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通过综合生物信息学分析探索脓毒症的生物标志物和潜在治疗药物。

Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis.

机构信息

Foshan Fourth People's Hospital, Guangdong Province, Foshan, 528041, China.

Center for Infection and Immunity and Guangdong Provincial Engineering Research Center of Molecular Imaging, the Fifth Affiliated Hospital of Sun Yat-Sen University, Guangdong Province, Zhuhai, 519000, China.

出版信息

BMC Infect Dis. 2024 Jan 2;24(1):32. doi: 10.1186/s12879-023-08883-9.

Abstract

BACKGROUND

Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear.

RESULTS

In this study, bioinformatics analysis revealed the novel key biomarkers associated with sepsis and potential regulators. Three public datasets (GSE28750, GSE57065 and GSE95233) were employed to recognize the differentially expressed genes (DEGs). Taking the intersection of DEGs from these three datasets, GO and KEGG pathway enrichment analysis revealed 537 shared DEGs and their biological functions and pathways. These genes were mainly enriched in T cell activation, differentiation, lymphocyte differentiation, mononuclear cell differentiation, and regulation of T cell activation based on GO analysis. Further, pathway enrichment analysis revealed that these DEGs were significantly enriched in Th1, Th2 and Th17 cell differentiation. Additionally, five hub immune-related genes (CD3E, HLA-DRA, IL2RB, ITK and LAT) were identified from the protein-protein interaction network, and sepsis patients with higher expression of hub genes had a better prognosis. Besides, 14 drugs targeting these five hub related genes were revealed on the basis of the DrugBank database, which proved advantageous for treating immune-related diseases.

CONCLUSIONS

These results strengthen the new understanding of sepsis development and provide a fresh perspective into discriminating the candidate biomarkers for predicting sepsis as well as identifying new drugs for treating sepsis.

摘要

背景

败血症是一种危及生命的疾病,由感染引起的过度炎症反应引起,死亡率高。然而,败血症的调节机制尚不清楚。

结果

本研究通过生物信息学分析,揭示了与败血症相关的新型关键生物标志物和潜在调节剂。使用三个公共数据集(GSE28750、GSE57065 和 GSE95233)来识别差异表达基因(DEGs)。取这三个数据集的 DEGs 的交集,GO 和 KEGG 通路富集分析揭示了 537 个共享的 DEGs 及其生物学功能和通路。这些基因主要富集在 T 细胞激活、分化、淋巴细胞分化、单核细胞分化和 T 细胞激活调节上,基于 GO 分析。进一步的通路富集分析表明,这些 DEGs 在 Th1、Th2 和 Th17 细胞分化中显著富集。此外,从蛋白质-蛋白质相互作用网络中鉴定出五个免疫相关基因(CD3E、HLA-DRA、IL2RB、ITK 和 LAT)的枢纽基因,并且这些枢纽基因表达水平较高的败血症患者预后较好。此外,基于 DrugBank 数据库发现了 14 种针对这五个枢纽相关基因的药物,这为治疗免疫相关疾病提供了有利条件。

结论

这些结果加强了对败血症发展的新认识,并为预测败血症的候选生物标志物提供了新的视角,并为治疗败血症确定了新的药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0b9/10763157/6342f6078d1f/12879_2023_8883_Fig1_HTML.jpg

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