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The unfolded protein response pathway as a possible link in the pathogenesis of COVID-19 and sepsis.
Liu, Hong; Wang, Junyi; Li, Shaofeng; Sun, Yanmei; Zhang, Peng; Ma, Jiahao.
Afiliação
  • Liu H; School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Wang J; Advanced Medical Research Institute, Shandong University, Jinan, Shandong, China.
  • Li S; School of Pharmacy, Key Laboratory of Nano-carbon Modified Film Technology of Henan Province, Diagnostic Laboratory of Animal Diseases, Xinxiang University, Xinxiang, China.
  • Sun Y; School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Zhang P; School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Ma J; School of Pharmacy, Key Laboratory of Nano-carbon Modified Film Technology of Henan Province, Diagnostic Laboratory of Animal Diseases, Xinxiang University, Xinxiang, China. ma1106013028@163.com.
Arch Virol ; 169(2): 20, 2024 Jan 08.
Article em En | MEDLINE | ID: mdl-38191819
ABSTRACT
The global impact of the COVID-19 pandemic has been substantial. Emerging evidence underscores a strong clinical connection between COVID-19 and sepsis. Numerous studies have identified the unfolded protein response (UPR) pathway as a crucial pathogenic pathway for both COVID-19 and sepsis, but it remains to be investigated whether this signaling pathway operates as a common pathogenic mechanism for both COVID-19 and sepsis. In this study, single-cell RNA-seq data and transcriptome data for COVID-19 and sepsis cases were downloaded from GEO (Gene Expression Omnibus). By analyzing the single-cell transcriptome data, we identified B cells as the critical cell subset and the UPR pathway as the critical signaling pathway. Based on the transcriptome data, a machine learning diagnostic model was then constructed using the interleaved genes of B-cell-related and UPR-pathway-related genes. We validated the diagnostic model using both internal and external datasets and found the accuracy and stability of this model to be extremely strong. Even after integrating our algorithmic model with the patient's clinical status, it continued to yield identical results, further emphasizing the reliability of this model. This study provides a novel molecular perspective on the pathogenesis of sepsis and COVID-19 at the single-cell level and suggests that these two diseases may share a common mechanism.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sepse / COVID-19 Tipo de estudo: Etiology_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Arch Virol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sepse / COVID-19 Tipo de estudo: Etiology_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Arch Virol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China