The metabolic fingerprint of COVID-19 severity

  1. Tim Dierckx
  2. Jan van Elslande
  3. Heli Salmela
  4. Bram Decru
  5. Els Wauters
  6. Jan Gunst
  7. Yannick Van Herck
  8. the CONTAGIOUS-consortium
  9. Joost Wauters
  10. Björn Stessel
  11. Pieter Vermeersch

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Abstract

Corona virus disease 2019 (COVID-19) has been associated with a wide range of divergent pathologies, and risk of severe disease is reported to be increased by a similarly broad range of co-morbidities. The present study investigated blood metabolites in order to elucidate how infection with severe acute respiratory syndrome coronavirus 2 can lead to such a variety of pathologies and what common ground they share. COVID-19 patient blood samples were taken at hospital admission in two Belgian patient cohorts, and a third cohort that included longitudinal samples was used for additional validation (total n=581). A total of 251 blood metabolite measures and ratios were assessed using nuclear magnetic resonance spectroscopy and tested for association to disease severity. In line with the varied effects of severe COVID-19, the range of severity-associated biomarkers was equally broad and included increased inflammatory markers (glycoprotein acetylation), amino acid concentrations (increased leucine and phenylalanine), increased lipoprotein particle concentrations (except those of very low density lipoprotein, VLDL), decreased cholesterol levels (except in large HDL and VLDL), increased triglyceride levels (only in IDL and LDL), fatty acid levels (decreased poly-unsaturated fatty acid, increased mono-unsaturated fatty acid) and decreased choline concentration, with association sizes comparable to those of routine clinical chemistry metrics of acute inflammation. Our results point to systemic metabolic biomarkers for COVID-19 severity that make strong targets for further fundamental research into its pathology (e.g. phenylalanine and omega-6 fatty acids).

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  1. ScreenIT

    SciScore for 10.1101/2020.11.09.20228221: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics: This study was approved by the Medical Ethical Committee of the University Hospitals of Leuven (MEC, UZ Leuven, s64161 and s63881) and the ethical approval committee of the Jessa hospital (20.75-20.05).
    Consent: Samples from UZL and Jessa cohorts were collected retrospectively, while the CONTAGIOUS cohort study is a prospective observational trial for which informed consent was obtained for all participants (clinicaltrials.gov identifier NCT04327570).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    We point out several strengths and limitations of our study. The studied populations had significant differences in demographics and clinical characteristics, and differences in sample type (serum vs plasma) between our two largest cohorts discourage the merging of their experimental results, even after accounting for the batch effects introduced by differences in sample handling between the different cohorts. However, this does lend a high degree of confidence to the results that were consistently observed in all three cohorts. Availability of longitudinal follow-up samples was limited to the CONTAGIOUS cohort of patients with severe infection. It is worth noting that, to our knowledge, this is the first study using 1H NMR metabolomics in severe viral infection. As such, without comparable results from studies on other infections, we cannot attribute the results reported in this study exclusively to SARS-CoV-2 infection. We suspect that e.g. a study into the metabolic associations of severe pneumonia could yield similar results, in light of the strength of the association of severity with the infectious disease multi-biomarker score from Julkunen et al38. Many of the associations to severity noted here could be interpreted as general signs of inflammation and robust correlation network analysis on paired NMR metabolomics, cytokine quantification and transcriptomics, while contrasting severe COVID-19 to severe (viral) pneumonia without SARS-CoV-2 infection, would allow for a ...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04327570RecruitingIn-depth Immunological Investigation of COVID-19.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.11.09.20228221v1 on medRxiv