Differences in innate Intracellular viral suppression competencies may explain variations in morbidity and mortality from SARS-CoV-2 infection

  1. Shaibu Oricha Bello
  2. Ehimario Igumbor
  3. Yusuf Yahaya Deeni
  4. Chinwe Lucia Ochu
  5. Popoola Mustapha Ayodele

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

SARS-CoV-2 infection and COVID-19 ravage the world with wide variations in morbidity and mortality that have remained largely unexplained, even by mutations in protein coding regions. In this study, we analyzed available complete SARS-CoV-2 sequences using the CpG index as a signature of Zinc finger antiviral protein (ZAP) activity to examine population variations in innate intracellular antiviral competencies. The result suggests that differential ZAP activity may be a major determinant of the outcome of SARS-CoV-2 infection. SARS-CoV-2 sequences from Africa, Asia, and pools of asymptomatic patients had I_CpG signature evidence of high ZAP activity, while SARS-CoV-2 sequences from North America and Intensive Care Unit or Deceased patients had I_CpG signature of low ZAP activity. ZAP activity is linked to the interferon system. Low ZAP activity may be part of the explanation for the increased morbidity of SARS-CoV-2 in the elderly and with comorbidities like diabetes, obesity, and hypertension. It may also provide some insight into the discrepancies between invitro anti-SARS-CoV-2 activities of candidate therapies and performance in clinical trials. Furthermore, our results suggest that asymptomatic patients may paradoxically shed a more dangerous virus.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.09.13.20193524: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Sequences from GISAID were then matched to patient metadata on Microsoft excel sheet using ‘sequences name’ and ‘virus name’ respectively.
    Microsoft excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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:
    The limitations of this study are that database bias, group size bias and over-interpretation may result in spurious findings. Nonetheless, this study provides an additional explanation to the confounding observations in a disease of certain uncertainties: COVID-19. Prospective studies will be required to provide further validation of our findings.

    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.

    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 10.1101/2020.09.13.20193524 on medRxiv