Hypertension delays viral clearance and exacerbates airway hyperinflammation in patients with COVID-19

  1. Saskia Trump
  2. Soeren Lukassen
  3. Markus S. Anker
  4. Robert Lorenz Chua
  5. Johannes Liebig
  6. Loreen Thürmann
  7. Victor Max Corman
  8. Marco Binder
  9. Jennifer Loske
  10. Christina Klasa
  11. Teresa Krieger
  12. Bianca P. Hennig
  13. Marey Messingschlager
  14. Fabian Pott
  15. Julia Kazmierski
  16. Sven Twardziok
  17. Jan Philipp Albrecht
  18. Jürgen Eils
  19. Sara Hadzibegovic
  20. Alessia Lena
  21. Bettina Heidecker
  22. Thore Bürgel
  23. Jakob Steinfeldt
  24. Christine Goffinet
  25. Florian Kurth
  26. Martin Witzenrath
  27. Maria Theresa Völker
  28. Sarah Dorothea Müller
  29. Uwe Gerd Liebert
  30. Naveed Ishaque
  31. Lars Kaderali
  32. Leif-Erik Sander
  33. Christian Drosten
  34. Sven Laudi
  35. Roland Eils
  36. Christian Conrad
  37. Ulf Landmesser
  38. Irina Lehmann

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.09.22.20199471: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Written informed consent was given by all patients or their legal representatives.
    IRB: The study was approved by the respective Institutional Review boards of the Charité-Universitätsmedizin Berlin (EA2/066/20) or the University Hospital Leipzig (123/20-ek) and conducted in accordance with the Declaration of Helsinki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableSingle-cell RNA sequencing cohort: We collected nasopharyngeal swabs for single-cell RNA transcriptome analyses (scRNA-seq) of 32 confirmed COVID-19 patients (23 males and nine females; median age: 67; range: 32–91 years of age) and 16 controls without any COVID-19 related symptoms (nine males, seven females; median age: 53; range: 24-79).
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Identification of RIG-I and type I/III interferon responsive gene sets: A549 cells were electrotransfected with 400bp long in vitro transcribed dsRNA48 and lysed at 2, 4, 6, 8, 16 and 24h after transfection, or mock electrotransfected and lysed at 2 and 24h.
    A549
    suggested: None
    Software and Algorithms
    SentencesResources
    The “viral responsive” cell states of ciliated and squamous epithelial cells (Extended Data Figure 1b) were identified by gene set enrichment analysis using clusterProfiler version 3.12.0 and the output of “FindClusters()” function from Seurat as input (https://yulab-smu.github.io/clusterProfiler-book/index.html)43.
    clusterProfiler
    suggested: (clusterProfiler, RRID:SCR_016884)
    For cell-cell interactions, which are based on the expression of known ligand-receptor pairs in different identified cell types, CellPhoneDB21 version 2.1.2 was used (https://github.com/Teichlab/cellphonedb). circlize 0.4.10 was used to generate the circos plots to display the cell-cell interactions44.
    CellPhoneDB21
    suggested: None
    circos
    suggested: (Circos, RRID:SCR_011798)
    Calculations were performed in SPSS version 25 and predicted means calculated using the maximum likelihood option.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Expression data was quantile normalized, genes with no significant expression at any condition / time point were excluded and gene regulation at different treatment time points vs. the 0h control was determined using the limma package (Bioconductor).
    limma
    suggested: (LIMMA, RRID:SCR_010943)
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    Differences in gene expression were calculated using “FindMarkers()” in Seurat version 3.1.4 with the MAST-based differential expression test adjusted for days post symptoms onset (dps).
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    Motif enrichment p-values were calculated using HOMER 4.10.050.
    HOMER
    suggested: (HOMER, RRID:SCR_010881)

    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. Version published to 10.1038/s41587-020-00796-1
  3. Version published to 10.1101/2020.09.22.20199471 on medRxiv