陆军军医大学学报2026，Vol.48Issue(7)：914-927,14.DOI:10.16016/j.2097-0927.202602071
基于焦亡相关基因的骨髓炎诊断模型构建与线粒体-炎症互作机制解析:整合多组学与机器学习的生物信息学研究
Construction of a pyroptosis-related gene-based diagnostic model for osteomyelitis and analysis of the mitochondria-inflammation interaction mechanism:a bioinformatics study integrating multi-omics and machine learning
摘要
Abstract
Objective Staphylococcus aureus(SA)-induced osteomyelitis(OM)is a common refractory orthopedic infection,presenting substantial challenges in early diagnosis and immune microenvironment characterization.Expression profiles of pyroptosis-related genes(PRGs)are closely associated with SA-OM;these genes may influence the immune microenvironment through mitochondrial-related pathways,thereby participating in disease progression,and specific gene combinations can be utilized to construct high-precision diagnostic models.This study aims to integrate multi-omics and machine learning to screen key pyroptosis-related diagnostic biomarkers in SA-OM,construct a high-precision diagnostic model,and elucidate its molecular mechanism influencing the immune microenvironment through"mitochondria-inflammation"crosstalk.Methods Based on 3 SA-OM datasets(GSE6269/GSE16129/GSE30119)retrieved from the GEO database,a total of 143 SA-OM patients and 79 healthy control samples were enrolled.Data preprocessing(batch effect correction using the sva package),differential expression analysis(DE-PRGs screened via the limma package,adj.P<0.05&|log2FC|>0.263),co-expression network construction(key module genes identified through WGCNA algorithm,softThreshold=5),multi-omics cross-validation(Pearson correlation analysis for MR-PRGs screening),machine learning modeling(feature genes selected via SVM-RFE/LASSO/random forest cross-validation,n=9),and diagnostic model construction(logistic regression nomogram model,efficacy evaluated through AUC,calibration curve slope,and DCA)were performed,combined with immune microenvironment analysis(CIBERSORT/ssGSEA quantitative analysis of 22 immune cell infiltration levels).Results Among 23 DE-PRGs,a diagnostic model comprising 8 key genes demonstrated excellent performance in both the training set(AUC=0.89,95%CI:0.83 to 0.95)and validation set(AUC=0.83,95%CI:0.76 to 0.90).RT-qPCR experiments further validated that the mRNA expression levels of the key pyroptosis pathway genes Caspase-1 and IL-18 in the SA-OM group were significantly upregulated compared with the control group(P<0.05),corroborating the bioinformatics findings.The METTL3-MRPL39 axis was significantly enriched in"metabolic pathways"and"mitochondrial gene expression"biological processes.Furthermore,Th1/Th17 cell infiltration levels in the disease group were 3.2-fold higher than those in the control group(P<0.001),and METTL3 expression exhibited positive correlation with effector T cell infiltration(r=0.65,P=0.008).Conclusion This study systematically elucidates the regulatory network of pyroptosis-related genes in SA-OM.The constructed diagnostic model provides a novel tool for early screening,while the identified mitochondrial-inflammation interplay mechanisms and specific immune microenvironment characteristics establish a theoretical foundation for the development of targeted therapeutic strategies.关键词
骨髓炎/细胞焦亡/分子亚型/免疫浸润/生物标志物Key words
osteomyelitis/pyroptosis/molecular subtype/immune infiltration/biomarker分类
医药卫生引用本文复制引用
张金烨,郑皓南,杨乾坤,余斌..基于焦亡相关基因的骨髓炎诊断模型构建与线粒体-炎症互作机制解析:整合多组学与机器学习的生物信息学研究[J].陆军军医大学学报,2026,48(7):914-927,14.基金项目
国家自然科学基金面上项目(82272517) Supported by the General Program of National Natural Science Foundation of China(82272517). （82272517）
