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Using an untargeted metabolomics approach to analyze serum metabolites in COVID-19 patients with nucleic acid turning negative.
Chen, Wenyu; Yao, Ming; Chen, Miaomiao; Ou, Zhao; Yang, Qi; He, Yanbin; Zhang, Ning; Deng, Min; Wu, Yuqi; Chen, Rongchang; Tan, Xiaoli; Kong, Ziqing.
  • Chen W; Department of Respiration, Affiliated Hospital of Jiaxing University, Jiaxing, China.
  • Yao M; Department of Anesthesiology and Pain Research Center, Affiliated Hospital of Jiaxing University, Jiaxing, China.
  • Chen M; Key Laboratory of Digital Technology in Medical Diagnostics of Zhejiang Province, Hangzhou, China.
  • Ou Z; Key Laboratory of Digital Technology in Medical Diagnostics of Zhejiang Province, Hangzhou, China.
  • Yang Q; Department of Respiration, Affiliated Hospital of Jiaxing University, Jiaxing, China.
  • He Y; Key Laboratory of Digital Technology in Medical Diagnostics of Zhejiang Province, Hangzhou, China.
  • Zhang N; Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Deng M; Department of Infection, Affiliated Hospital of Jiaxing University, Jiaxing, China.
  • Wu Y; Calibra Lab at DIAN Diagnostics, Hangzhou, China.
  • Chen R; Calibra Lab at DIAN Diagnostics, Hangzhou, China.
  • Tan X; Department of Respiration, Affiliated Hospital of Jiaxing University, Jiaxing, China.
  • Kong Z; Calibra Lab at DIAN Diagnostics, Hangzhou, China.
Front Pharmacol ; 13: 964037, 2022.
Artículo en Inglés | MEDLINE | ID: covidwho-2022839
ABSTRACT

Background:

The coronavirus disease of 2019 (COVID-19) is a severe public health issue that has infected millions of people. The effective prevention and control of COVID-19 has resulted in a considerable increase in the number of cured cases. However, little research has been done on a complete metabonomic examination of metabolic alterations in COVID-19 patients following treatment. The current project pursues rigorously to characterize the variation of serum metabolites between healthy controls and COVID-19 patients with nucleic acid turning negative via untargeted metabolomics.

Methods:

The metabolic difference between 20 COVID-19 patients (CT ≥ 35) and 20 healthy controls were investigated utilizing untargeted metabolomics analysis employing High-resolution UHPLC-MS/MS. COVID-19 patients' fundamental clinical indicators, as well as health controls, were also collected.

Results:

Out of the 714 metabolites identified, 203 still significantly differed between COVID-19 patients and healthy controls, including multiple amino acids, fatty acids, and glycerophospholipids. The clinical indexes including monocytes, lymphocytes, albumin concentration, total bilirubin and direct bilirubin have also differed between our two groups of participators.

Conclusion:

Our results clearly showed that in COVID-19 patients with nucleic acid turning negative, their metabolism was still dysregulated in amino acid metabolism and lipid metabolism, which could be the mechanism of long-COVID and calls for specific post-treatment care to help COVID-19 patients recover.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio experimental / Estudio observacional / Estudio pronóstico / Ensayo controlado aleatorizado Tópicos: Covid persistente Idioma: Inglés Revista: Front Pharmacol Año: 2022 Tipo del documento: Artículo País de afiliación: Fphar.2022.964037

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio experimental / Estudio observacional / Estudio pronóstico / Ensayo controlado aleatorizado Tópicos: Covid persistente Idioma: Inglés Revista: Front Pharmacol Año: 2022 Tipo del documento: Artículo País de afiliación: Fphar.2022.964037