Variants in ACE2 and TMPRSS2 genes are not major determinants of COVID-19 severity in UK Biobank subjects

  1. David Curtis

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Abstract

It is plausible that variants in the ACE2 and TMPRSS2 genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects of whom 74 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in ACE2 or TMPRSS2 . There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not a major determinant of whether infection with SARS-CoV-2 results in severe symptoms. This research has been conducted using the UK Biobank Resource.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.01.20085860: (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
    All variants were annotated using VEP, PolyPhen and SIFT (Adzhubei et al., 2013; Kumar et al., 2009; McLaren et al., 2016).
    SIFT
    suggested: (SIFT, RRID:SCR_012813)
    Additionally, 10 was added to the weight if the PolyPhen annotation was possibly or probably damaging and also if the SIFT annotation was deleterious, meaning that a non-synonymous variant annotated as both damaging and deleterious would be assigned an overall weight of 30.
    PolyPhen
    suggested: None

    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: 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 10.1101/2020.05.01.20085860v3 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.05.01.20085860: (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
    All variants were annotated using VEP, PolyPhen and SIFT (Adzhubei et al., 2013; Kumar et al., 2009; McLaren et al., 2016).
    PolyPhen
    suggested: None
          <div style="margin-bottom:8px">
        <div><b>SIFT</b></div>
        <div>suggested: (SIFT, <a href="https://scicrunch.org/resources/Any/search?q=SCR_012813">SCR_012813</a>)</div>
      </div>
    </td></tr></table>

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.05.01.20085860v2 on medRxiv
  5. Version published to 10.1101/2020.05.01.20085860v1 on medRxiv
  6. Version published to 10.1159/000515200