Specific immune-regulatory transcriptional signatures reveal sex and age differences in SARS-CoV-2 infected patients

  1. Paula Paccielli Freire
  2. Alexandre H. C. Marques
  3. Gabriela Crispim Baiocchi
  4. Lena F. Schimke
  5. Dennyson Leandro M. Fonseca
  6. Ranieri Coelho Salgado
  7. Igor Salerno Filgueiras
  8. Sarah Maria da Silva Napoleao
  9. Desirée Rodrigues Plaça
  10. Thiago Dominguez Crespo Hirata
  11. Nadia El Khawanky
  12. Lasse Melvaer Giil
  13. Gustavo Cabral de Miranda
  14. Robson Francisco Carvalho
  15. Luis Carlos de Souza Ferreira
  16. Antonio Condino-Neto
  17. Helder Takashi Imoto Nakaya
  18. Igor Jurisica
  19. Hans D. Ochs
  20. Niels Olsen Saraiva Camara
  21. Vera Lúcia Garcia Calich
  22. Otavio Cabral-Marques

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Abstract

The coronavirus disease 2019 (COVID-19) fatality rate varies in different patient groups. However, the underlying mechanisms that explain this variation are poorly understood. Here, we reanalyzed and integrated public RNAseq datasets of nasopharyngeal swabs and peripheral blood leukocytes from patients with SARS-CoV-2, comparing transcription patterns according to sex, age, and viral load. We found that female and young patients infected by SARS-CoV-2 exhibited a similar transcriptomic pattern with a larger number of total (up- and downregulated) differentially expressed genes (DEGs) compared to males and elderly patients. The transcriptional analysis showed a sex-specific profile with a higher transcriptional modulation of immune response-associated genes in female and young subjects against SARS-CoV-2. The functional clustering was characterized by a highly correlated interferome network of cytokine/chemokine- and neutrophil-associated genes that were enriched both in nasopharyngeal cells and peripheral blood of COVID-19 patients. Females exhibited reduced transcriptional levels of key pro-inflammatory/neutrophil-related genes such as CXCL8 receptors ( CXCR1/CXCR2 ), IL-1β, S100A9, ITGAM , and DBNL compared to males, which correlate with a protective gene expression profile against inflammatory damage. Our data indicate specific immune-regulatory pathways associated with sex and age of patients infected with SARS-CoV-2. These results point out therapeutic targets to reduce morbidity and mortality of COVID-19.

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    SciScore for 10.1101/2020.11.12.20230417: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableAge (< 60 young and ≥ 60 elderly individuals), gender (male and female), and viral load (only for GSE152075) categorized as previously described19.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    SC2) (data accessible at NCBI GEO database60, accession number GSE GSE15207519 and GSE15606320).
    NCBI GEO
    suggested: None
    Read counts were transformed (log2 count per million or CPM), and differentially expressed transcripts between groups were identified through the webtool NetworkAnalyst 3.0 (https://www.networkanalyst.ca/)61 using limma-voom pipeline62.
    NetworkAnalyst
    suggested: (NetworkAnalyst, RRID:SCR_016909)
    Biological processes [Gene Ontology (GO)] were analyzed using EnrichR (available at http://amp.pharm.mssm.edu/Enrichr/)21,63, and the enriched immunological terms were generated according to adjusted p-value < 0.05 and Z-score (correction to the test) in a combined score provided by EnrichR database21,63.
    EnrichR
    suggested: (Enrichr, RRID:SCR_001575)
    We plotted the set of genes associated with CMSP (GO:0019221) and NMI (GO:0002446) in bubble-based heat maps with hierarchical clustering using web tool Morpheus (https://software.broadinstitute.org/morpheus/)64 with Euclidian distance metric.
    Morpheus
    suggested: (Morpheus, RRID:SCR_014975)
    GraphPad Prisma v.8 (GraphPad Software) was used to generate the violin plots.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    The UniProtKB database (available at http://www.uniprot.org/) was used to access the functional information.
    UniProtKB
    suggested: (UniProtKB, RRID:SCR_004426)
    http://www.uniprot.org/
    suggested: (Universal Protein Resource, RRID:SCR_002380)
    Shared CMSP and NMI genes among all groups were displayed using Circos Plot (http://circos.ca/).
    Circos
    suggested: (Circos, RRID:SCR_011798)
    Final network was exported in SVG format and finalized with legends in Adobe Illustrator.
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)
    Finally, all statistical graphs were constructed using the functionalities of the ggplot2 package74.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 34 and 36. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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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  2. Version published to 10.1101/2020.11.12.20230417v1 on medRxiv