Insights into potential mechanisms of asthma patients with COVID-19: A study based on the gene expression profiling of bronchoalveolar lavage fluid

被引:16
作者
Jiang, Yong [1 ]
Yan, Qian [2 ]
Liu, Cheng-Xin [2 ]
Peng, Chen-Wen [2 ]
Zheng, Wen-Jiang [2 ]
Zhuang, Hong-Fa [3 ]
Huang, Hui-ting [3 ]
Liu, Qiong [3 ]
Liao, Hui-Li [3 ]
Zhan, Shao-Feng [3 ,4 ]
Liu, Xiao-Hong [3 ,4 ]
Huang, Xiu-Fang [3 ,5 ]
机构
[1] Shenzhen Hosp Integrated Tradit Chinese & Western, Shenzhen, Peoples R China
[2] Guangzhou Univ Chinese Med, Clin Med Sch 1, Guangzhou, Peoples R China
[3] Guangzhou Univ Chinese Med, Affiliated Hosp 1, Guangzhou, Peoples R China
[4] Guangzhou Univ Chinese Med, Affiliated Hosp 1, Lingnan Med Res Ctr, 12 Airport Rd, Guangzhou 510405, Peoples R China
[5] Guangzhou Univ Chinese Med, Affiliated Hosp 1, 12 Airport Rd, Guangzhou 510405, Peoples R China
基金
中国国家自然科学基金;
关键词
COVID-19; Asthma; Host factor interaction networks; Bioinformatics analysis; Comorbidity; Severity; BRONCHIAL EPITHELIAL-CELLS; AIRWAY INFLAMMATION; ENDOTHELIAL GLYCOCALYX; CYTOKINE STORM; NRF2; ASSOCIATION; INHIBITION; MORTALITY; PATHWAY; SARS-COV-2;
D O I
10.1016/j.compbiomed.2022.105601
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: The 2019 novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a major challenge threatening the global healthcare system. Respiratory virus infection is the most common cause of asthma attacks, and thus COVID-19 may contribute to an increase in asthma exacerbations. However, the mechanisms of COVID-19/asthma comorbidity remain unclear. Methods: The "Limma " package or "DESeq2 " package was used to screen differentially expressed genes (DEGs). Alveolar lavage fluid datasets of COVID-19 and asthma were obtained from the GEO and GSV database. A series of analyses of common host factors for COVID-19 and asthma were conducted, including PPI network construction, module analysis, enrichment analysis, inference of the upstream pathway activity of host factors, tissue-specific analysis and drug candidate prediction. Finally, the key host factors were verified in the GSE152418 and GSE164805 datasets. Results: 192 overlapping host factors were obtained by analyzing the intersection of asthma and COVID-19. FN1, UBA52, EEF1A1, ITGB1, XPO1, NPM1, EGR1, EIF4E, SRSF1, CCR5, PXN, IRF8 and DDX5 as host factors were tightly connected in the PPI network. Module analysis identified five modules with different biological functions and pathways. According to the degree values ranking in the PPI network, EEF1A1, EGR1, UBA52, DDX5 and IRF8 were considered as the key cohost factors for COVID-19 and asthma. The H2O2, VEGF, IL-1 and Wnt signaling pathways had the strongest activities in the upstream pathways. Tissue-specific enrichment analysis revealed the different expression levels of the five critical host factors. LY294002, wortmannin, PD98059 and heparin might have great potential to evolve into therapeutic drugs for COVID-19 and asthma comorbidity. Finally, the validation dataset confirmed that the expression of five key host factors were statistically significant among COVID-19 groups with different severity and healthy control subjects. Conclusions: This study constructed a network of common host factors between asthma and COVID-19 and predicted several drugs with therapeutic potential. Therefore, this study is likely to provide a reference for the management and treatment for COVID-19/asthma comorbidity.
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页数:16
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