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pmid:36911695
The use of bioinformatics methods to identify the effects of SARS-CoV-2 and influenza viruses on the regulation of gene expression in patients.
Zhongyi Sun · Li Ke · Qiuyue Zhao · Jiachen Qu · Yanan Hu · Han Gao · Zhiyong Peng
Frontiers in immunology · 2023 doi:10.3389/fimmu.2023.1098688
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Complete file
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Numerous studies have reported similarities and differences in the clinical manifestations, laboratory tests, and mortality between these two infections. However, the genetic effects of coronavirus and influenza viruses on the host that lead to these characteristics have rarely been reported.\nMethods: COVID-19 (GSE157103) and influenza (GSE111368, GSE101702) datasets were downloaded from the Gene Expression Ominbus (GEO) database. Differential gene, gene set enrichment, protein-protein interaction (PPI) network, gene regulatory network, and immune cell infiltration analyses were performed to identify the critical impact of COVID-19 and influenza viruses on the regulation of host gene expression.\nResults: The number of differentially expressed genes in the COVID-19 patients was significantly higher than in the influenza patients. 22 common differentially expressed genes (DEGs) were identified between the COVID-19 and influenza datasets. The effects of the viruses on the regulation of host gene expression were determined using gene set enrichment and PPI network analyses. Five HUB genes were finally identified: IFI27, OASL, RSAD2, IFI6, and IFI44L.\nConclusion: We identified five HUB genes between COVID-19 and influenza virus infection, which might be helpful in the diagnosis and treatment of COVID-19 and influenza. This knowledge may also guide future mechanistic studies that aim to identify pathogen-specific interventions.", "claims": [{"id": "claim-method", "statement": "After normalization, the raw sequencing data were log2-transformed, and the resulting array was directly analyzed using the R package “limma” (17).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36911695", "locator": "sections[4] \"Analysis of differentially expressed genes\" paragraph 2", "quote": "After normalization, the raw sequencing data were log2-transformed, and the resulting array was directly analyzed using the R package “limma” (17)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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