Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

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Abstract

Background

The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic.

Measure

Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset.

Results

A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months.

Conclusion

Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

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  1. SciScore for 10.1101/2020.07.09.20149633: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Protein microarray fabrication: The proteins, along with the negative (BSA) and positive controls (anti-Human IgG and IgM antibody), were printed in quadruplicate on PATH substrate slide (Grace Bio-Labs, Oregon, USA) to generate identical arrays in a 2× 7 subarray format using Super Marathon printer (Arrayjet, UK).
    IgM
    suggested: None
    The arrays were washed with 1×PBST and bound antibodies were detected by incubating with Cy3-conjugated goat anti-human IgG and Alexa Fluor 647-conjugated donkey anti-human IgM (Jackson ImmunoResearch, PA, USA), which were diluted 1: 1,000 in 1×PBST, and incubated at room temperature for 1 h.
    anti-human IgG
    suggested: (Bio-Rad Cat# MCA647F, RRID:AB_808612)
    anti-human IgM
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Neutralization detection using pseudovirus neutralizaion assay: A full length codon-optimized spike protein (S) of the SARS-CoV-2 was first cloned into the lentivirus vector GV367, and then used to generate a eGFP-coexpressing pseudovirus by cotransfected into HEK293T cells with the other two viral packaging help vectors pHelper1.0 and pHelper2.0 (Genechem, Shanghai).
    HEK293T
    suggested: NCBI_Iran Cat# C498, RRID:CVCL_0063)
    The SARS-CoV-2 pseudovirus neutralization assay was carried out on Vero E6 cells in a 96-well plate.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analysis: All statistical analyses were carried out using SPSS or R software.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Cluster analysis was performed with pheatmap package of R.
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)

    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.

    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.