Genetic risk factors and COVID-19 severity in Brazil: results from BRACOVID study

  1. Alexandre C Pereira
  2. Taniela M Bes
  3. Mariliza Velho
  4. Emanuelle Marques
  5. Cintia E Jannes
  6. Karina R Valino
  7. Carla L Dinardo
  8. Silvia F Costa
  9. Alberto J S Duarte
  10. Alexandre R Santos
  11. Miguel Mitne-Neto
  12. Jose Medina-Pestana
  13. Jose E Krieger

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Abstract

The coronavirus disease 2019 (COVID-19) pandemic has changed the paradigms for disease surveillance and rapid deployment of scientific-based evidence for understanding disease biology, susceptibility and treatment. We have organized a large-scale genome-wide association study (GWAS) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected individuals in Sao Paulo, Brazil, one of the most affected areas of the pandemic in the country, itself one of the most affected in the world. Here, we present the results of the initial analysis in the first 5233 participants of the BRACOVID study. We have conducted a GWAS for COVID-19 hospitalization enrolling 3533 cases (hospitalized COVID-19 participants) and 1700 controls (non-hospitalized COVID-19 participants). Models were adjusted by age, sex and the 4 first principal components. A meta-analysis was also conducted merging BRACOVID hospitalization data with the Human Genetic Initiative (HGI) Consortia results. BRACOVID results validated most loci previously identified in the HGI meta-analysis. In addition, no significant heterogeneity according to ancestral group within the Brazilian population was observed for the two most important COVID-19 severity associated loci: 3p21.31 and Chr21 near IFNAR2. Using only data provided by BRACOVID, a new genome-wide significant locus was identified on Chr1 near the genes DSTYK and RBBP5. The associated haplotype has also been previously associated with a number of blood cell related traits and might play a role in modulating the immune response in COVID-19 cases.

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  1. Version published to 10.1093/hmg/ddac045
  2. ScreenIT

    SciScore for 10.1101/2021.10.06.21264631: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: After signing an informed consent, a sample of whole-blood already collected for in-hospital biochemical analysis or SARS-CoV-2 serology was used for genomic DNA extraction.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    After imputation data were exported in the standard PLINK format, downstream QC procedures and statistical analysis were conducted using the latest PLINK (http://pngu.mgh.harvard.edu/_purcell/plink) and R software packages (http://www.r-project.org/), installed on a Linux based computation resource.
    http://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Local linkage disequilibrium structure was determined using Haploview (14).
    Haploview
    suggested: (Haploview, RRID:SCR_003076)

    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:
    The main limitation of this study is the lack of a suitable replication sample for the GWAS results. The observed genome-wide significant locus near DSTYK needs to be replicated in an independent sample to continue to be considered a modulator of Covid-19 severity. The continuous effort to increase the sample size of the BRACOVID study may allow the identification genome-wide significant loci with decreased effect size. Taken together, our analysis supports the hypothesis that the identified 79Kb haplotype on chromosome 1 may modulate Covid-19 relevant immunological traits through the gene expression of at least one of the genes with significant eQTLs in the region.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.10.06.21264631v1 on medRxiv