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通过生物信息学分析筛选出院后新冠病毒检测再次阳性患者的关键基因并分析其机制。

Screening the hub genes and analyzing the mechanisms in discharged COVID-19 patients retesting positive through bioinformatics analysis.

机构信息

Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Hospital of Guangzhou Medical University, Guangzhou, China.

Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China.

出版信息

J Clin Lab Anal. 2022 Jul;36(7):e24495. doi: 10.1002/jcla.24495. Epub 2022 Jun 3.

Abstract

BACKGROUND

After encountering COVID-19 patients who test positive again after discharge, our study analyzed the pathogenesis to further assess the risk and possibility of virus reactivation.

METHODS

A separate microarray was acquired from the Gene Expression Omnibus (GEO), and its samples were divided into two groups: a "convalescent-RTP" group consisting of convalescent and "retesting positive" (RTP) patients (group CR) and a "healthy-RTP" group consisting of healthy control and RTP patients (group HR). The enrichment analysis was performed with R software, obtaining the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, the protein-protein interaction (PPI) networks of each group were established, and the hub genes were discovered using the cytoHubba plugin.

RESULTS

In this study, 6622 differentially expressed genes were identified in the group CR, among which RAB11B-AS1, DISP1, MICAL3, PSMG1, and DOCK4 were up-regulated genes, and ANAPC1, IGLV1-40, SORT1, PLPPR2, and ATP1A1-AS1 were down-regulated. 7335 genes were screened in the group HR, including the top 5 up-regulated genes ALKBH6, AMBRA1, MIR1249, TRAV18, and LRRC69, and the top 5 down-regulated genes FAM241B, AC018529.3, AL031963.3, AC006946.1, and FAM149B1. The GO and KEGG analysis of the two groups revealed a significant enrichment in immune response and apoptosis. In the PPI network constructed, group CR and group HR identified 10 genes, respectively, and TP53BP1, SNRPD1, and SNRPD2 were selected as hub genes.

CONCLUSIONS

Using the messenger ribonucleic acid (mRNA) expression data from GSE166253, we found TP53BP1, SNRPD1, and SNRPD2 as hub genes in RTP patients, which is vital to the management and prognostic prediction of RTP patients.

摘要

背景

在遇到出院后再次检测呈阳性的 COVID-19 患者后,我们的研究分析了发病机制,以进一步评估病毒重新激活的风险和可能性。

方法

从基因表达综合数据库(GEO)中获取一个单独的微阵列,将其样本分为两组:一组是由恢复期和“再次检测阳性”(RTP)患者组成的“恢复期-RTP”组(组 CR),另一组是由健康对照和 RTP 患者组成的“健康-RTP”组(组 HR)。使用 R 软件进行富集分析,获得基因本体论(GO)和京都基因与基因组百科全书(KEGG)。随后,建立了每组的蛋白质-蛋白质相互作用(PPI)网络,并使用 cytoHubba 插件发现了枢纽基因。

结果

在这项研究中,在组 CR 中鉴定出 6622 个差异表达基因,其中 RAB11B-AS1、DISP1、MICAL3、PSMG1 和 DOCK4 为上调基因,而 ANAPC1、IGLV1-40、SORT1、PLPPR2 和 ATP1A1-AS1 为下调基因。在组 HR 中筛选出 7335 个基因,包括前 5 个上调基因 ALKBH6、AMBRA1、MIR1249、TRAV18 和 LRRC69,以及前 5 个下调基因 FAM241B、AC018529.3、AL031963.3、AC006946.1 和 FAM149B1。两组的 GO 和 KEGG 分析显示,免疫反应和细胞凋亡有明显的富集。在构建的 PPI 网络中,组 CR 和组 HR 分别确定了 10 个基因,选择 TP53BP1、SNRPD1 和 SNRPD2 作为枢纽基因。

结论

使用 GSE166253 中的信使核糖核酸(mRNA)表达数据,我们发现 TP53BP1、SNRPD1 和 SNRPD2 是 RTP 患者的枢纽基因,这对 RTP 患者的管理和预后预测至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/212e/9279949/d15a6155b764/JCLA-36-e24495-g004.jpg

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