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Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study

Several relatively recently published studies have shown changes in plasma metabolites in various viral diseases such as Zika, Dengue, RSV or SARS-CoV-1. The aim of this study was to analyze the metabolome profile of patients during acute COVID-19 approximately one month after the acute infection an...

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Autores principales: Liptak, Peter, Baranovicova, Eva, Rosolanka, Robert, Simekova, Katarina, Bobcakova, Anna, Vysehradsky, Robert, Duricek, Martin, Dankova, Zuzana, Kapinova, Andrea, Dvorska, Dana, Halasova, Erika, Banovcin, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321209/
https://www.ncbi.nlm.nih.gov/pubmed/35888766
http://dx.doi.org/10.3390/metabo12070641
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author Liptak, Peter
Baranovicova, Eva
Rosolanka, Robert
Simekova, Katarina
Bobcakova, Anna
Vysehradsky, Robert
Duricek, Martin
Dankova, Zuzana
Kapinova, Andrea
Dvorska, Dana
Halasova, Erika
Banovcin, Peter
author_facet Liptak, Peter
Baranovicova, Eva
Rosolanka, Robert
Simekova, Katarina
Bobcakova, Anna
Vysehradsky, Robert
Duricek, Martin
Dankova, Zuzana
Kapinova, Andrea
Dvorska, Dana
Halasova, Erika
Banovcin, Peter
author_sort Liptak, Peter
collection PubMed
description Several relatively recently published studies have shown changes in plasma metabolites in various viral diseases such as Zika, Dengue, RSV or SARS-CoV-1. The aim of this study was to analyze the metabolome profile of patients during acute COVID-19 approximately one month after the acute infection and to compare these results with healthy (SARS-CoV-2-negative) controls. The metabolome analysis was performed by NMR spectroscopy from the peripheral blood of patients and controls. The blood samples were collected on 3 different occasions (at admission, during hospitalization and on control visit after discharge from the hospital). When comparing sample groups (based on the date of acquisition) to controls, there is an indicative shift in metabolomics features based on the time passed after the first sample was taken towards controls. Based on the random forest algorithm, there is a strong discriminatory predictive value between controls and different sample groups (AUC equals 1 for controls versus samples taken at admission, Mathew correlation coefficient equals 1). Significant metabolomic changes persist in patients more than a month after acute SARS-CoV-2 infection. The random forest algorithm shows very strong discrimination (almost ideal) when comparing metabolite levels of patients in two various stages of disease and during the recovery period compared to SARS-CoV-2-negative controls.
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spelling pubmed-93212092022-07-27 Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study Liptak, Peter Baranovicova, Eva Rosolanka, Robert Simekova, Katarina Bobcakova, Anna Vysehradsky, Robert Duricek, Martin Dankova, Zuzana Kapinova, Andrea Dvorska, Dana Halasova, Erika Banovcin, Peter Metabolites Article Several relatively recently published studies have shown changes in plasma metabolites in various viral diseases such as Zika, Dengue, RSV or SARS-CoV-1. The aim of this study was to analyze the metabolome profile of patients during acute COVID-19 approximately one month after the acute infection and to compare these results with healthy (SARS-CoV-2-negative) controls. The metabolome analysis was performed by NMR spectroscopy from the peripheral blood of patients and controls. The blood samples were collected on 3 different occasions (at admission, during hospitalization and on control visit after discharge from the hospital). When comparing sample groups (based on the date of acquisition) to controls, there is an indicative shift in metabolomics features based on the time passed after the first sample was taken towards controls. Based on the random forest algorithm, there is a strong discriminatory predictive value between controls and different sample groups (AUC equals 1 for controls versus samples taken at admission, Mathew correlation coefficient equals 1). Significant metabolomic changes persist in patients more than a month after acute SARS-CoV-2 infection. The random forest algorithm shows very strong discrimination (almost ideal) when comparing metabolite levels of patients in two various stages of disease and during the recovery period compared to SARS-CoV-2-negative controls. MDPI 2022-07-13 /pmc/articles/PMC9321209/ /pubmed/35888766 http://dx.doi.org/10.3390/metabo12070641 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liptak, Peter
Baranovicova, Eva
Rosolanka, Robert
Simekova, Katarina
Bobcakova, Anna
Vysehradsky, Robert
Duricek, Martin
Dankova, Zuzana
Kapinova, Andrea
Dvorska, Dana
Halasova, Erika
Banovcin, Peter
Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study
title Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study
title_full Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study
title_fullStr Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study
title_full_unstemmed Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study
title_short Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study
title_sort persistence of metabolomic changes in patients during post-covid phase: a prospective, observational study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321209/
https://www.ncbi.nlm.nih.gov/pubmed/35888766
http://dx.doi.org/10.3390/metabo12070641
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