PDF(Pubmed)
Abstract：
During SARS-CoV-2 infection, the virus transforms the infected host cell into factories that produce new viral particles. As infection progresses, the infected cells undergo numerous changes in various pathways. One of these changes is the occurrence of a cytokine storm, which leads to severe symptoms. In this study, we examined the transcriptomic changes caused by COVID-19 by analyzing RNA-seq data obtained from COVID-19-positive patients as well as COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. We analyzed the first datasets, consisting of 96 samples to validate our methods. The objective of this publication is to report the pilot results. To explore potential biomarkers related to disease severity, we conducted a differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Given the large number of potential biomarkers we identified, we further performed pathway enrichment analysis with terms from Kyoto Encyclopedia of Genes and Genomics (KEGG) to obtain a more profound understanding of altered pathways. Our results indicate that pathways related to immune processes, response to infection, and multiple signaling pathways were affected. These findings align with several previous studies that also reported the influence of SARS-CoV-2 infection on these pathways.
摘要：
在SARS-CoV-2感染期间,该病毒将受感染的宿主细胞转化为产生新病毒颗粒的工厂。随着感染的进展,受感染的细胞经历各种途径的许多变化。这些变化之一是细胞因子风暴的发生，导致严重的症状。在这项研究中,我们通过分析从COVID-19阳性患者和COVID-19阴性供体获得的RNA-seq数据,检查了由COVID-19引起的转录组变化.收集RNA-seq数据用于鉴定与不同病程相关的潜在生物标志物。我们分析了第一个数据集，由96个样本组成，以验证我们的方法。本出版物的目的是报告试点结果。探索与疾病严重程度相关的潜在生物标志物，我们进行了人类转录组的差异表达分析，重点关注COVID-19阳性和症状严重程度。鉴于我们发现了大量潜在的生物标志物，我们进一步使用京都基因和基因组学百科全书(KEGG)中的术语进行了通路富集分析,以获得对改变通路的更深刻理解.我们的结果表明，与免疫过程相关的途径，对感染的反应，多个信号通路受到影响。这些发现与先前的一些研究一致，这些研究也报道了SARS-CoV-2感染对这些途径的影响。
