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Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19
The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. Exploratory studies evaluating the impact of COVID-19 infection on the plasma metabolome have been performed, often with small numbers of patients, and with or without relevant control data; however, determi...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132252/ https://www.ncbi.nlm.nih.gov/pubmed/34013258 http://dx.doi.org/10.21203/rs.3.rs-480167/v1 |
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author | D’Alessandro, Angelo Akpan, Imo Thomas, Tiffany Reisz, Julie Cendali, Francesca Gamboni, Fabia Nemkov, Travis Thangaraju, Kiruphagaran Katneni, Upendra Tanaka, Kenichi Kahn, Stacie Wei, Alexander Valk, Jacob Hudson, Krystalyn Roh, David Moriconi, Chiara Zimring, James Hod, Eldad Spitalnik, Steven Buehler, Paul Francis, Richard |
author_facet | D’Alessandro, Angelo Akpan, Imo Thomas, Tiffany Reisz, Julie Cendali, Francesca Gamboni, Fabia Nemkov, Travis Thangaraju, Kiruphagaran Katneni, Upendra Tanaka, Kenichi Kahn, Stacie Wei, Alexander Valk, Jacob Hudson, Krystalyn Roh, David Moriconi, Chiara Zimring, James Hod, Eldad Spitalnik, Steven Buehler, Paul Francis, Richard |
author_sort | D’Alessandro, Angelo |
collection | PubMed |
description | The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. Exploratory studies evaluating the impact of COVID-19 infection on the plasma metabolome have been performed, often with small numbers of patients, and with or without relevant control data; however, determining the impact of biological and clinical variables remains critical to understanding potential markers of disease severity and progression. The present large study, including relevant controls, sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831), testing positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on 831 plasma samples from acutely ill patients while in the emergency department, at admission, and during hospitalization. We then performed additional lipidomics analyses of the 60 subjects with the lowest and highest body mass index, either COVID-19 positive or negative. Omics data were correlated to detailed data on patient characteristics and clinical laboratory assays measuring coagulation, hematology and chemistry analytes. Significant changes in arginine/proline/citrulline, tryptophan/indole/kynurenine, fatty acid and acyl-carnitine metabolism emerged as highly relevant markers of disease severity, progression and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half yielding ~ 78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for follow-up mechanistic studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses. |
format | Online Article Text |
id | pubmed-8132252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-81322522021-05-20 Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 D’Alessandro, Angelo Akpan, Imo Thomas, Tiffany Reisz, Julie Cendali, Francesca Gamboni, Fabia Nemkov, Travis Thangaraju, Kiruphagaran Katneni, Upendra Tanaka, Kenichi Kahn, Stacie Wei, Alexander Valk, Jacob Hudson, Krystalyn Roh, David Moriconi, Chiara Zimring, James Hod, Eldad Spitalnik, Steven Buehler, Paul Francis, Richard Res Sq Article The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. Exploratory studies evaluating the impact of COVID-19 infection on the plasma metabolome have been performed, often with small numbers of patients, and with or without relevant control data; however, determining the impact of biological and clinical variables remains critical to understanding potential markers of disease severity and progression. The present large study, including relevant controls, sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831), testing positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on 831 plasma samples from acutely ill patients while in the emergency department, at admission, and during hospitalization. We then performed additional lipidomics analyses of the 60 subjects with the lowest and highest body mass index, either COVID-19 positive or negative. Omics data were correlated to detailed data on patient characteristics and clinical laboratory assays measuring coagulation, hematology and chemistry analytes. Significant changes in arginine/proline/citrulline, tryptophan/indole/kynurenine, fatty acid and acyl-carnitine metabolism emerged as highly relevant markers of disease severity, progression and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half yielding ~ 78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for follow-up mechanistic studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses. American Journal Experts 2021-05-10 /pmc/articles/PMC8132252/ /pubmed/34013258 http://dx.doi.org/10.21203/rs.3.rs-480167/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article D’Alessandro, Angelo Akpan, Imo Thomas, Tiffany Reisz, Julie Cendali, Francesca Gamboni, Fabia Nemkov, Travis Thangaraju, Kiruphagaran Katneni, Upendra Tanaka, Kenichi Kahn, Stacie Wei, Alexander Valk, Jacob Hudson, Krystalyn Roh, David Moriconi, Chiara Zimring, James Hod, Eldad Spitalnik, Steven Buehler, Paul Francis, Richard Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 |
title | Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 |
title_full | Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 |
title_fullStr | Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 |
title_full_unstemmed | Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 |
title_short | Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19 |
title_sort | biological and clinical factors contributing to the metabolic heterogeneity of hospitalized patients with and without covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132252/ https://www.ncbi.nlm.nih.gov/pubmed/34013258 http://dx.doi.org/10.21203/rs.3.rs-480167/v1 |
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