A comprehensive germline variant and expression analyses of ACE2 , TMPRSS2 and SARS-CoV-2 activator FURIN genes from the Middle East: Combating SARS-CoV-2 with precision medicine

  1. Fahd Al-Mulla
  2. Anwar Mohammad
  3. Ashraf Al Madhoun
  4. Dania Haddad
  5. Hamad Ali
  6. Muthukrishnan Eaaswarkhanth
  7. Sumi Elsa John
  8. Rasheeba Nizam
  9. Arshad Channanath
  10. Mohamed Abu-Farha
  11. Rasheed Ahmad
  12. Jehad Abubaker
  13. Thangavel Alphonse Thanaraj

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

The severity of the new COVID-19 pandemic caused by the SARS-CoV-2 virus is strikingly variable in different global populations. SARS-CoV-2 uses ACE2 as a cell receptor, TMPRSS2 protease, and FURIN peptidase to invade human cells. Here, we investigated 1,378 whole-exome sequences of individuals from the Middle Eastern populations (Kuwait, Qatar, and Iran) to explore natural variations in the ACE2 , TMPRSS2, and FURIN genes. We identified two activating variants (K26R and N720D) in the ACE2 gene that are more common in Europeans than in the Middle Eastern, East Asian, and African populations. We postulate that K26R can activate ACE2 and facilitate binding to S-protein RBD while N720D enhances TMPRSS2 cutting and, ultimately, viral entry. We also detected deleterious variants in FURIN that are frequent in the Middle Eastern but not in the European populations. This study highlights specific genetic variations in the ACE2 and FURIN genes that may explain SARS-CoV-2 clinical disparity. We showed structural evidence of the functionality of these activating variants that increase the SARS-CoV-2 aggressiveness. Finally, our data illustrate a significant correlation between ACE2 variants identified in people from Middle Eastern origins that can be further explored to explain the variation in COVID-19 infection and mortality rates globally.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.16.099176: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The genetic data of non-Finnish European, East Asian and African American populations were obtained from the gnomAD repository 41, which contain data on a total of 125,748 exomes and 71,702 genomes (https://gnomad.broadinstitute.org/).
    https://gnomad.broadinstitute.org/
    suggested: (Genome Aggregation Database, RRID:SCR_014964)
    Statistical analysis: The missense variants were defined as deleterious when predicted to be damaging, probably damaging, disease causing and deleterious by the five algorithms applied, SIFT 50, PolyPhen-2 HumVar, PolyPhen-2 HumDiv 51, MutationTaster 52 and LRT score 53 and/or CADD (Combined Annotation-Dependent Depletion) score of more than 20 54.
    SIFT
    suggested: (SIFT, RRID:SCR_012813)
    PolyPhen-2
    suggested: None
    MutationTaster
    suggested: (MutationTaster, RRID:SCR_010777)
    The significance of the differences in MAFs between different populations was calculated using Chi-Square test, using the R software (https://www.r-project.org/).
    https://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Structural Analysis: All the identified ACE2 missense exon variants were mapped, modeled, and analyzed using Pymol modeling software (https://pymol.org/2/).
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)

    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: 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: Please consider improving the rainbow (“jet”) colormap(s) used on page 24. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.16.099176 on bioRxiv