inflammation, cartilage damage, and degeneration. Our study applied bioinformatics analysis to uncover the immunity in OA and tried to explore the underlying immune-related molecular mechanism. First, OA-related gene-expression profiling data were retrieved from GEO database. Then, we analysed a series of datadata with using the xCell algorithm, GEO2R, enrichment analysis of SangerBox website, CytoHubba, ROC logistic regression and correlation analysis. Finally, Nine infiltrating immune cells with differential abundance between OA and normal samples were obtained. There were 42 IODEGs in OA, and their functions were associated with immune cells and corresponding biological processes. Moreover, 5 hub genes, including GREM1, NRP1, VEGFA, FYN and IL6R, were identified. Correlation analysis demonstrated that NRP1 was negatively associated with NKT cells, NRP1 and GREM1 were positively associated with aDC, VEGFA was positively associated with CD8+ naïve T cells, while VEGFA, FYN and IL6R were negatively associated with Macrophages M1. The 5 hub genes could be employed as effective diagnostic biomarkers for OA. In addition, they may participate in OA pathogenesis via interactions with infiltrating immune cells.

Keywords

• Osteoarthritis
• immune infiltration
• differentially expressed genes
• bioinformatics analysis
• immune cells