Cardiac SARS-CoV-2 infection is associated with pro-inflammatory transcriptomic alterations within the heart

  1. Hanna Bräuninger
  2. Bastian Stoffers
  3. Antonia D E Fitzek
  4. Kira Meißner
  5. Ganna Aleshcheva
  6. Michaela Schweizer
  7. Jessica Weimann
  8. Björn Rotter
  9. Svenja Warnke
  10. Carolin Edler
  11. Fabian Braun
  12. Kevin Roedl
  13. Katharina Scherschel
  14. Felicitas Escher
  15. Stefan Kluge
  16. Tobias B Huber
  17. Benjamin Ondruschka
  18. Heinz-Peter Schultheiss
  19. Paulus Kirchhof
  20. Stefan Blankenberg
  21. Klaus Püschel
  22. Dirk Westermann
  23. Diana Lindner

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Abstract

Aims

Cardiac involvement in COVID-19 is associated with adverse outcome. However, it is unclear whether cell-specific consequences are associated with cardiac SARS-CoV-2 infection. Therefore, we investigated heart tissue utilizing in situ hybridization, immunohistochemistry, and RNA-sequencing in consecutive autopsy cases to quantify virus load and characterize cardiac involvement in COVID-19.

Methods and results

In this study, 95 SARS-CoV-2-positive autopsy cases were included. A relevant SARS-CoV-2 virus load in the cardiac tissue was detected in 41/95 deceased (43%). Massive analysis of cDNA ends (MACE)-RNA-sequencing was performed to identify molecular pathomechanisms caused by the infection of the heart. A signature matrix was generated based on the single-cell dataset ‘Heart Cell Atlas’ and used for digital cytometry on the MACE-RNA-sequencing data. Thus, immune cell fractions were estimated and revealed no difference in immune cell numbers in cases with and without cardiac infection. This result was confirmed by quantitative immunohistological diagnosis. MACE-RNA-sequencing revealed 19 differentially expressed genes (DEGs) with a q-value <0.05 (e.g. up: IFI44L, IFT3, TRIM25; down: NPPB, MB, MYPN). The upregulated DEGs were linked to interferon pathways and originate predominantly from endothelial cells. In contrast, the downregulated DEGs originate predominately from cardiomyocytes. Immunofluorescent staining showed viral protein in cells positive for the endothelial marker ICAM1 but rarely in cardiomyocytes. The Gene Ontology (GO) term analysis revealed that downregulated GO terms were linked to cardiomyocyte structure, whereas upregulated GO terms were linked to anti-virus immune response.

Conclusion

This study reveals that cardiac infection induced transcriptomic alterations mainly linked to immune response and destruction of cardiomyocytes. While endothelial cells are primarily targeted by the virus, we suggest cardiomyocyte destruction by paracrine effects. Increased pro-inflammatory gene expression was detected in SARS-CoV-2-infected cardiac tissue but no increased SARS-CoV-2 associated immune cell infiltration was observed.

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  1. Version published to 10.1093/cvr/cvab322
  2. ScreenIT

    SciScore for 10.1101/2020.12.19.20248542: (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 local ethics committee of the Hamburg Chamber of Physicians (PV7311).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The reads were mapped to the human genome (hg38) and transcripts were quantified by HTSeq.
    HTSeq
    suggested: (HTSeq, RRID:SCR_005514)
    Differential gene expression was calculated using DESeq223 and plotted using Graph Pad Prism (GraphPad Software, USA).
    Graph Pad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    ) tool ComplexHeatmap was used.24 3.7 Gene Ontology Enrichment Analysis:
    ComplexHeatmap
    suggested: (ComplexHeatmap, RRID:SCR_017270)
    Gene Ontology (GO) annotation data are based on ENSEMBL.
    ENSEMBL
    suggested: (Ensembl, RRID:SCR_002344)
    GO enrichment analysis was performed using the topGO package (bioconductor)
    topGO
    suggested: (topGO, RRID:SCR_014798)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04321096Active, not recruitingThe Impact of Camostat Mesilate on COVID-19 Infection
    NCT04338906WithdrawnCombination Therapy With Camostat Mesilate + Hydroxychloroqu…

    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 10.1101/2020.12.19.20248542v1 on medRxiv