ACE2 polymorphisms as potential players in COVID-19 outcome

  1. André Salim Khayat
  2. Paulo Pimentel de Assumpção
  3. Bruna Claudia Meireles Khayat
  4. Taíssa Maíra Thomaz Araújo
  5. Jéssica Almeida Batista-Gomes
  6. Luciana Carvalho Imbiriba
  7. Geraldo Ishak
  8. Paula Baraúna de Assumpção
  9. Fabiano Cordeiro Moreira
  10. Rommel Rodriguez Burbano
  11. André Ribeiro-dos-Santos
  12. Ândrea Kelly Ribeiro-dos-Santos
  13. Ney Pereira Carneiro dos Santos
  14. Sidney Emmanuel Batista dos Santos

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The clinical condition COVID-19, caused by SARS-CoV-2, was declared a pandemic by the WHO in March 2020. Currently, there are more than 5 million cases worldwide, and the pandemic has increased exponentially in many countries, with different incidences and death rates among regions/ethnicities and, intriguingly, between sexes. In addition to the many factors that can influence these discrepancies, we suggest a biological aspect, the genetic variation at the viral S protein receptor in human cells, ACE2 (angiotensin I-converting enzyme 2), which may contribute to the worse clinical outcome in males and in some regions worldwide. We performed exomics analysis in native and admixed South American populations, and we also conducted in silico genomics databank investigations in populations from other continents. Interestingly, at least ten polymorphisms in coding, noncoding and regulatory sites were found that can shed light on this issue and offer a plausible biological explanation for these epidemiological differences. In conclusion, there are ACE2 polymorphisms that could influence epidemiological discrepancies observed among ancestry and, moreover, between sexes.

Article activity feed

  1. Version published to 10.1371/journal.pone.0243887
  2. ScreenIT

    SciScore for 10.1101/2020.05.27.20114843: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the National Committee for Ethics in Research (CONEP) and the Research Ethics Committee of the UFPA Tropical Medicine Center under CAAE number 20654313.6.0000.5172.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses in the 1000 Genomes Project: The analysis was performed on data from the 1000 Genomes Phase 3 database (1000G), which comprises 84,4 million variants in 2,504 individuals from 26 different populations [18].
    1000 Genomes Project
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)
    Analyses in Amazon Natives and Admixed Population: For the allelic comparison between the populations cataloged in the 1000 Genomes database and the population not described in the respective project, we investigated a population composed of 64 Amerindians and 82 admixed individuals from the Amazon region of northern Brazil.
    1000 Genomes
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)
    Furthermore, we also compared our findings to a database of variants analyzed in a Southeast Brazilian population, the Online Archive of Brazilian Mutations (ABraOM, we represent here as ABM) [20].
    Online Archive
    suggested: None
    Exomic Bioinformatics: The quality of the FASTQ reads was analyzed (FastQC v.
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    0.13 – http://hannonlab.cshl.edu/fastx_toolkit/).
    http://hannonlab.cshl.edu/fastx_toolkit/
    suggested: (FASTX-Toolkit, RRID:SCR_005534)
    The sequences were aligned with the reference genome (GRCh37) using the BWA v.
    BWA
    suggested: (BWA, RRID:SCR_010910)
    The file was indexed and sorted (SAMtools v.
    SAMtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    1.129 – http://broadinstitute.github.io/picard/), and mapping quality recalibration and local realignment (GATK v.
    http://broadinstitute.github.io/picard/
    suggested: (Picard, RRID:SCR_006525)
    The results were processed to determine the variants (GATK v.3.2) from the reference genome.
    GATK
    suggested: (GATK, RRID:SCR_001876)
    SnpEff v.
    SnpEff
    suggested: (SnpEff, RRID:SCR_005191)
    , Ensembl Variant Effect Predictor (Ensembl release 99) and ClinVar (v.2018–10) were used for variant annotations.
    Ensembl Variant Effect Predictor
    suggested: None
    Variant
    suggested: (VARIANT, RRID:SCR_005194)
    ClinVar
    suggested: (ClinVar, RRID:SCR_006169)

    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.

  3. Version published to 10.1101/2020.05.27.20114843v1 on medRxiv