A genetic variant protective against severe COVID-19 is inherited from Neandertals

  1. Hugo Zeberg
  2. Svante Pääbo

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Abstract

It was recently shown that the major genetic risk factor associated with becoming severely ill with COVID-19 when infected by SARS-CoV-2 is inherited from Neandertals. Thanks to new genetic association studies additional risk factors are now being discovered. Using data from a recent genome-wide associations from the Genetics of Mortality in Critical Care (GenOMICC) consortium, we show that a haplotype at a region associated with requiring intensive care is inherited from Neandertals. It encodes proteins that activate enzymes that are important during infections with RNA viruses. As compared to the previously described Neandertal risk haplotype, this Neandertal haplotype is protective against severe COVID-19, is of more moderate effect, and is found at substantial frequencies in all regions of the world outside Africa.

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    SciScore for 10.1101/2020.10.05.327197: (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
    Linkage disequilibrium was calculated using LDlink 4.1 and alleles were compared to the archaic genomes using tabix (HTSlib 1.10).
    LDlink
    suggested: None
    The Neandertal haplotype covering the region was investigated using sites where the Neandertal allele is not present in 108 Yoruba individuals (1000G Genomes Project), and the distances between the first two SNPs which cause the LD to fall below 0.75 in Europeans was taken as the length of the Neandertal haplotype.
    1000G Genomes Project
    suggested: None
    The inferred ancestral states at variable positions among present-day humans were taken from Ensembl.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Maps displaying allele frequencies of different populations were made using Mathematica 11.0 (Wolfram Research, Inc., Champaign, IL) and OpenStreetMap data.
    Mathematica
    suggested: (Wolfram Mathematica, RRID:SCR_014448)

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.10.05.327197v3 on bioRxiv
  3. Version published to 10.1101/2020.10.05.327197v2 on bioRxiv
  4. Version published to 10.1101/2020.10.05.327197v1 on bioRxiv