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

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, Khalid Ouararhni, Mohamad Y. Khatib, Ali Ait Hssain, Ali S. Omrani, Saad Al-Kaabi, Abdullatif Al Khal, Asmaa A. Al-Thani, Waseem Samsam, Abdulaziz Farooq, Jassim Al-SuwaidiMohammed Al-Maadheed, Heba H. Al-Siddiqi, Alexandra E. Butler, Julie V. Decock, Vidya Mohamed-Ali, Fares Al-Ejeh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

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.Prognostic markers for patients with COVID-19 are of critical importance in determining the course of SARS-CoV-2 infection and patient handling. Here the authors determine and apply a prognostic proteomic panel for risk and drug prediction in the management of SARS-CoV-2 infected patients.
Original languageEnglish
Article number946
Number of pages14
JournalNature Communications
Volume13
Issue number1
DOIs
Publication statusPublished - 17 Feb 2022

Keywords

  • Expression
  • Il-6
  • Immunoglobulin
  • Receptor
  • T-cell responses

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