Tian Ye, Wang Liang, Chen Wenhao, Zhong Wu, Hu Yingchun
Department of Emergency Medicine, Affiliated Hospital of Southwest Medical University.
Shock. 2023 May 1;59(5):708-715. doi: 10.1097/SHK.0000000000002115. Epub 2023 Mar 7.
Objective: Based on the functions of immunoregulation and signal transduction, septic peripheral blood sequencing and bioinformatics technology were used to screen potential core targets. Methods: Peripheral blood of 23 patients with sepsis and 10 normal volunteers underwent RNA-seq processing within 24 hours after admission to the hospital. Data quality control and differential gene screening were performed based on R language ( P < 0.01; log2FC ≥ 2). Gene function enrichment analysis was conducted on differentially expressed genes (DEGs). Then, target genes were submitted to STRING to constitute the PPI network, and GSE65682 were used to explore the prognostic relevance of potential core genes. Meta-analysis was used to verify the expression trends of core genes in the sepsis group. Then, cell line localization analysis of core genes in the 5 peripheral blood mononuclear cell samples (normal control = 2; systemic inflammatory response syndrome = 1; SEPSIS = 2) was performed. Results: A total of 1,128 DEGs were obtained between sepsis and normal group, of which 721 were upregulated and 407 downregulated. These DEGs were mainly enriched in leukocyte-mediated cytotoxicity, cell killing regulation, adaptive immune response regulation, lymphocyte-mediated immune regulation, and negative regulation of adaptive immune response. PPI network analysis results showed that CD160, KLRG1, S1PR5, and RGS16 were located in the core area, which are related to adaptive immune regulation, signal transduction, and intracellular components. The above four genes in the core area were found to be related to the prognosis of patients with sepsis, of which RGS16 was negatively correlated with the survival rate, and CD160, KLRG1, and S1PR5 were positively correlated. However, several public data sets showed that CD160, KLRG1, and S1PR5 were all downregulated in the peripheral blood of patients with sepsis, while RGS16 was upregulated in the sepsis group. Single-cell sequencing analysis showed that they were mainly expressed in NK-T cells. Conclusions: CD160, KLRG1, S1PR5, and RGS16 were mainly located in human peripheral blood NK-T cells. Sepsis participants expressed lower levels of S1PR5, CD160, and KLRG1, while sepsis participants expressed higher levels of RGS16. This suggests that they may be potential research targets for sepsis.
基于免疫调节和信号转导功能,运用脓毒症外周血测序及生物信息学技术筛选潜在核心靶点。方法:选取23例脓毒症患者及10名正常志愿者的外周血,于入院后24小时内进行RNA测序处理。基于R语言进行数据质量控制及差异基因筛选(P<0.01;log2FC≥2)。对差异表达基因(DEGs)进行基因功能富集分析。随后,将靶基因提交至STRING构建蛋白质-蛋白质相互作用(PPI)网络,并利用GSE65682探究潜在核心基因的预后相关性。采用荟萃分析验证脓毒症组中核心基因的表达趋势。接着,对5份外周血单个核细胞样本(正常对照=2;全身炎症反应综合征=1;脓毒症=2)进行核心基因的细胞系定位分析。结果:脓毒症组与正常组共获得1128个差异表达基因,其中721个上调,407个下调。这些差异表达基因主要富集于白细胞介导的细胞毒性、细胞杀伤调节、适应性免疫反应调节、淋巴细胞介导的免疫调节以及适应性免疫反应的负调节。PPI网络分析结果显示,CD160、KLRG1、S1PR5和RGS16位于核心区域,与适应性免疫调节、信号转导及细胞内成分相关。发现核心区域的上述4个基因与脓毒症患者的预后相关,其中RGS16与生存率呈负相关,而CD160、KLRG1和S1PR5与生存率呈正相关。然而,多个公共数据集显示,脓毒症患者外周血中CD160、KLRG1和S1PR5均下调,而脓毒症组中RGS16上调。单细胞测序分析表明,它们主要在自然杀伤T细胞中表达。结论:CD160、KLRG1、S1PR5和RGS16主要定位于人外周血自然杀伤T细胞。脓毒症患者中S1PR5、CD160和KLRG1表达水平较低,而脓毒症患者中RGS16表达水平较高。这表明它们可能是脓毒症潜在的研究靶点。