Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

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Abstract

Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyzed the transcriptomes of 605,904 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observed a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD epithelial cells expressed higher levels of genes linked directly to the efficiency of viral replication and innate immune response. Additionally, we identified basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.

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  1. SciScore for 10.1101/2020.10.20.347187: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Heat-induced citrate antigen retrieval (pH 6.0) and pepsin antigen retrieval was performed for Rabbit monoclonal ACE2 (ab108252, EPR4435(2) Abcam, UK) and the anti-αvβ6 integrin antibody (6.2A1; Biogen, Cambridge, MA, USA), respectively
    EPR4435 ( 2
    suggested: None
    anti-αvβ6 integrin
    suggested: None
    Rabbit monoclonal ACE2 (1:400) and anti-αvβ6 integrin (1:3000) was diluted in Leica antibody diluent (RE AR9352, Leica, Biosystems, UK) and incubated with the sections overnight at 4°C.
    ACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    For the boxplots, count numbers of selected genes were plotted using the geom_boxplot and geom_jitter function of the ggplot2 R package 77
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Gene module score: To calculate the combined expression of genes, we used the AddModuleScore in Seurat v3.1.5 package.
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    Heat-induced citrate antigen retrieval (pH 6.0) and pepsin antigen retrieval was performed for Rabbit monoclonal ACE2 (ab108252, EPR4435(2) Abcam, UK) and the anti-αvβ6 integrin antibody (6.2A1; Biogen, Cambridge, MA, USA), respectively
    Biogen
    suggested: (Biogen Idec, RRID:SCR_003790)
    Statistical analyses were completed using GraphPad Prism 7.0 (GraphPad Software, San Diego, CA, USA).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

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


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    One limitation of our study is that we focus mainly on the peripheral regions of the lungs, and did not analyze cells in the upper airways or trachea. It is possible that there are significant differences in SARS-CoV-2 entry gene expression between disease and control samples in the more proximal regions of the lungs. Our study is also limited to the expression profiles of patients with CLD without SARS-CoV-2 infection, as the collection of samples from patients who are both infected with SARS-CoV-2 and have chronic lung disease are difficult to collect at present. Nevertheless, our study highlights that dysregulation of genes related to viral replication and innate immune response in the epithelial cells, and basal differences in the inflammatory gene expression programs are key factors leading to an increased risk of COVID-19 severity and poorer outcomes in patients with CLD.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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

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