Abstract

Background and Objectives. Glucocorticoid-induced osteonecrosis of the femoral head (GIONFH) is a serve complication of long-term administration of glucocorticoids. Previous experimental studies have shown that ferroptosis might be involved in the pathological process of GIONFH. The purpose of this study is to identify the ferroptosis-related genes and pathways of GIONFH by bioinformatics to further illustrate the mechanism of ferroptosis in SONFH through bioinformatics analysis. Materials and Methods. The GSE123568 mRNA expression profile dataset, including 30 GIONFH samples and 10 non-GIONFH samples, was downloaded from the Gene Expression Omnibus (GEO) database. Ferroptosis-related genes were obtained from the FerrDb database. First, differentially expressed genes (DEGs) were identified between the serum samples from GIONFH cases and those from controls. Ferroptosis-related DEGs were obtained from the intersection of ferroptosis-related genes and DEGs. Only ferroptosis DEGs were used for all analyses. Then, we conducted a Kyoto encyclopedia of genome (KEGG) and gene ontology (GO) pathway enrichment analysis. We constructed a protein-protein interaction (PPI) network to screen out hub genes. Additionally, the expression levels of the hub genes were validated in an independent dataset GSE10311. Results. A total of 27 ferroptosis-related DEGs were obtained between the peripheral blood samples of GIONFH cases and non-GIONFH controls. Then, GO, and KEGG pathway enrichment analysis revealed that ferroptosis-related DEGs were mainly enriched in the regulation of the apoptotic process, oxidation-reduction process, and cell redox homeostasis, as well as HIF-1, TNF, FoxO signaling pathways, and osteoclast differentiation. Eight hub genes, including TLR4, PTGS2, SNCA, MAPK1, CYBB, SLC2A1, TXNIP, and MAP3K5, were identified by PPI network analysis. The expression levels of TLR4, TXNIP and MAP3K5 were further validated in the dataset GSE10311. Conclusion. A total of 27 ferroptosis-related DEGs involved in GIONFH were identified via bioinformatics analysis. TLR4, TXNIP, and MAP3K5 might serve as potential biomarkers and drug targets for GIONFH.

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