AUTHOR=Shi Junhong , Chen Lan , Yuan Xinru , Yang Jinjin , Xu Yanlei , Shen Li , Huang Yu , Wang Bingjie , Yu Fangyou TITLE=A potential XGBoost Diagnostic Score for Staphylococcus aureus bloodstream infection JOURNAL=Frontiers in Immunology VOLUME=Volume 16 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1574003 DOI=10.3389/fimmu.2025.1574003 ISSN=1664-3224 ABSTRACT=Staphylococcus aureus (S. aureus) bloodstream infection is often life-threatening, and increasing in incidence. We identified 63 differentially expressed genes (DEGs) in the GSE33341 S. aureus infection samples. Subsequently, intersecting the 63 DEGs with 950 genes from the blue module through weighted gene co-expression network analysis (WGCNA) yielded 38 genes. We leveraged Boruta and least absolute shrinkage and selection operator (LASSO) algorithms and identified5 diagnostic genes (DRAM1, UPP1, IL18RAP, CLEC4A, and PGLYRP1). Comparative analysis revealed that Extreme Gradient Boosting (XGBoost) surpassed SVM-RFE and Random Forest models, demonstrating superior diagnostic performance for S. aureus bloodstream infection (mean AUC for XGBoost =0.954; mean AUC for SVM-RFE =0.93275; mean AUC for Random Forest =0.94625). The XGBoost Diagnostic Score correlated with multiple immune cells to varying degrees, manifesting significant negative associations with CD8 T cells and CD4 naive T cells in both human and mouse samples. The diagnostic power of the Diagnostic Score was further validated by RT-qPCR results obtained from both mouse and patient samples, as well as RNA-Seq analysis conducted on mouse samples. XGBoost Diagnostic Score, consisting of DRAM1, UPP1, IL18RAP, CLEC4A, and PGLYRP1, may serve as a Diagnostic tool for S. aureus bloodstream infection.