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

  1. Nightingale Health UK Biobank Initiative
  2. Heli Julkunen
  3. Anna Cichońska
  4. P Eline Slagboom
  5. Peter Würtz  Is a corresponding author
  1. Nightingale Health Ltd, Finland
  2. Leiden University Medical Center, Netherlands

Abstract

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.

Data availability

The data are available for approved researchers from UK Biobank. The metabolic biomarker data has been released to the UK Biobank resource in March 2021.

The following previously published data sets were used
    1. Sudlow et al
    (2015) UK Biobank
    https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779.

Article and author information

Author details

  1. Nightingale Health UK Biobank Initiative

  2. Heli Julkunen

    R&D, Nightingale Health Ltd, Helsinki, Finland
    Competing interests
    Heli Julkunen, HJ is employee of Nightingale Health Ltd..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4282-0248
  3. Anna Cichońska

    R&D, Nightingale Health Ltd, Helsinki, Finland
    Competing interests
    Anna Cichońska, AC is employee and hold stock options with Nightingale Health Ltd..
  4. P Eline Slagboom

    Leiden University Medical Center, Leiden, Netherlands
    Competing interests
    No competing interests declared.
  5. Peter Würtz

    R&D, Nightingale Health Ltd, Helsinki, Finland
    For correspondence
    peter.wurtz@nightingalehealth.com
    Competing interests
    Peter Würtz, PW is employee and shareholder of Nightingale Health Ltd..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5832-0221

Funding

The study was funded by Nightingale Health Plc. Three of the study authors are employees of Nightingale Health Plc.

Ethics

Human subjects: The UK Biobank recruited 502 639 participants aged 37-70 years in 22 assessment centres across the UK. All participants provided written informed consent and ethical approval was obtained from the North West Multi-Center Research Ethics Committee. Details of the design of the UK Biobank have been reported previously (Sudlow et al PLOS Medicine 2015). The current analysis was approved under UK Biobank Project 30418.

Copyright

© 2021, Julkunen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Nightingale Health UK Biobank Initiative
  2. Heli Julkunen
  3. Anna Cichońska
  4. P Eline Slagboom
  5. Peter Würtz
(2021)
Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population
eLife 10:e63033.
https://doi.org/10.7554/eLife.63033

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https://doi.org/10.7554/eLife.63033

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