Low Baseline Pulmonary Levels of Cytotoxic Lymphocytes as a Predisposing Risk Factor for Severe COVID-19

  1. Pascal H. G. Duijf

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Abstract

COVID-19 is caused by the highly contagious coronavirus SARS-CoV-2 and currently has detrimental human health, community, and economic impacts around the world. It is unclear why some SARS-CoV-2-positive individuals develop severe COVID-19 symptoms, which can be fatal, while others only develop mild symptoms. In the absence of an effective and widely available vaccine, it is of paramount importance that we identify risk factors for development of severe symptoms to be able to improve treatment approaches. The ACE2 gene encodes the receptor on human cells that the virus uses to infect these cells. This study finds that if the lungs of healthy individuals have high levels of ACE2, they typically have low levels of the immune cells that eliminate viruses. Therefore, some individuals may develop severe COVID-19 due to simultaneous high levels of the virus receptor and low levels of immune cells that eradicate the virus in their lungs.

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  1. Version published to 10.1128/msystems.00741-20
  2. Version published to 10.1101/2020.05.04.075291v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.05.04.075291: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    These were based on immunohistochemical staining of the tissues using DAB (3,3’-diaminobenzidine)-labeled antibodies (HPA000288, CAB026174), followed by knowledge-based annotation, as described on said website.
    CAB026174
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    These represent fold increase in expression in Calu-3 lung cells, 24 hours after infection with SARS-CoV-2 at a multiplicity of infection of 2, compared to uninfected Calu-3 cells.
    Calu-3
    suggested: KCLB Cat# 30055, RRID:CVCL_0609)
    Software and Algorithms
    SentencesResources
    Gene expression levels were obtained using RNA-SeQC v1.1.9 (51) and expressed in transcripts per million (TPM).
    RNA-SeQC
    suggested: (RNA-SeQC, RRID:SCR_005120)
    This dataset was accessed via Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo), accession number GSE23546, and was previously described (52).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    All analyses were performed in the R computing environment (R Project for Statistical Computing, Vienna, Austria).
    R Project for Statistical
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    First, mRNA expression levels from 40 human tissues were obtained from the Human Protein Atlas (https://www.proteinatlas.org).
    https://www.proteinatlas.org
    suggested: (HPA, RRID:SCR_006710)

    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.

  4. Version published to 10.1101/2020.05.04.075291v1 on bioRxiv