Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters

Database
Language
Document Type
Year range
1.
Brief Bioinform ; 23(1)2022 01 17.
Article in English | MEDLINE | ID: covidwho-1429177

ABSTRACT

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.


Subject(s)
COVID-19 , RNA-Seq , SARS-CoV-2 , Viral Proteins , COVID-19/genetics , COVID-19/metabolism , Genome-Wide Association Study , Humans , Patient Acuity , Risk Factors , SARS-CoV-2/genetics , SARS-CoV-2/metabolism , Viral Proteins/genetics , Viral Proteins/metabolism
SELECTION OF CITATIONS
SEARCH DETAIL