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术后脓毒症中铁死亡诊断与治疗潜力的遗传分析

Genetic analysis of diagnostic and therapeutic potential for ferroptosis in postoperative sepsis.

作者信息

Pei Shuaijie, Liu Jianfeng, Wang Zhiwei, Fan Yan, Meng Shuqi, Huang Xiaofan, Cui Yan, Xie Keliang

机构信息

Department of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China; Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China.

Department of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.

出版信息

Int Immunopharmacol. 2025 Feb 6;147:114042. doi: 10.1016/j.intimp.2025.114042. Epub 2025 Jan 9.

Abstract

BACKGROUND

Ferroptosis is a new form of iron-dependent cell death that is closely associated with sepsis. However, few studies have investigated the diagnostic and therapeutic potential for ferroptosis-related genes (FRGs) among postoperative sepsis.

METHODS

The GSE131761 dataset was used to identify differentially expressed FRGs (DE-FRGs). KEGG and GO analyses were subsequently performed. LASSO and SVM-RFE methods were applied for identifying genetic biomarkers for sepsis. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were applied for exploring the biological properties of the DEGs. CIBERSORT was applied to analyse immune cell infiltration. DGldb was employed for predicting potential target drugs for the DEGs. Competing endogenous RNA (ceRNA) networks were constructed to analyse the regulatory patterns of the DEGs. The expression of hub genes was validated based on GSE26440 dataset. The bioinformatics analysis was carried out with R software (version 4.1.2). Blood from sepsis patients and healthy controls was collected and the expression of hub genes was experimentally verified by real-time quantitative polymerase chain reaction (RT-qPCR).

RESULTS

38 sepsis-associated DE-FRGs were assessed via Gene Expression Omnibus (GEO) and Ferroptosis database (FerrDb), and the gene function analysis showed that they were closely related to inflammatory response and autophagy regulation. Subsequently, SVM-RFE and LASSO methods determined 7 marker genes. GSEA suggested that these marker genes may be involved in regulating several biological pathways. Furthermore, 52 gene-targeted drugs were identified in this study, the vast majority of which were associated with MAPK14. CIBERSORT analysis suggested that SLC38A1, MGST1, and MAPK14 may be involved in immune microenvironment alterations. We revealed the potential complex regulatory relationship by constructing a ceRNA network based on marker genes. Finally, 6 genes were validated in the validation set, with 5 of them further confirmed through RT-qPCR.

CONCLUSION

Seven genes associated with ferroptosis are screened from postoperative sepsis samples. The expression of these genes has high diagnostic validity for sepsis and may serve as potential diagnostic biomarkers. This study gives an entrance point to uncover the underlying mechanisms of sepsis.

摘要

背景

铁死亡是一种新的铁依赖性细胞死亡形式,与脓毒症密切相关。然而,很少有研究探讨术后脓毒症中铁死亡相关基因(FRGs)的诊断和治疗潜力。

方法

使用GSE131761数据集鉴定差异表达的FRGs(DE-FRGs)。随后进行KEGG和GO分析。应用LASSO和SVM-RFE方法鉴定脓毒症的遗传生物标志物。基因集富集分析(GSEA)和基因集变异分析(GSVA)用于探索DEGs的生物学特性。应用CIBERSORT分析免疫细胞浸润。利用DGldb预测DEGs的潜在靶标药物。构建竞争性内源性RNA(ceRNA)网络以分析DEGs的调控模式。基于GSE26440数据集验证枢纽基因的表达。使用R软件(版本4.1.2)进行生物信息学分析。收集脓毒症患者和健康对照者的血液,并通过实时定量聚合酶链反应(RT-qPCR)实验验证枢纽基因的表达。

结果

通过基因表达综合数据库(GEO)和铁死亡数据库(FerrDb)评估了38个脓毒症相关的DE-FRGs,基因功能分析表明它们与炎症反应和自噬调节密切相关。随后,SVM-RFE和LASSO方法确定了7个标记基因。GSEA表明这些标记基因可能参与调节多种生物学途径。此外,本研究鉴定了52种基因靶向药物,其中绝大多数与MAPK14相关。CIBERSORT分析表明,SLC38A1、MGST1和MAPK14可能参与免疫微环境改变。通过基于标记基因构建ceRNA网络,揭示了潜在的复杂调控关系。最后,在验证集中验证了6个基因,其中5个通过RT-qPCR进一步得到证实。

结论

从术后脓毒症样本中筛选出7个与铁死亡相关的基因。这些基因的表达对脓毒症具有较高的诊断效度,可能作为潜在的诊断生物标志物。本研究为揭示脓毒症的潜在机制提供了切入点。

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