Genetic risk factors for death with SARS-CoV-2 from the UK Biobank

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Abstract

We present here genetic risk factors for survivability from infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for coronavirus disease 19 (COVID-19). At the time of writing it is too early to determine comprehensively and without doubt all risk factors, but there is an urgency due to the global pandemic crisis that merits this early analysis. We have nonetheless discovered 5 novel risk variants in 4 genes, discovered by examining 193 deaths from 1,412 confirmed infections in a group of 5,871 UK Biobank participants tested for the virus. We also examine the distribution of these genetic variants across broad ethnic groups and compare it to data from the UK Office of National Statistics for increased risk of death from SARS-CoV-2. We confidently identify the gene ERAP2 with a high-risk variant, as well as three other genes of potential interest. Although mostly rare, a common theme of genetic risk factors affecting survival might be the inability to launch or modulate an effective immune and stress response to infection from the SARS-CoV-2 virus.

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  1. SciScore for 10.1101/2020.07.01.20144592: (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
    These were subjected to data quality Control using Plink software 46.
    Plink
    suggested: (PLINK, RRID:SCR_001757)
    From the predicted phenotypes in the UK Biobank cohort participants who were tested for SARS-CoV- 2, potentially causal genes were obtained from the ontology via the dcGO mapping, comprising of: ALOXE3, BRF2, ERAP2, MPP5, RAMP3, RBL1 and TMEM181.
    dcGO
    suggested: (dcGO, RRID:SCR_014392)
    Independently of this, we used a separate list of potentially causal genes that was created by the UniProt 50 database team, and annotated by them as SARS-CoV-2 receptors comprising: ACE2, BSG, BST2, FURIN, IL6, IL6R, IL6ST, ITGAL,
    UniProt
    suggested: (UniProtKB, RRID:SCR_004426)

    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 pages 6 and 14. 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. SciScore for 10.1101/2020.07.01.20144592: (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 variableWe also observed that all 5 of the deaths in people with this variant were in men who self-reported as having hypertension; of the 6 survivors 4 are female and 2 male ( one with hypertension) .

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    These were subjected to data quality Control using Plink software 46 .
    Plink
    suggested: (PLINK, SCR_001757)
    We used a method of phenotype prediction 49 which combines ontologies from dcGO and the same principles of HMM dirichlet mixtures as used by FATHMM , against a genetic background from the 1000 genomes project .
    dcGO
    suggested: (dcGO, SCR_014392)
    Independently of this , we used a separate list of potentially causal genes that was created by the UniProt 50 database team , and annotated by them as SARS-CoV-2 receptors comprising: ACE2 , BSG , BST2 , FURIN , IL6 , IL6R , IL6ST , ITGAL ,
    UniProt
    suggested: (UniProtKB, SCR_004426)

    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 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.