Absent or insufficient anti-SARS-CoV-2 S antibodies at ICU admission are associated to higher viral loads in plasma, antigenemia and mortality in COVID-19 patients

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Abstract

Purpose

to evaluate the association between anti-SARS-CoV-2 S IgM and IgG antibodies with viral RNA load in plasma, the frequency of antigenemia and with the risk of mortality in critically ill patients with COVID-19.

Methods

anti-SARS-CoV-2 S antibodies levels, viral RNA load and antigenemia were profiled in plasma of 92 adult patients in the first 24 hours following ICU admission. The impact of these variables on 30-day mortality was assessed by using Kaplan-Meier curves and multivariate Cox regression analysis.

Results

non survivors showed more frequently absence of anti-SARS-CoV-2 S IgG and IgM antibodies than survivors (26.3% vs 5.6% for IgM and 18.4% vs 5.6% for IgG), and a higher frequency of antigenemia (47.4% vs 22.2%) ( p <0.05). Non survivors showed lower concentrations of anti-S IgG and IgM and higher viral RNA loads in plasma, which were associated to increased 30-day mortality and decreased survival mean time. [Adjusted HR (CI95%), p ]: [S IgM (AUC ≥60): 0.48 (0.24; 0.97), 0.040]; [S IgG (AUC ≥237): 0.47 (0.23; 0.97), 0.042]; [Antigenemia (+): 2.45 (1.27; 4.71), 0.007]; [N1 viral load (≥ 2.156 copies/mL): 2.21 (1.11; 4.39),0.024]; [N2 viral load (≥ 3.035 copies/mL): 2.32 (1.16; 4.63), 0.017]. Frequency of antigenemia was >2.5-fold higher in patients with absence of antibodies. Levels of anti-SARS-CoV-2 S antibodies correlated inversely with viral RNA load.

Conclusion

absence / insufficient levels of anti-SARS-CoV-2 S antibodies following ICU admission is associated to poor viral control, evidenced by increased viral RNA loads in plasma, higher frequency of antigenemia, and also to increased 30-day mortality.

Take-home message

absent or low levels of antibodies against the S protein of SARS-CoV- 2 at ICU admission is associated to an increased risk of mortality, higher frequency of antigenemia and higher viral RNA loads in plasma. Profiling anti-SARS-CoV-2 s antibodies at ICU admission could help to predict outcome and to better identify those patients potentially deserving replacement treatment with monoclonal or polyclonal antibodies.

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  1. SciScore for 10.1101/2021.03.08.21253121: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Samples were stored at −80°C until quantification of antibodies, viral RNA load and antigenemia evaluation.
    antigenemia evaluation.
    suggested: None
    Immunoassay for antibody quantification: a specific immunoassay was developed to quantify anti-SARS-CoV-2 S IgG and IgM antibodies in plasma.
    anti-SARS-CoV-2 S IgG
    suggested: None
    IgM
    suggested: None
    The following day, serum samples were added, and the binding to the S protein was determined by successive incubations with a secondary peroxidase-conjugated anti- human IgG or IgM (Jackson Immunoresearch, West Grove, PA, USA) antibody and the OPD substrate (Sigma Aldrich, San Luis, MO, USA).
    anti- human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    The area under the curve (AUC) was calculated by using GraphPad Prism 8.0 (GraphPad Sofware, Inc., San Diego, CA, USA) and the following parameters: Baseline Y=0.1; ignore peaks that are less than 10% of the distance from minimum to maximum Y; all peaks must go above the baseline.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Antigenemia: The presence/absence of N antigen of SARS-CoV-2 in plasma was evaluated by using the Panbio™ COVID-19 Ag Rapid Test Device from Abbott (Chicago, IL, USA).
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    SPSS INC, Armonk, NY, U.S.A), and figures were generated using GraphPad Prism 8.0 (GraphPad Software, Inc.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04457505RecruitingOne Year Follow-ups of Patients Admitted to Spanish Intensiv…


    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.