Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profiling

  1. Ewan Hunter
  2. Christina Koutsothanasi
  3. Adam Wilson
  4. Francisco C. Santos
  5. Matthew Salter
  6. Jurjen W. Westra
  7. Ryan Powell
  8. Ann Dring
  9. Paulina Brajer
  10. Benedict Egan
  11. Matthew Parnall
  12. Catriona Williams
  13. Aemilia Katzinski
  14. Thomas Lavin
  15. Aroul Ramadass
  16. William Messer
  17. Amanda Brunton
  18. Zoe Lyski
  19. Rama Vancheeswaran
  20. Andrew Barlow
  21. Dmitri Pchejetski
  22. Peter A. Robbins
  23. Jane Mellor
  24. Alexandre Akoulitchev

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Abstract

The COVID-19 pandemic has raised several global public health challenges to which the international medical community have responded. Diagnostic testing and the development of vaccines against the SARS-CoV-2 virus have made remarkable progress to date. As the population is now faced with the complex lifestyle and medical decisions that come with living in a pandemic, a forward-looking understanding of how a COVID-19 diagnosis may affect the health of an individual represents a pressing need. Previously we used whole genome microarray to identify 200 3D genomic marker leads that could predict mild or severe COVID-19 disease outcomes from blood samples in a multinational cohort of COVID-19 patients. Here, we focus on the development and validation of a qPCR assay to accurately predict severe COVID-19 disease requiring intensive care unit (ICU) support and/or mechanical ventilation. From 200 original biomarker leads we established a classification model containing six markers. The markers were qualified and validated on 38 COVID-19 patients from an independent cohort. Overall, the six-marker model obtained a positive predictive value of 93% and balanced accuracy of 88% across 116 patients for the prognosis of COVID-19 severity requiring ICU care/ventilation support. The six-marker signature identifies individuals at the highest risk of developing severe complications in COVID-19 with high predictive accuracy and can assist in patient prognosis and clinical management decisions.

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    SciScore for 10.1101/2021.06.21.21259145: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Mapping was carried out using Bedtools closest function for the 3 closest protein coding loci (Gencode v33).
    Bedtools
    suggested: (BEDTools, RRID:SCR_006646)
    Gencode
    suggested: (GENCODE, RRID:SCR_014966)
    EpiSwitch® RankProd R library).
    RankProd
    suggested: (RankProd, RRID:SCR_013046)
    analysis: Pathway enrichment analysis was performed using the Reactome Pathway Browser [24]
    Reactome Pathway Browser
    suggested: None
    Protein interaction networks were generated using the Search Tool for the Retrieval of Interacting proteins (STRING) database [24, 25].
    STRING
    suggested: (STRING, RRID:SCR_005223)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.06.21.21259145v1 on medRxiv