Identification of Ferroptosis-Related Biomarkers for Diagnosis and Molecular Classification of Staphylococcus aureus -Induced Osteomyelitis

• Published in: Journal of inflammation research 2023-01, Vol.16, p.1805-1823
• Main Authors: Shi, Xiangwen, Tang, Linmeng, Ni, Haonan, Li, Mingjun, Wu, Yipeng, Xu, Yongqing
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; biomarker; Dendritic cells; Diagnosis; ferroptosis; Gene expression; Genes; immune infiltration; Immune response; Infiltration (Hydrology); Inflammation; molecular subtype; Original Research; Osteomyelitis; Staphylococcus aureus; T cells
• ISSN: 1178-7031; 1178-7031
• DOI: 10.2147/JIR.S406562

(SA)-induced osteomyelitis (OM) is one of the most common refractory diseases in orthopedics. Early diagnosis is beneficial to improve the prognosis of patients. Ferroptosis plays a key role in inflammation and immune response, while the mechanism of ferroptosis-related genes (FRGs) in SA-induced OM is still unclear. The purpose of this study was to determine the role of ferroptosis-related genes in the diagnosis, molecular classification and immune infiltration of SA-induced OM by bioinformatics. Datasets related to SA-induced OM and ferroptosis were collected from the Gene Expression Omnibus (GEO) and ferroptosis databases, respectively. The least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms were combined to screen out differentially expressed-FRGs (DE-FRGs) with diagnostic characteristics, and gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore specific biological functions and pathways. Based on these key DE-FRGs, a diagnostic model was established, and molecular subtypes were divided to explore the changes in the immune microenvironment between molecular subtypes. A total of 41 DE-FRGs were identified. After screening and intersecting with LASSO and SVM-RFE algorithms, 8 key DE-FRGs with diagnostic characteristics were obtained, which may regulate the pathogenesis of OM through the immune response and amino acid metabolism. The ROC curve indicated that the 8 DE-FRGs had excellent diagnostic ability for SA-induced OM (AUC=0.993). Two different molecular subtypes (subtype 1 and subtype 2) were identified by unsupervised cluster analysis. The CIBERSORT analysis revealed that the subtype 1 OM had higher immune cell infiltration rates, mainly in T cells CD4 memory resting, macrophages M0, macrophages M2, dendritic cells resting, and dendritic cells activated. We developed a diagnostic model related to ferroptosis and molecular subtypes significantly related to immune infiltration, which may provide a novel insight for exploring the pathogenesis and immunotherapy of SA-induced OM.