Wenyu Chen1, Ming Yao2, Miaomiao Chen3, Zhao Ou3, Qi Yang1, Yanbin He3, Ning Zhang4, Min Deng5, Yuqi Wu6, Rongchang Chen6, Xiaoli Tan1, Ziqing Kong6. 1. Department of Respiration, Affiliated Hospital of Jiaxing University, Jiaxing, China. 2. Department of Anesthesiology and Pain Research Center, Affiliated Hospital of Jiaxing University, Jiaxing, China. 3. Key Laboratory of Digital Technology in Medical Diagnostics of Zhejiang Province, Hangzhou, China. 4. Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China. 5. Department of Infection, Affiliated Hospital of Jiaxing University, Jiaxing, China. 6. Calibra Lab at DIAN Diagnostics, Hangzhou, China.
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.
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.
Authors: Lloyd W Sumner; Alexander Amberg; Dave Barrett; Michael H Beale; Richard Beger; Clare A Daykin; Teresa W-M Fan; Oliver Fiehn; Royston Goodacre; Julian L Griffin; Thomas Hankemeier; Nigel Hardy; James Harnly; Richard Higashi; Joachim Kopka; Andrew N Lane; John C Lindon; Philip Marriott; Andrew W Nicholls; Michael D Reily; John J Thaden; Mark R Viant Journal: Metabolomics Date: 2007-09 Impact factor: 4.290