SARS-CoV-2 genetic variations associated with COVID-19 pathogenicity

  1. Pakorn Aiewsakun
  2. Patrawee Nilplub
  3. Patompon Wongtrakoongate
  4. Suradej Hongeng
  5. Arunee Thitithanyanont

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Abstract

In this study, we performed genome-wide association analyses on SARS-CoV-2 genomes to identify genetic mutations associated with pre-symptomatic/asymptomatic COVID-19 cases. Various potential covariates and confounding factors of COVID-19 severity, including patient age, gender and country, as well as virus phylogenetic relatedness were adjusted for. In total, 3021 full-length genomes of SARS-CoV-2 generated from original clinical samples and whose patient status could be determined conclusively as either ‘pre-symptomatic/asymptomatic’ or ‘symptomatic’ were retrieved from the GISAID database. We found that the mutation 11 083G>T, located in the coding region of non-structural protein 6, is significantly associated with asymptomatic COVID-19. Patient age is positively correlated with symptomatic infection, while gender is not significantly correlated with the development of the disease. We also found that the effects of the mutation, patient age and gender do not vary significantly among countries, although each country appears to have varying baseline chances of COVID-19 symptom development.

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  1. Version published to 10.1099/mgen.0.000734 on Access Microbiology
  2. ScreenIT

    SciScore for 10.1101/2020.05.27.20114546: (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
    A maximum likelihood phylogeny was estimated from the prepared full-length alignment by using IQ-TREE [22].
    IQ-TREE
    suggested: (IQ-TREE, RRID:SCR_017254)
    The best-fit nucleotide substitution models was determined to be GTR+I+F under the Bayesian information criterion by using ModelFinder [23] and was used for the tree reconstruction.
    ModelFinder
    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.

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  3. Version published to 10.1101/2020.05.27.20114546v1 on medRxiv