Genetic variability in COVID-19-related genes in the Brazilian population

  1. Rodrigo Secolin
  2. Tânia K. de Araujo
  3. Marina C. Gonsales
  4. Cristiane S. Rocha
  5. Michel Naslavsky
  6. Luiz De Marco
  7. Maria A. C. Bicalho
  8. Vinicius L. Vazquez
  9. Mayana Zatz
  10. Wilson A. Silva
  11. Iscia Lopes-Cendes

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Abstract

SARS-CoV-2 utilizes the angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane serine protease (TMPRSS2) to infect human lung cells. Previous studies have suggested that different host ACE2 and TMPRSS2 genetic backgrounds might contribute to differences in the rate of SARS-CoV-2 infection or COVID-19 severity. Recent studies have also shown that variants in 15 genes related to type I interferon immunity to influenza virus might predispose patients toward life-threatening COVID-19 pneumonia. Other genes ( SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, IL6, CTSL , ABO , and FURIN ) and HLA alleles have also been implicated in the response to infection with SARS-CoV-2. Currently, Brazil has recorded the third-highest number of COVID-19 cases worldwide. We aimed to investigate the genetic variation present in COVID-19-related genes in the Brazilian population. We analyzed 27 candidate genes and HLA alleles in 954 admixed Brazilian exomes. We used the information available in two public databases ( http://www.bipmed.org and http://abraom.ib.usp.br/ ) and additional exomes from individuals born in southeast Brazil, the region of the country with the highest number of COVID-19 patients. Variant allele frequencies were compared with the 1000 Genomes Project phase 3 (1KGP) and gnomAD databases. We detected 395 nonsynonymous variants; of these, 325 were also found in the 1KGP and/or gnomAD. Six of these variants were previously reported to influence the rate of infection or clinical prognosis of COVID-19. The remaining 70 variants were identified exclusively in the Brazilian sample, with a mean allele frequency of 0.0025. In silico analysis revealed that seven of these variants are predicted to affect protein function. Furthermore, we identified HLA alleles previously associated with the COVID-19 response at loci DQB1 and DRB1 . Our results showed genetic variability common to other populations and rare and ultrarare variants exclusively found in the Brazilian population. These findings might lead to differences in the rate of infection or response to infection by SARS-CoV-2 and should be further investigated in patients with this disease.

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  1. Version published to 10.1038/s41439-021-00146-w
  2. ScreenIT

    SciScore for 10.1101/2020.12.04.411736: (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
    Gene regions were extracted by vcftools33 based on the position reported in Ensembl GRCh37 Release 10134 (Supplementary Table 1).
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Variant consequences were annotated from each gene region by ANNOVAR software (version 2019Oct24)35, using the following flags: -otherinfo (to include Brazil AF); -onetranscript; -buildver hg19; -remove; -protocol refGene,gnomad211_exome; ALL.sites.2015_08; EUR.sites.2015_08; AFR.sites.2015_08; AMR.sites.2015_08; EAS.sites.2015_08; SAS.sites.2015_08; -operation g,f; and -nastring.
    ANNOVAR
    suggested: (ANNOVAR, RRID:SCR_012821)
    In addition, we annotated variants which were not identified by ANNOVAR using Variant Effect Prediction (VEP) algorithm36, with the following parameters: --buffer_size 500; --canonical; --distance 5000; --species homo_sapiens; --symbol.
    Variant Effect Prediction
    suggested: None
    , Functional Analysis through Hidden Markov Models (FATHMM)46, SNPs&GO47, and MutPred2 (http://mutpred.mutdb.org).
    http://mutpred.mutdb.org
    suggested: (MutPred, RRID:SCR_010778)
    HLA allele frequencies were calculated by Arlequin v.
    Arlequin
    suggested: (ARLEQUIN, RRID:SCR_009051)
    HLA allele and haplotype frequencies of other populations: HLA frequency data were obtained from the Allele Frequency Net Database (http://www.allelefrequencies.net/) 56 for 10 distinct populations that are most and least affected by COVID-19.
    http://www.allelefrequencies.net/
    suggested: (Allele Frequencies in Worldwide Populations, RRID:SCR_007259)

    Results from OddPub: Thank you for sharing your data.

    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 10.1101/2020.12.04.411736v1 on bioRxiv