Bioinformatics and systems-biology analysis to determine the effects of Coronavirus disease 2019 on patients with allergic asthma

Hongwei Fang; Zhun Sun; Zhouyi Chen; Anning Chen; Donglin Sun; Yan Kong; Hao Fang; Guojun Qian

doi:10.3389/fimmu.2022.988479

Bioinformatics and systems-biology analysis to determine the effects of Coronavirus disease 2019 on patients with allergic asthma

Front Immunol. 2022 Sep 23:13:988479. doi: 10.3389/fimmu.2022.988479. eCollection 2022.

Authors

Hongwei Fang^{1

2}, Zhun Sun², Zhouyi Chen¹, Anning Chen², Donglin Sun², Yan Kong³, Hao Fang^{1

4}, Guojun Qian²

Affiliations

¹ Department of Anesthesiology, Zhongshan Hospital, Fudan University, Shanghai, China.
² Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China.
³ Department of Anesthesiology (High-Tech Branch), The First Affiliated Hospital of Anhui Medical University, Hefei, China.
⁴ Department of Anesthesiology, Minhang Hospital, Fudan University, Shanghai, China.

Abstract

Background: The coronavirus disease (COVID-19) pandemic has posed a significant challenge for global health systems. Increasing evidence shows that asthma phenotypes and comorbidities are major risk factors for COVID-19 symptom severity. However, the molecular mechanisms underlying the association between COVID-19 and asthma are poorly understood. Therefore, we conducted bioinformatics and systems biology analysis to identify common pathways and molecular biomarkers in patients with COVID-19 and asthma, as well as potential molecular mechanisms and candidate drugs for treating patients with both COVID-19 and asthma.

Methods: Two sets of differentially expressed genes (DEGs) from the GSE171110 and GSE143192 datasets were intersected to identify common hub genes, shared pathways, and candidate drugs. In addition, murine models were utilized to explore the expression levels and associations of the hub genes in asthma and lung inflammation/injury.

Results: We discovered 157 common DEGs between the asthma and COVID-19 datasets. A protein-protein-interaction network was built using various combinatorial statistical approaches and bioinformatics tools, which revealed several hub genes and critical modules. Six of the hub genes were markedly elevated in murine asthmatic lungs and were positively associated with IL-5, IL-13 and MUC5AC, which are the key mediators of allergic asthma. Gene Ontology and pathway analysis revealed common associations between asthma and COVID-19 progression. Finally, we identified transcription factor-gene interactions, DEG-microRNA coregulatory networks, and potential drug and chemical-compound interactions using the hub genes.

Conclusion: We identified the top 15 hub genes that can be used as novel biomarkers of COVID-19 and asthma and discovered several promising candidate drugs that might be helpful for treating patients with COVID-19 and asthma.

Keywords: allergic asthma; bioinformatics; coronavirus disease 2019; disease biomarker; drug; gene ontology; hub gene; systems-biology.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Asthma* / genetics
Biomarkers, Tumor / genetics
COVID-19* / genetics
Computational Biology
Gene Expression Profiling
Gene Regulatory Networks
Interleukin-13 / genetics
Interleukin-5 / genetics
Mice
MicroRNAs* / genetics
Systems Biology
Transcription Factors / genetics

Substances

Biomarkers, Tumor
Interleukin-13
Interleukin-5
MicroRNAs
Transcription Factors