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Peripheral Blood Genes Crosstalk between COVID-19 and Sepsis.
Fang, Changyin; Ma, Yongping.
  • Fang C; Department of Biochemistry and Molecular Biology, Basic Medical College, Chongqing Medical University, Yuzhong District, Yi XueYuan Road, No 1, Chongqing 400016, China.
  • Ma Y; Department of Biochemistry and Molecular Biology, Basic Medical College, Chongqing Medical University, Yuzhong District, Yi XueYuan Road, No 1, Chongqing 400016, China.
Int J Mol Sci ; 24(3)2023 Jan 30.
Article in English | MEDLINE | ID: covidwho-2240601
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Sepsis / MicroRNAs / COVID-19 Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Year: 2023 Document Type: Article Affiliation country: Ijms24032591

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Sepsis / MicroRNAs / COVID-19 Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Year: 2023 Document Type: Article Affiliation country: Ijms24032591