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Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population

Biomarkers of low-grade inflammation have been associated with susceptibility to a severe infectious disease course, even when measured prior to disease onset. We investigated whether metabolic biomarkers measured by nuclear magnetic resonance (NMR) spectroscopy could be associated with susceptibili...

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Autores principales: Julkunen, Heli, Cichońska, Anna, Slagboom, P Eline, Würtz, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172246/
https://www.ncbi.nlm.nih.gov/pubmed/33942721
http://dx.doi.org/10.7554/eLife.63033
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author Julkunen, Heli
Cichońska, Anna
Slagboom, P Eline
Würtz, Peter
author_facet Julkunen, Heli
Cichońska, Anna
Slagboom, P Eline
Würtz, Peter
author_sort Julkunen, Heli
collection PubMed
description Biomarkers of low-grade inflammation have been associated with susceptibility to a severe infectious disease course, even when measured prior to disease onset. We investigated whether metabolic biomarkers measured by nuclear magnetic resonance (NMR) spectroscopy could be associated with susceptibility to severe pneumonia (2507 hospitalised or fatal cases) and severe COVID-19 (652 hospitalised cases) in 105,146 generally healthy individuals from UK Biobank, with blood samples collected 2007–2010. The overall signature of metabolic biomarker associations was similar for the risk of severe pneumonia and severe COVID-19. A multi-biomarker score, comprised of 25 proteins, fatty acids, amino acids, and lipids, was associated equally strongly with enhanced susceptibility to severe COVID-19 (odds ratio 2.9 [95%CI 2.1–3.8] for highest vs lowest quintile) and severe pneumonia events occurring 7–11 years after blood sampling (2.6 [1.7–3.9]). However, the risk for severe pneumonia occurring during the first 2 years after blood sampling for people with elevated levels of the multi-biomarker score was over four times higher than for long-term risk (8.0 [4.1–15.6]). If these hypothesis generating findings on increased susceptibility to severe pneumonia during the first few years after blood sampling extend to severe COVID-19, metabolic biomarker profiling could potentially complement existing tools for identifying individuals at high risk. These results provide novel molecular understanding on how metabolic biomarkers reflect the susceptibility to severe COVID-19 and other infections in the general population.
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spelling pubmed-81722462021-06-04 Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population Julkunen, Heli Cichońska, Anna Slagboom, P Eline Würtz, Peter eLife Epidemiology and Global Health Biomarkers of low-grade inflammation have been associated with susceptibility to a severe infectious disease course, even when measured prior to disease onset. We investigated whether metabolic biomarkers measured by nuclear magnetic resonance (NMR) spectroscopy could be associated with susceptibility to severe pneumonia (2507 hospitalised or fatal cases) and severe COVID-19 (652 hospitalised cases) in 105,146 generally healthy individuals from UK Biobank, with blood samples collected 2007–2010. The overall signature of metabolic biomarker associations was similar for the risk of severe pneumonia and severe COVID-19. A multi-biomarker score, comprised of 25 proteins, fatty acids, amino acids, and lipids, was associated equally strongly with enhanced susceptibility to severe COVID-19 (odds ratio 2.9 [95%CI 2.1–3.8] for highest vs lowest quintile) and severe pneumonia events occurring 7–11 years after blood sampling (2.6 [1.7–3.9]). However, the risk for severe pneumonia occurring during the first 2 years after blood sampling for people with elevated levels of the multi-biomarker score was over four times higher than for long-term risk (8.0 [4.1–15.6]). If these hypothesis generating findings on increased susceptibility to severe pneumonia during the first few years after blood sampling extend to severe COVID-19, metabolic biomarker profiling could potentially complement existing tools for identifying individuals at high risk. These results provide novel molecular understanding on how metabolic biomarkers reflect the susceptibility to severe COVID-19 and other infections in the general population. eLife Sciences Publications, Ltd 2021-05-04 /pmc/articles/PMC8172246/ /pubmed/33942721 http://dx.doi.org/10.7554/eLife.63033 Text en © 2021, Julkunen et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Epidemiology and Global Health
Julkunen, Heli
Cichońska, Anna
Slagboom, P Eline
Würtz, Peter
Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
title Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
title_full Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
title_fullStr Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
title_full_unstemmed Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
title_short Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
title_sort metabolic biomarker profiling for identification of susceptibility to severe pneumonia and covid-19 in the general population
topic Epidemiology and Global Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172246/
https://www.ncbi.nlm.nih.gov/pubmed/33942721
http://dx.doi.org/10.7554/eLife.63033
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