Identification of a Novel Hypoxia-Related Gene Prognostic Signature in Osteoarthritis

Abstract

Abstract Background. Osteoarthritis (OA) is a well-known joint disorder characterized by inflammation. Current evidence suggests that immune cell infiltration plays an important role in the development of OA. This study explored the heterogeneity of immune cell infiltration in OA and its association with genes related to hypoxic conditions. Methods. We obtained OA-related expression dataset profiles (GSE98918 and GSE55235) from the Gene Expression Omnibus (GEO) repository. By analyzing the differences between these datasets, we identified differentially expressed genes (DEGs) between both OA groups and screened DEGs associated with hypoxia. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were conducted to explore significantly enriched pathways associated with genes related to hypoxia with differential expression in osteoarthritis. We generated protein-protein interaction (PPI) networks and networks of mRNA interactions with miRNA, RNA-binding protein (RBP), and transcription factor (TF). The CIBERSORT algorithm was finally used to explore immune infiltration patterns and examine the effect of inflammation on OA pathogenesis. Results. In the GSE98918 dataset, four immune cell types (regulatory T cells (Tregs), M1/M2 Macrophages, and resting Mast cells) demonstrated significant differences (P < 0.05) between OA and Normal groups and exhibited positive correlations. The infiltration levels of these four immune cell were significantly correlated with six hypoxia-related differentially expressed genes. In the GSE55235 dataset, ten immune cell types exhibited significant alterations (P < 0.05) between the OA and Normal groups, with most having negative correlations. These immune cell infiltration abundances were significantly correlated with six hypoxia-related DEGs. Conclusion. This study revealed the heterogeneity in immune cell infiltration abundance between OA and normal groups and their relationship with hypoxia-related genes. These discoveries contribute to our understanding of the development of OA and potential therapeutic targets.