Multi-ancestry Mendelian randomization of omics traits revealing drug targets of COVID-19 severity

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Abstract

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  1. SciScore for 10.1101/2020.05.07.20093286: (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
    10 of these 11 drugs were mapped to their target genes using Drug-Gene-Interaction (DGI) database (http://dgidb.org/) (23) and CHEMBL database (21) (Supplementary Table 1); ii) 332 human proteins interacting with SARS-CoV-2 proteins from Gordon et al. (8); iii) 44 genes associated with SARS-CoV from Gralinski et al. (9).
    CHEMBL
    suggested: (ChEMBL, RRID:SCR_014042)
    ChEMBL and/or Drugbank databases.
    Drugbank
    suggested: (DrugBank, RRID:SCR_002700)
    , ChEMBL, Drugbank and/or ClinicalTrial.gov.
    ClinicalTrial.gov
    suggested: ( Lifestyle Interventions for Expectant Moms (LIFE-Moms , RRID:SCR_014376)

    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: We detected the following sentences addressing limitations in the study:
    Some limitations of our analysis are worth noting. Whilst initiatives are underway to collect genetic information for COVID-19 patients (e.g. the COVID-19 host genetics initiative, https://covid-19genehostinitiative.net/) and in the UK Biobank (42), no such GWAS of COVID-19 phenotypes has yet been performed. Our evaluation of potential targets therefore excludes estimated effects of these targets on COVID-19 disease risk or progression. In the near future such data is likely to become available in a number of large-scale population-based biobanks across the world, including the UK Biobank, China Kadoorie Biobank (43), HUNT study (44), FinnGen (https://www.finngen.fi/fi), DeCODE (https://www.decode.com/) and the Million Veteran Program (45). These biobanks are designed to study long-term health conditions, but with data linkage between these biobanks and electronic health records and/or COVID-19 data (as has recently happened with UK Biobank), these biobanks could be tremendous resources to rapidly generate genetic association data in epidemic and pandemic situations. The recent initial GWAS of COVID-19 found no GWAS hits, which highlight the importance of seriously considering potential bias of the data. When the unbiased data are available, the drug target information and the genetic predictors of the 353 drug targets we curated in this study as well as the drug target prioritization pipeline could provide even more valuable insights into the potential drug targets for infec...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04320277Not yet recruitingBaricitinib in Symptomatic Patients Infected by COVID-19: an…


    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

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