Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19

Abstract Research exploring the development and outcome of COVID-19 infections has led to the need to find better diagnostic and prognostic biomarkers. This cross-sectional study used targeted metabolomics to identify potential COVID-19 biomarkers that predicted the course of the illness by assessin...

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Autores principales:	Yamilé López-Hernández, Joel Monárrez-Espino, Ana-Sofía Herrera-van Oostdam, Julio Enrique Castañeda Delgado, Lun Zhang, Jiamin Zheng, Juan José Oropeza Valdez, Rupasri Mandal, Fátima de Lourdes Ochoa González, Juan Carlos Borrego Moreno, Flor M. Trejo-Medinilla, Jesús Adrián López, José Antonio Enciso Moreno, David S. Wishart
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8ff8b043cd734a649ee74f44c69b07b6
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spelling	oai:doaj.org-article:8ff8b043cd734a649ee74f44c69b07b62021-12-02T17:03:49ZTargeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-1910.1038/s41598-021-94171-y2045-2322https://doaj.org/article/8ff8b043cd734a649ee74f44c69b07b62021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94171-yhttps://doaj.org/toc/2045-2322Abstract Research exploring the development and outcome of COVID-19 infections has led to the need to find better diagnostic and prognostic biomarkers. This cross-sectional study used targeted metabolomics to identify potential COVID-19 biomarkers that predicted the course of the illness by assessing 110 endogenous plasma metabolites from individuals admitted to a local hospital for diagnosis/treatment. Patients were classified into four groups (≈ 40 each) according to standard polymerase chain reaction (PCR) COVID-19 testing and disease course: PCR−/controls (i.e., non-COVID controls), PCR+/not-hospitalized, PCR+/hospitalized, and PCR+/intubated. Blood samples were collected within 2 days of admission/PCR testing. Metabolite concentration data, demographic data and clinical data were used to propose biomarkers and develop optimal regression models for the diagnosis and prognosis of COVID-19. The area under the receiver operating characteristic curve (AUC; 95% CI) was used to assess each models’ predictive value. A panel that included the kynurenine: tryptophan ratio, lysoPC a C26:0, and pyruvic acid discriminated non-COVID controls from PCR+/not-hospitalized (AUC = 0.947; 95% CI 0.931–0.962). A second panel consisting of C10:2, butyric acid, and pyruvic acid distinguished PCR+/not-hospitalized from PCR+/hospitalized and PCR+/intubated (AUC = 0.975; 95% CI 0.968–0.983). Only lysoPC a C28:0 differentiated PCR+/hospitalized from PCR+/intubated patients (AUC = 0.770; 95% CI 0.736–0.803). If additional studies with targeted metabolomics confirm the diagnostic value of these plasma biomarkers, such panels could eventually be of clinical use in medical practice.Yamilé López-HernándezJoel Monárrez-EspinoAna-Sofía Herrera-van OostdamJulio Enrique Castañeda DelgadoLun ZhangJiamin ZhengJuan José Oropeza ValdezRupasri MandalFátima de Lourdes Ochoa GonzálezJuan Carlos Borrego MorenoFlor M. Trejo-MedinillaJesús Adrián LópezJosé Antonio Enciso MorenoDavid S. WishartNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yamilé López-Hernández Joel Monárrez-Espino Ana-Sofía Herrera-van Oostdam Julio Enrique Castañeda Delgado Lun Zhang Jiamin Zheng Juan José Oropeza Valdez Rupasri Mandal Fátima de Lourdes Ochoa González Juan Carlos Borrego Moreno Flor M. Trejo-Medinilla Jesús Adrián López José Antonio Enciso Moreno David S. Wishart Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19
description	Abstract Research exploring the development and outcome of COVID-19 infections has led to the need to find better diagnostic and prognostic biomarkers. This cross-sectional study used targeted metabolomics to identify potential COVID-19 biomarkers that predicted the course of the illness by assessing 110 endogenous plasma metabolites from individuals admitted to a local hospital for diagnosis/treatment. Patients were classified into four groups (≈ 40 each) according to standard polymerase chain reaction (PCR) COVID-19 testing and disease course: PCR−/controls (i.e., non-COVID controls), PCR+/not-hospitalized, PCR+/hospitalized, and PCR+/intubated. Blood samples were collected within 2 days of admission/PCR testing. Metabolite concentration data, demographic data and clinical data were used to propose biomarkers and develop optimal regression models for the diagnosis and prognosis of COVID-19. The area under the receiver operating characteristic curve (AUC; 95% CI) was used to assess each models’ predictive value. A panel that included the kynurenine: tryptophan ratio, lysoPC a C26:0, and pyruvic acid discriminated non-COVID controls from PCR+/not-hospitalized (AUC = 0.947; 95% CI 0.931–0.962). A second panel consisting of C10:2, butyric acid, and pyruvic acid distinguished PCR+/not-hospitalized from PCR+/hospitalized and PCR+/intubated (AUC = 0.975; 95% CI 0.968–0.983). Only lysoPC a C28:0 differentiated PCR+/hospitalized from PCR+/intubated patients (AUC = 0.770; 95% CI 0.736–0.803). If additional studies with targeted metabolomics confirm the diagnostic value of these plasma biomarkers, such panels could eventually be of clinical use in medical practice.
format	article
author	Yamilé López-Hernández Joel Monárrez-Espino Ana-Sofía Herrera-van Oostdam Julio Enrique Castañeda Delgado Lun Zhang Jiamin Zheng Juan José Oropeza Valdez Rupasri Mandal Fátima de Lourdes Ochoa González Juan Carlos Borrego Moreno Flor M. Trejo-Medinilla Jesús Adrián López José Antonio Enciso Moreno David S. Wishart
author_facet	Yamilé López-Hernández Joel Monárrez-Espino Ana-Sofía Herrera-van Oostdam Julio Enrique Castañeda Delgado Lun Zhang Jiamin Zheng Juan José Oropeza Valdez Rupasri Mandal Fátima de Lourdes Ochoa González Juan Carlos Borrego Moreno Flor M. Trejo-Medinilla Jesús Adrián López José Antonio Enciso Moreno David S. Wishart
author_sort	Yamilé López-Hernández
title	Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19
title_short	Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19
title_full	Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19
title_fullStr	Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19
title_full_unstemmed	Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19
title_sort	targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for covid-19
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8ff8b043cd734a649ee74f44c69b07b6
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Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19

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