Macrophage expression and prognostic significance of the long pentraxin PTX3 in COVID-19

  1. Enrico Brunetta
  2. Marco Folci
  3. Barbara Bottazzi
  4. Maria De Santis
  5. Giuseppe Gritti
  6. Alessandro Protti
  7. Sarah N. Mapelli
  8. Stefanos Bonovas
  9. Daniele Piovani
  10. Roberto Leone
  11. Ilaria My
  12. Veronica Zanon
  13. Gianmarco Spata
  14. Monica Bacci
  15. Domenico Supino
  16. Silvia Carnevale
  17. Marina Sironi
  18. Sadaf Davoudian
  19. Clelia Peano
  20. Francesco Landi
  21. Fabiano Di Marco
  22. Federico Raimondi
  23. Andrea Gianatti
  24. Claudio Angelini
  25. Alessandro Rambaldi
  26. Cecilia Garlanda
  27. Michele Ciccarelli
  28. Maurizio Cecconi
  29. Alberto Mantovani

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.1038/s41590-020-00832-x
  2. ScreenIT

    SciScore for 10.1101/2020.06.26.20139923: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the local Ethical Committee (authorization 233/20), and the requirement for informed consent was waived.
    Consent: The study was approved by the local Ethical Committee (authorization 233/20), and the requirement for informed consent was waived.
    Randomizationnot detected.
    BlindingPTX3 plasma levels were measured, as previously described 20, by a sandwich ELISA (detection limit 0.1 ng/mL, inter-assay variability from 8 to 10%) developed in-house, by personnel blind to patients’ characteristics.
    Power Analysisnot detected.
    Sex as a biological variableWe included all males and non-pregnant females, 18 years of age or older, admitted to Humanitas Clinical and Research Center (Rozzano, Milan, Italy) between March 4th and May 16rd, 2020 (data cutoff on May 13rd) with a laboratory-confirmed diagnosis of COVID-19.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Tissues were again washed and then incubated with the primary antibody (affinity purified rabbit IgG anti-human PTX3) 39 for 15 min.
    anti-human PTX3
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Data relative to bulk transcription in human normal bronchial (NHBE) and malignant cell lines (Calu-3 and A549) upon SARS-CoV-2 infection, were derived from the experiments within the series GSE147507 31.
    Calu-3
    suggested: None
    A549
    suggested: None
    Software and Algorithms
    SentencesResources
    Bioinformatic analysis: Data relative to the transcriptional response to SARS-CoV-2 infection were derived from datasets deposited within the Gene Expression Omnibus (GEO).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Raw bulk RNA-Seq reads were quality inspected with the software “FastQC” (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and aligned with STAR (version 2.6.1) 32 on the GRCh38 genome guided by GENCODE annotation (version 33)
    https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
    suggested: (FastQC, RRID:SCR_014583)
    STAR
    suggested: (STAR, RRID:SCR_015899)
    Gene summarized counts were processed in R, genes whose expression was major than 2 reads were filtered and vst normalized with the R package DESeq2 33
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    Available single cell RNA-Seq experiments, related to BALF of SARS-CoV2 individuals, were obtained from the public repositories Gene Expression Omnibus (GEO) and FigShare platform under the identifiers GSE145926 34,35 and the FigShare platform (https://figshare.com/articles/COVID-19_severity_correlates_with_airway_epithelium-immune_cell_interactions_identified_by_single-cell_analysis/12436517). scRNA-Seq datasets of SARS-CoV-2 infected PBMC (deposited in GEO under the series GSE150728) 36 were explored with the portal cellxgene (https://chanzuckerberg.github.io/cellxgene/) and obtained from “The COVID19 Cell Atlas portal” (
    FigShare
    suggested: (FigShare, RRID:SCR_004328)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    With this caveat, it is tempting to speculate that PTX3 plasma levels may better reflect local tissue disruptive inflammation including the involvement of myelomonocytic cells and the vascular bed. The significance of PTX3 as a biomarker in COVID-19 patient management and stratification and its role in the virus-host interaction deserve further studies.

    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.

  3. Version published to 10.1101/2020.06.26.20139923v1 on medRxiv