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Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications

Author

Listed:
  • Maryam A. Y. Al-Nesf

    (Hamad General Hospital, Hamad Medical Corporation
    Royal Free Campus, University College London)

  • Houari B. Abdesselem

    (Hamad Bin Khalifa University, Qatar Foundation)

  • Ilham Bensmail

    (Hamad Bin Khalifa University, Qatar Foundation)

  • Shahd Ibrahim

    (Hamad General Hospital, Hamad Medical Corporation)

  • Walaa A. H. Saeed

    (Hamad General Hospital, Hamad Medical Corporation)

  • Sara S. I. Mohammed

    (Hamad General Hospital, Hamad Medical Corporation)

  • Almurtada Razok

    (Hamad General Hospital, Hamad Medical Corporation)

  • Hashim Alhussain

    (Qatar University)

  • Reham M. A. Aly

    (Qatar University)

  • Muna Al Maslamani

    (Hamad Medical Corporation)

  • Khalid Ouararhni

    (Hamad Bin Khalifa University, Qatar Foundation)

  • Mohamad Y. Khatib

    (Hezm Mebairek General Hospital, Hamad Medical Corporation)

  • Ali Ait Hssain

    (Hamad General Hospital, Hamad Medical Corporation)

  • Ali S. Omrani

    (Hamad Medical Corporation)

  • Saad Al-Kaabi

    (Hamad General Hospital, Hamad Medical Corporation)

  • Abdullatif Al Khal

    (Hamad Medical Corporation)

  • Asmaa A. Al-Thani

    (Qatar University)

  • Waseem Samsam

    (Anti-Doping Laboratory Qatar)

  • Abdulaziz Farooq

    (Aspetar Hospital, Orthopaedic and Sports Medicine Hospital, FIFA Medical Centre of Excellence)

  • Jassim Al-Suwaidi

    (Hamad General Hospital, Hamad Medical Corporation)

  • Mohammed Al-Maadheed

    (Royal Free Campus, University College London
    Anti-Doping Laboratory Qatar)

  • Heba H. Al-Siddiqi

    (Hamad Bin Khalifa University, Qatar Foundation)

  • Alexandra E. Butler

    (Hamad Bin Khalifa University, Qatar Foundation
    Royal College of Surgeons of Ireland in Bahrain)

  • Julie V. Decock

    (Hamad Bin Khalifa University, Qatar Foundation
    Hamad Bin Khalifa University, Qatar Foundation)

  • Vidya Mohamed-Ali

    (Royal Free Campus, University College London
    Anti-Doping Laboratory Qatar)

  • Fares Al-Ejeh

    (Hamad Bin Khalifa University, Qatar Foundation
    Hamad Bin Khalifa University, Qatar Foundation
    University of Queensland)

Abstract

COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy controls, and show that 375 proteins are differentially expressed in the plasma of severe COVID-19 patients. These differentially expressed plasma proteins are implicated in the pathogenesis of COVID-19 and present targets for candidate drugs to prevent or treat severe complications. Based on the plasma proteomics and clinical lab tests, we also report a 12-plasma protein signature and a model of seven routine clinical tests that validate in an independent cohort as early risk predictors of COVID-19 severity and patient survival. The risk predictors and candidate drugs described in our study can be used and developed for personalized management of SARS-CoV-2 infected patients.

Suggested Citation

  • Maryam A. Y. Al-Nesf & Houari B. Abdesselem & Ilham Bensmail & Shahd Ibrahim & Walaa A. H. Saeed & Sara S. I. Mohammed & Almurtada Razok & Hashim Alhussain & Reham M. A. Aly & Muna Al Maslamani & Khal, 2022. "Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28639-4
    DOI: 10.1038/s41467-022-28639-4
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    References listed on IDEAS

    as
    1. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
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