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Brief Bioinform ; 23(1)2022 01 17.
Artigo em Inglês | MEDLINE | ID: mdl-34535795

RESUMO

Whether risk genes of severe coronavirus disease 2019 (COVID-19) from genome-wide association study could play their regulatory roles by interacting with host genes that were interacted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator (https://github.com/Haoxiang-Qi/Network-Calculator.git). By using Network Calculator, we identified a network composed of 13 risk genes and 28 SARS-CoV-2 interacted host genes that had the highest network proximity with each other, with a hub gene HNRNPK identified. Among these genes, 14 of them were identified to be differentially expressed in RNA-seq data from severe COVID-19 cases. Besides, by expression enrichment analysis in single-cell RNA-seq data, compared with mild COVID-19, these genes were significantly enriched in macrophage, T cell and epithelial cell for severe COVID-19. Meanwhile, 74 pathways were significantly enriched. Our analysis provided insights for the underlying genetic etiology of severe COVID-19 from the perspective of network biology.


Assuntos
COVID-19 , RNA-Seq , SARS-CoV-2 , Proteínas Virais , COVID-19/genética , COVID-19/metabolismo , Estudo de Associação Genômica Ampla , Humanos , Gravidade do Paciente , Fatores de Risco , SARS-CoV-2/genética , SARS-CoV-2/metabolismo , Proteínas Virais/genética , Proteínas Virais/metabolismo
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