Age-related Differences in the Nasal Mucosal Immune Response to SARS-CoV-2

  1. Clarissa M. Koch
  2. Andrew D. Prigge
  3. Kishore R. Anekalla
  4. Avani Shukla
  5. Hanh Chi Do Umehara
  6. Leah Setar
  7. Jairo Chavez
  8. Hiam Abdala-Valencia
  9. Yuliya Politanska
  10. Nikolay S. Markov
  11. Grant R. Hahn
  12. Taylor Heald-Sargent
  13. L. Nelson Sanchez- Pinto
  14. William J. Muller
  15. Benjamin D. Singer
  16. Alexander V. Misharin
  17. Karen M. Ridge
  18. Bria M. Coates

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Abstract

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  1. Version published to 10.1165/rcmb.2021-0292oc
  2. ScreenIT

    SciScore for 10.1101/2021.01.26.21250269: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Approval for this study was obtained from the Institutional Review Board at Ann & Robert H.
    Consent: Informed consent was obtained from adult participants and parents/guardians of pediatric participants.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Clinical Data: Clinical data were collected and managed using REDCap electronic data capture tools hosted at the Northwestern University Clinical and Translational Sciences Institute (24).
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    FASTQ files were generated using bcl2fastq (Illumina).
    bcl2fastq
    suggested: (bcl2fastq , RRID:SCR_015058)
    0.6.4 and aligned to the hybrid genome described above using STAR 2.6.1d (30)
    STAR
    suggested: (STAR, RRID:SCR_015899)
    Gene-level assignment was then performed using featureCounts 1.6.4 (31).
    featureCounts
    suggested: (featureCounts, RRID:SCR_012919)
    Weighted gene co-expression network analysis (WGCNA): WGCNA was performed manually using WGCNA version 1.69 with default settings unless otherwise noted (32).
    WGCNA
    suggested: (Weighted Gene Co-expression Network Analysis, RRID:SCR_003302)
    Deconvolution of bulk RNA-seq signatures: Deconvolution of bulk RNA-seq signatures was performed using AutoGeneS v1.0.3 (34).
    AutoGeneS
    suggested: None
    Data were visualized using ggplot2 version 3.3.1 and Graphpad Prism.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Graphpad Prism
    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:

    Our study has several limitations. First, our institution utilized two different PCR platforms for the detection of SARS-CoV-2 during the study period. Due to differences in methodology, viral loads cannot be directly compared between the platforms. Moreover, PCR testing was not available for the adults accompanying children infected with SARS- CoV-2 during the study period. To overcome this limitation, we used dual RNA-seq, which allows for simultaneous host transcriptomic analysis and pathogen characterization (21). By creating custom hybrid genomes, we were able to identify and quantify viral transcripts in our samples as a surrogate for viral load, thus, enabling comparison across all groups in our study. Second, while our study includes children infected with other respiratory viruses – RSV and IV, which serve as proper controls to SARS-CoV-2-infected children, it primarily includes hospitalized children with SARS-CoV-2, representing a minority of pediatric SARS-CoV-2 infections. However, 14% of our pediatric cohort were asymptomatic with incidental SARS-CoV-2 diagnoses. The local host response in these asymptomatic children’s nasal mucosa could not be distinguished from more severely affected pediatric participants. Similarly, our study only included two hospitalized young adults with moderate SARS-CoV-2 infection and did not include any severely ill hospitalized adults requiring intubation and mechanical ventilation. Therefore, hospitalized adults with severe SARS-CoV-...

    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 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.

  3. Version published to 10.1101/2021.01.26.21250269v1 on medRxiv