ArticlePloS one2024
Identification of the feature genes involved in cytokine release syndrome in COVID-19.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- Viral Mechanisms and Drug Influences on Janus Kinase/Signal Transducers and Activators of Transcription (JAK/STAT) Pathway in Human Coronaviruses Infection: A Systematic Review.Health science reports · 2026Review
- Article
- Genetic Susceptibility in Endothelial Injury Syndromes after Hematopoietic Cell Transplantation and Other Cellular Therapies: Climbing a Steep Hill.Current issues in molecular biology · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveScreening of feature genes involved in cytokine release syndrome (CRS) from the coronavirus disease 19 (COVID-19).
methodsThe data sets related to COVID-19 were retrieved using Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) related to CRS were analyzed with R software and Venn diagram, and the biological processes and signaling pathways involved in DEGs were analyzed with GO and KEGG enrichment. Core genes were screened using Betweenness and MCC algorithms. GSE164805 and GSE171110 dataset were used to verify the expression level of core genes. Immunoinfiltration analysis was performed by ssGSEA algorithm in the GSVA package. The DrugBank database was used to analyze the feature genes for potential therapeutic drugs.
resultsThis study obtained 6950 DEGs, of which 971 corresponded with CRS disease genes (common genes). GO and KEGG enrichment showed that multiple biological processes and signaling pathways associated with common genes were closely related to the inflammatory response. Furthermore, the analysis revealed that transcription factors that regulate these common genes are also involved in inflammatory response. Betweenness and MCC algorithms were used for common gene screening, yielding seven key genes. GSE164805 and GSE171110 dataset validation revealed significant differences between the COVID-19 and normal controls in four core genes (feature genes), namely IL6R, TLR4, TLR2, and IFNG. The upregulated IL6R, TLR4, and TLR2 genes were mainly involved in the Toll-like receptor signaling pathway of the inflammatory pathway, while the downregulated IFNG genes primarily participated in the necroptosis and JAK-STAT signaling pathways. Moreover, immune infiltration analysis indicated that higher expression of these genes was associated with immune cell infiltration that mediates inflammatory response. In addition, potential therapeutic drugs for these four feature genes were identified via the DrugBank database.
conclusionIL6R, TLR4, TLR2, and IFNG may be potential pathogenic genes and therapeutic targets for the CRS associated with COVID-19.
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