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Peripheral Blood Genes Crosstalk between COVID-19 and Sepsis

Severe coronavirus disease 2019 (COVID-19) has led to a rapid increase in death rates all over the world. Sepsis is a life-threatening disease associated with a dysregulated host immune response. It has been shown that COVID-19 shares many similarities with sepsis in many aspects. However, the molec...

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Detalles Bibliográficos
Autores principales: Fang, Changyin, Ma, Yongping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916586/
https://www.ncbi.nlm.nih.gov/pubmed/36768914
http://dx.doi.org/10.3390/ijms24032591
Descripción
Sumario:Severe coronavirus disease 2019 (COVID-19) has led to a rapid increase in death rates all over the world. Sepsis is a life-threatening disease associated with a dysregulated host immune response. It has been shown that COVID-19 shares many similarities with sepsis in many aspects. However, the molecular mechanisms underlying sepsis and COVID-19 are not well understood. The aim of this study was to identify common transcriptional signatures, regulators, and pathways between COVID-19 and sepsis, which may provide a new direction for the treatment of COVID-19 and sepsis. First, COVID-19 blood gene expression profile (GSE179850) data and sepsis blood expression profile (GSE134347) data were obtained from GEO. Then, we intersected the differentially expressed genes (DEG) from these two datasets to obtain common DEGs. Finally, the common DEGs were used for functional enrichment analysis, transcription factor and miRNA prediction, pathway analysis, and candidate drug analysis. A total of 307 common DEGs were identified between the sepsis and COVID-19 datasets. Protein–protein interactions (PPIs) were constructed using the STRING database. Subsequently, hub genes were identified based on PPI networks. In addition, we performed GO functional analysis and KEGG pathway analysis of common DEGs, and found a common association between sepsis and COVID-19. Finally, we identified transcription factor–gene interaction, DEGs-miRNA co-regulatory networks, and protein–drug interaction, respectively. Through ROC analysis, we identified 10 central hub genes as potential biomarkers. In this study, we identified SARS-CoV-2 infection as a high risk factor for sepsis. Our study may provide a potential therapeutic direction for the treatment of COVID-19 patients suffering from sepsis.