Diverse Humoral Immune Responses in Younger and Older Adult COVID-19 Patients

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Abstract

As numerous viral variants continue to emerge in the coronavirus disease 2019 (COVID-19) pandemic, determining antibody reactivity to SARS-CoV-2 epitopes becomes essential in discerning changes in the immune response to infection over time. This study enabled us to identify specific areas of antigenicity within the SARS-CoV-2 proteome, allowing us to detect correlations of epitopes with clinical metadata and immunological signals to gain holistic insight into SARS-CoV-2 infection.

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  1. SciScore for 10.1101/2021.01.12.21249702: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Collection of blood samples and deidentified patient information was approved by the University of Virginia Institutional Review Board IRB-HSR #22231 and 200110.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Microarrays were probed with sera and antibody binding detected by incubation with fluorochrome-conjugated goat anti-human IgG or IgA or IgM (Jackson ImmunoResearch, West Grove, PA, USA or Bethyl Laboratories, Inc., Montgomery, TX, USA).
    anti-human IgG
    suggested: None
    IgA
    suggested: None
    IgG, IgA and IgM antibodies are captured by specific bead-region microspheres, each conjugated with SARS-CoV-2 antigen subunits S1, S2, RBD, or N, and are measured by median fluorescent intensity (MFI).
    IgM
    suggested: None
    antigen subunits S1
    suggested: None
    Fifty μL of phycoerythrin-anti-human immunoglobulin (IgG, IgA or IgM per kit in use) detection antibody was added to each well, plate sealed and incubated 90 minutes at room temperature with constant shaking.
    phycoerythrin-anti-human immunoglobulin ( IgG
    suggested: None
    Antibody responses to individual reactive antigens (n=52) were modeled as dependent variables, and the following variables were modeled as independent variables: sex, age category, requirement of a ventilator, days symptomatic prior to sample collection, length of hospital stay, admission to the ICU, maximum required supplemental oxygen category, comorbidity score, maximum body temperature during while admitted, body-mass index (BMI), maximum CRP, maximum ferritin, maximum D dimer, minimum lymphocytes, maximum AST and troponin lab levels, and the base 2 log-transformed measurements from the Milliplex serum analysis.
    BMI
    suggested: None
    troponin lab levels ,
    suggested: None
    To select variables associated with SARS-CoV-2-specific antibodies, linear mixed effects regression (LMER) was used to model all antibody responses against SARS-CoV-2 reactive antigens with random intercepts at the sample level and antigen level to adjust for repeated measures.
    SARS-CoV-2-specific
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Protein microarray analysis of serum samples: The first generation multi-coronavirus protein microarray, produced by Antigen Discovery, Inc. (ADI, Irvine, CA, USA), included 935 full-length coronavirus proteins, overlapping 100, 50 and 30 aa protein fragments and overlapping 13-20 aa peptides from SARS-CoV-2 (WA-1), SARS-CoV, MERS-CoV, HCoV-NL63 and HCoV-OC43.
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    All these coronavirus proteins were produced in Escherichia coli except the SARS-CoV-2 and SARS-CoV S proteins, which were made in Sf9 insect cells and the SARS-CoV-2 RBD, made in HEK-293 cells.
    HEK-293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Software and Algorithms
    SentencesResources
    Data visualization was performed using the circlize (20), ComplexHeatmap (21), ggplot2 and corrplot (22)packages in R.
    ComplexHeatmap
    suggested: (ComplexHeatmap, RRID:SCR_017270)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    A substantial limitation in our study was the small sample size which likely limited our ability to detect relationships between epitopes, cytokines, and clinical outcomes. This further limited in our ability to statistically analyze and classify our serosilent samples and therefore were categorized subjectively based on full length IVTT N and S2 protein reactivity. As this small cohort is meant for hypothesis generation, a larger cohort is needed to further validate our findings. Our study is also limited to epitopes produced in Escherichia coli which restricts our ability to see epitopes that require eukaryotic post-translational modification such as glycosylation. This is particularly relevant in regards to the spike protein, which exists as a trimer on the virion surface and undergoes conformational changes during viral entry into cells (6). As addressed in Camerini et al we also observed similar limitations in response to S1 fragments produced in vitro, which perhaps was influenced in part by prokaryotic production of IVTT proteins. However, we were able to detect an area in S1 which is notable in its correlations and outcomes as discussed above.

    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

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