COVID-19 patients have increased levels of membrane-associated and soluble CD48

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Abstract

COVID-19 is a respiratory-centered systemic disorder caused by SARS-CoV-2. The disease can progress into a severe form causing acute lung injury.

CD48 is a co-signaling receptor, existing as both membrane-bound and soluble forms reported to be dysregulated in several inflammatory conditions. Therefore, we reasoned that CD48 could be deregulated in COVID-19 as well.

Here we analyzed CD48 expression in autoptic sections and peripheral blood leukocytes and sera of COVID-19 patients by gene expression profiling (HTG® autoimmune panel), immunohistochemistry, flow cytometry and ELISA.

Lung tissue of COVID-19 patients showed increased CD48 mRNA expression and infiltration of CD48+ lymphocytes. In the peripheral blood, mCD48 was considerably increased on all evaluated cells, and additionally, sCD48 levels were significantly higher in COVID-19 patients independently of disease severity. Considering the alterations of mCD48 and sCD48, a specific role for CD48 in COVID-19 can be assumed, suggesting it as a potential target for therapy.

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  1. SciScore for 10.1101/2022.03.18.484843: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Tissue collection was approved by the Ethics committee of Northern and Central Switzerland (study ID 2020-00969).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    anti-CD48 antibody (EPR4108; ab134049; Abcam, Cambridge, UK), washed, and counterstained with hematoxylin (Gill II).
    anti-CD48
    suggested: None
    Software and Algorithms
    SentencesResources
    Gene Expression Programming (GEP) of lung tissue: GEP of the lung tissue obtained at autopsy and used for the TMA construction was performed by HTG according to established protocols (https://www.htgmolecular.com/assets/htg/resources/BR-05-HTG-EdgeSeq-System.pdf).
    Gene Expression Programming
    suggested: None
    A PCA analysis was then performed using the pcomp function in R©, version 4.0.3 (R-Project for Statistical Computing, Vienna, Austria) and differential expression analysis of COVID-19 cases against controls was conducted with the DESeq2 package using default settings.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    The heatmap was produced with the pheatmap package.
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    Thereafter, cells were washed twice (250g, 5 min, 4°C) with 0.1% BSA/PBS, and FC data were acquired by BD LSR II Flow Cytometer and analyzed with FlowJo software (Tree Star, OR, USA)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Data were analyzed by Prism version 9.0 (GraphPad Software, San Diego, California, USA).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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.