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基于加权基因共表达网络分析鉴定与 COVID-19 相关的潜在核心基因。

Potential core genes associated with COVID-19 identified via weighted gene co-expression network analysis.

机构信息

Department of Pancreatic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.

出版信息

Swiss Med Wkly. 2022 Nov 30;152:40033. doi: 10.57187/smw.2022.40033. eCollection 2022 Nov 21.

Abstract

AIMS

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel virus belonging to the Coronaviridae family that causes coronavirus disease (COVID-19). This disease rapidly reached pandemic status, presenting a serious threat to global health. However, the detailed molecular mechanism contributing to COVID-19 has not yet been elucidated.

METHODS

The expression profiles, including the mRNA levels, of samples from patients infected with SARS-CoV-2 along with clinical data were obtained from the GSE152075 dataset in the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules, which were then implemented to evaluate the relationships between fundamental modules and clinical traits. The differentially expressed genes (DEGs), gene ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were evaluated using R software packages.

RESULTS

A total of 377 SARS-CoV-2-infected samples and 54 normal samples with available clinical and genetic data were obtained from the GEO database. There were 1444 DEGs identified between the sample types, which were used to screen out 11 co-expression modules in the WGCNA. Six co-expression modules were significantly associated with three clinical traits (SARS-CoV-2 positivity, age, and sex). Among the DEGs in two modules significantly correlated with SARS-CoV-2 positivity, enrichment was observed in the biological process of viral infection strategies (viral translation) in the GO analysis. The KEGG signalling pathway analysis demonstrated that the DEGs in the two modules were commonly enriched in oxidative phosphorylation, ribosome, and thermogenesis pathways. Moreover, a five-core gene set (RPL35A, RPL7A, RPS15, RPS20, and RPL17) with top connectivity with other genes was identified in the SARS-CoV-2 infection modules, suggesting that these genes may be indispensable in viral transcription after infection.

CONCLUSION

The identified core genes and signalling pathways associated with SARS-CoV-2 infection can significantly supplement the current understanding of COVID-19. The five core genes encoding ribosomal proteins may be indispensable in viral protein biosynthesis after SARS-CoV-2 infection and serve as therapeutic targets for COVID-19 treatment. These findings can be used as a basis for creating a hypothetical model for future experimental studies regarding associations of SARS-CoV-2 infection with ribosomal protein function.

摘要

目的

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)是一种新型冠状病毒,属于冠状病毒科,可引起冠状病毒病(COVID-19)。这种疾病迅速蔓延,对全球健康构成严重威胁。然而,导致 COVID-19 的详细分子机制尚未阐明。

方法

从 GEO 数据库中的 GSE152075 数据集获取 SARS-CoV-2 感染患者样本的表达谱,包括 mRNA 水平和临床数据。使用加权基因共表达网络分析(WGCNA)识别共表达模块,然后评估基本模块与临床特征之间的关系。使用 R 软件包评估差异表达基因(DEGs)、基因本体论(GO)功能富集和京都基因与基因组百科全书(KEGG)通路。

结果

从 GEO 数据库中获得了 377 例 SARS-CoV-2 感染样本和 54 例有临床和遗传数据的正常样本。在样本类型之间鉴定出 1444 个 DEGs,用于 WGCNA 筛选出 11 个共表达模块。6 个共表达模块与 3 个临床特征(SARS-CoV-2 阳性、年龄和性别)显著相关。在与 SARS-CoV-2 阳性显著相关的两个模块中的 DEGs 中,GO 分析观察到病毒感染策略(病毒翻译)的生物学过程富集。KEGG 信号通路分析表明,两个模块中的 DEGs 通常富集于氧化磷酸化、核糖体和产热途径。此外,在 SARS-CoV-2 感染模块中,确定了一个具有与其他基因最高连接性的五个核心基因集(RPL35A、RPL7A、RPS15、RPS20 和 RPL17),表明这些基因在感染后病毒转录中可能是不可或缺的。

结论

鉴定出与 SARS-CoV-2 感染相关的核心基因和信号通路,可以显著补充对 COVID-19 的现有认识。编码核糖体蛋白的 5 个核心基因可能在 SARS-CoV-2 感染后的病毒蛋白生物合成中不可或缺,可作为 COVID-19 治疗的治疗靶点。这些发现可作为未来关于 SARS-CoV-2 感染与核糖体蛋白功能关联的实验研究的假设模型的基础。

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