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Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data.
Dong, Zehua; Yan, Qiyu; Cao, Wenxiu; Liu, Zhixian; Wang, Xiaosheng.
  • Dong Z; Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Yan Q; Big Data Research Institute, China Pharmaceutical University, Nanjing, China.
  • Cao W; Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Liu Z; Big Data Research Institute, China Pharmaceutical University, Nanjing, China.
  • Wang X; Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
Front Immunol ; 13: 930866, 2022.
Artículo en Inglés | MEDLINE | ID: covidwho-2022713
ABSTRACT

Background:

Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored.

Methods:

This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients.

Results:

This analysis identified 13 genes significantly upregulated in COVID-19 patients' leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes' downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes.

Conclusions:

A strong antiviral immune response is essential in reducing severity of COVID-19.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Transcriptoma / COVID-19 Tipo de estudio: Estudio pronóstico Límite: Humanos Idioma: Inglés Revista: Front Immunol Año: 2022 Tipo del documento: Artículo País de afiliación: Fimmu.2022.930866

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Transcriptoma / COVID-19 Tipo de estudio: Estudio pronóstico Límite: Humanos Idioma: Inglés Revista: Front Immunol Año: 2022 Tipo del documento: Artículo País de afiliación: Fimmu.2022.930866