She Han, Tan Lei, Zhou Yuanqun, Zhu Yu, Ma Chunhua, Wu Yue, Du Yuanlin, Liu Liangming, Hu Yi, Mao Qingxiang, Li Tao
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
State Key Laboratory of Trauma, Burns and Combined Injury, Second Department of Research Institute of Surgery, Daping Hospital, Army Medical University, Chongqing, China.
Front Genet. 2022 Feb 21;13:821275. doi: 10.3389/fgene.2022.821275. eCollection 2022.
Sepsis is a heterogeneous disease state triggered by an uncontrolled inflammatory host response with high mortality and morbidity in severely ill patients. Unfortunately, the treatment effectiveness varies among sepsis patients and the underlying mechanisms have yet to be elucidated. The present aim is to explore featured metabolism-related genes that may become the biomarkers in patients with sepsis. In this study, differentially expressed genes (DEGs) between sepsis and non-sepsis in whole blood samples were identified using two previously published datasets (GSE95233 and GSE54514). A total of 66 common DEGs were determined, namely, 52 upregulated and 14 downregulated DEGs. The Gene Set Enrichment Analysis (GSEA) results indicated that these DEGs participated in several metabolic processes including carbohydrate derivative, lipid, organic acid synthesis oxidation reduction, and small-molecule biosynthesis in patients with sepsis. Subsequently, a total of 8 hub genes were screened in the module with the highest score from the Cytoscape plugin cytoHubba. Further study showed that these hub DEGs may be robust markers for sepsis with high area under receiver operating characteristic curve (AUROC). The diagnostic values of these hub genes were further validated in myocardial tissues of septic rats and normal controls by untargeted metabolomics analysis using liquid chromatography-mass spectrometry (LC-MS). Immune cell infiltration analysis revealed that different infiltration patterns were mainly characterized by B cells, T cells, NK cells, monocytes, macrophages, dendritics, eosinophils, and neutrophils between sepsis patients and normal controls. This study indicates that metabolic hub genes may be hopeful biomarkers for prognosis prediction and precise treatment in sepsis patients.
脓毒症是一种由不受控制的炎症宿主反应引发的异质性疾病状态,在重症患者中具有高死亡率和高发病率。不幸的是,脓毒症患者的治疗效果各不相同,其潜在机制尚未阐明。目前的目的是探索可能成为脓毒症患者生物标志物的特征性代谢相关基因。在本研究中,使用两个先前发表的数据集(GSE95233和GSE54514)鉴定全血样本中脓毒症和非脓毒症之间的差异表达基因(DEG)。共确定了66个常见的DEG,即52个上调的DEG和14个下调的DEG。基因集富集分析(GSEA)结果表明,这些DEG参与了脓毒症患者的多个代谢过程,包括碳水化合物衍生物、脂质、有机酸合成氧化还原和小分子生物合成。随后,从Cytoscape插件cytoHubba中得分最高的模块中筛选出总共8个枢纽基因。进一步研究表明,这些枢纽DEG可能是脓毒症的强大标志物,受试者工作特征曲线下面积(AUROC)较高。通过使用液相色谱-质谱(LC-MS)的非靶向代谢组学分析,在脓毒症大鼠和正常对照的心肌组织中进一步验证了这些枢纽基因的诊断价值。免疫细胞浸润分析显示,脓毒症患者和正常对照之间不同的浸润模式主要以B细胞、T细胞、NK细胞、单核细胞、巨噬细胞、树突状细胞、嗜酸性粒细胞和中性粒细胞为特征。本研究表明,代谢枢纽基因可能是脓毒症患者预后预测和精准治疗的有希望的生物标志物。