Comprehensive investigation of RNA-sequencing dataset reveals the hub genes and molecular mechanisms of coronavirus disease 2019 acute respiratory distress syndrome

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2021-08-05 DOI:10.1049/syb2.12034
Wangsheng Deng, Jiaxing Zeng, Shunyu Lu, Chaoqian Li
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引用次数: 3

Abstract

The goal of this study is to reveal the hub genes and molecular mechanisms of the coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) based on the genome-wide RNA sequencing dataset. The RNA sequencing dataset of COVID-19 ARDS was obtained from GSE163426. A total of 270 differentially expressed genes (DEGs) were identified between COVID-19 ARDS and control group patients. Functional enrichment analysis of DEGs suggests that these DEGs may be involved in the following biological processes: response to cytokine, G-protein coupled receptor activity, ionotropic glutamate receptor signalling pathway and G-protein coupled receptor signalling pathway. By using the weighted correlation network analysis approach to analyse these DEGs, 10 hub DEGs that may play an important role in COVID-19 ARDS were identified. A total of 67 potential COVID-19 ARDS targetted drugs were identified by a complement map analysis. Immune cell infiltration analysis revealed that the levels of T cells CD4 naive, T cells follicular helper, macrophages M1 and eosinophils in COVID-19 ARDS patients were significantly different from those in control group patients. In conclusion, this study identified 10 COVID-19 ARDS-related hub DEGs and numerous potential molecular mechanisms through a comprehensive analysis of the RNA sequencing dataset and also revealed the difference in immune cell infiltration of COVID-19 ARDS.

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综合rna测序数据揭示2019冠状病毒病急性呼吸窘迫综合征枢纽基因及分子机制
本研究旨在基于全基因组RNA测序数据揭示2019冠状病毒病(COVID-19)急性呼吸窘迫综合征(ARDS)的枢纽基因和分子机制。COVID-19 ARDS的RNA测序数据集来自GSE163426。在COVID-19 ARDS患者与对照组患者之间共鉴定出270个差异表达基因(DEGs)。DEGs的功能富集分析表明,这些DEGs可能参与细胞因子应答、g蛋白偶联受体活性、嗜离子性谷氨酸受体信号通路和g蛋白偶联受体信号通路等生物学过程。采用加权相关网络分析方法对这些deg进行分析,鉴定出10个可能在COVID-19 ARDS中起重要作用的枢纽deg。通过补体图谱分析,共鉴定出67种潜在的COVID-19 ARDS靶向药物。免疫细胞浸润分析显示,COVID-19 ARDS患者的T细胞CD4 naive、T细胞滤泡辅助细胞、巨噬细胞M1和嗜酸性粒细胞水平与对照组相比有显著差异。综上所述,本研究通过对RNA测序数据的综合分析,确定了10个与COVID-19 - ARDS相关的枢纽DEGs和许多潜在的分子机制,并揭示了COVID-19 - ARDS免疫细胞浸润的差异。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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