Exploration of interethnic variation in the ibuprofen metabolizing enzyme CYP2C9: a genetic-based cautionary guide for treatment of COVID-19 symptoms

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Abstract

Coronavirus disease 2019 (COVID-19), is a rapidly spreading infectious illness that causes a debilitating respiratory syndrome. While non-steroidal anti-inflammatory drugs (NSAIDs), may be prescribed for the management of pain and fever, there was early controversy on the use of ibuprofen for symptomatic treatment of COVID-19. P450 enzyme CYP2C9 are known to be involved in the metabolism of NSAIDs. Although no study has been conducted in the setting of population genetics in patients with COVID-19 yet, there are plausible mechanisms by which genetic determinants may play a role in adverse drug reactions (ADRs). In this work, we adjusted expected phenotype frequencies based on racial demographic models dependent on population ancestry in drug responses and toxicity events associated with ibuprofen treatment. A cohort of 101 Jordanian Arab samples retrospectively were selected and genotyped using Affymetrix DMET Plus Premier Package, within the context of over 100,000 global subjects in 417 published reports. European populations are 7.2x more likely to show impaired ibuprofen metabolism than Sub-Saharan populations, and 4.5x more likely than East Asian ancestry populations. Hence, a proactive assessment of the most likely gene-drug candidates will lead to more effective treatments and a better understanding of the role of pharmacogenetics for COVID-19.

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  1. SciScore for 10.1101/2021.01.09.21249508: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: After a signed informed consent, a 3ml venous blood sample was collected in 3ml EDTA tubes from each participant at the Princess Haya Biotechnology Centre between May 2010 and December 2011.
    IRB: The Institutional Review Board (IRB) of the Jordan University of Science and Technology approved this study on 4/7/2013 under registration number 67/2/2013.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableSample collection: This study retrospectively included 101 unrelated Jordanian participants, of which 54 were male and 47 were female.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical and genetic analyses were performed for selection and validation using Microsoft Excel and SPSS v16.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    The statistical comparison of allele frequencies on experimental data and reference populations were performed by Pearson’s χ2 test with Bonferroni correction and the negative logarithm of the adjusted significance values [-log10 (adj.p.val)] using the R statistical package v3.6.2 with ggplot2 and visualized using Rstudio v1.3.1056 (Boston, MA).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Rstudio
    suggested: (RStudio, RRID:SCR_000432)
    In order to detect the homologous sequences, which likely result in false-positive or false-negative variant calls, sequence similarity searches were performed using the Ensembl BLAST/BLAT search programs with default parameters.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Cryptic population structure was inferred using CYP2C9 SNP data to identify the ancestral relatedness between the Jordanian Arab population and three defined datasets: 1,810 individuals from 22 populations from the 1000 Genomes Project Phase III (1kG-p3) dataset, excluding admixed populations (Table S2); 3,413 individuals from 18 global reports (Table S3); and 31,880 individuals from 118 reports from the European (EUR) and Near Eastern (NEA) populations from the CPIC updated report in March 2020.
    1000 Genomes Project
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)

    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.

  2. SciScore for 10.1101/2021.01.09.21249508: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementAfter a signed informed consent, a 3ml venous blood sample was collected in 3ml EDTA tubes from each participant at the Princess Haya Biotechnology Centre between May 2010 and December 2011.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableMETHODS Sample collection This study retrospectively included 101 unrelated Jordanian participants, of which 54 were male and 47 were female.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical and genetic analyses were performed for selection and validation using Microsoft Excel and SPSS v16.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    The statistical comparison of allele frequencies on experimental data and reference populations were performed by Pearson's χ2 test with Bonferroni correction and the negative logarithm of the adjusted significance values [-log10 (adj.p.val)] using the R statistical package v3.6.2 with ggplot2 and visualized using Rstudio v1.3.1056 (Boston, MA).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Rstudio
    suggested: (RStudio, RRID:SCR_000432)
    In order to detect the homologous sequences, which likely result in false-positive or false-negative variant calls, sequence similarity searches were performed using the Ensembl BLAST/BLAT search programs with default parameters.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Cryptic population structure was inferred using CYP2C9 SNP data to identify the ancestral relatedness between the Jordanian Arab population and three defined datasets: 1,810 individuals from 22 populations from the 1000 Genomes Project Phase III (1kG-p3) dataset, excluding admixed populations (Table S2); 3,413 individuals from 18 global reports (Table S3); and 31,880 individuals from 118 reports from the European (EUR) and Near Eastern (NEA) populations from the CPIC updated report in March 2020.
    1000 Genomes Project
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)

    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.


    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.