COVID-19 感染与原发性干燥综合征潜在共同致病机制的生物信息学分析。

Bioinformatics analysis of potential common pathogenic mechanisms for COVID-19 infection and primary Sjogren's syndrome.

机构信息

Department of Tuberculosis and Respiratory, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Hubei Clinical Research Center for Infectious Diseases, Wuhan, China.

出版信息

Front Immunol. 2022 Jul 26;13:938837. doi: 10.3389/fimmu.2022.938837. eCollection 2022.

BACKGROUND

Accumulating evidence has revealed that the prevalence of Coronavirus 2019 (COVID-19) was significantly higher in patients with primary Sjogren's syndrome (pSS) compared to the general population. However, the mechanism remains incompletely elucidated. This study aimed to further investigate the molecular mechanisms underlying the development of this complication.

METHODS

The gene expression profiles of COVID-19 (GSE157103) and pSS (GSE40611) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for pSS and COVID-19, functional annotation, protein-protein interaction (PPI) network, module construction and hub gene identification were performed. Finally, we constructed transcription factor (TF)-gene regulatory network and TF-miRNA regulatory network for hub genes.

RESULTS

A total of 40 common DEGs were selected for subsequent analyses. Functional analyses showed that cellular components and metabolic pathways collectively participated in the development and progression of pSS and COVID-19. Finally, 12 significant hub genes were identified using the cytoHubba plugin, including CMPK2, TYMS, RRM2, HERC5, IFI44L, IFI44, IFIT2, IFIT1, IFIT3, MX1, CDCA2 and TOP2A, which had preferable values as diagnostic markers for COVID-19 and pSS.

CONCLUSIONS

Our study reveals common pathogenesis of pSS and COVID-19. These common pathways and pivotal genes may provide new ideas for further mechanistic studies.

背景

越来越多的证据表明，原发性干燥综合征（pSS）患者 2019 年冠状病毒病（COVID-19）的患病率明显高于普通人群。然而，其机制仍不完全清楚。本研究旨在进一步探讨这种并发症发展的潜在分子机制。

方法

从基因表达综合数据库（GEO）中下载 COVID-19（GSE157103）和 pSS（GSE40611）的基因表达谱。在确定 pSS 和 COVID-19 的共同差异表达基因（DEGs）后，进行功能注释、蛋白质-蛋白质相互作用（PPI）网络、模块构建和关键基因鉴定。最后，我们构建了关键基因的转录因子（TF）-基因调控网络和 TF-miRNA 调控网络。

结果

共选择了 40 个共同的 DEGs 进行后续分析。功能分析表明，细胞成分和代谢途径共同参与了 pSS 和 COVID-19 的发生和发展。最后，使用 cytoHubba 插件鉴定出 12 个重要的关键基因，包括 CMPK2、TYMS、RRM2、HERC5、IFI44L、IFI44、IFIT2、IFIT1、IFIT3、MX1、CDCA2 和 TOP2A，它们作为 COVID-19 和 pSS 的诊断标志物具有较好的价值。