Maternal cytokine response after SARS-CoV-2 infection during pregnancy

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Abstract

Objective: Dysregulation of the immune system during pregnancy is associated with adverse pregnancy outcomes. Recent studies report cytokine changes during the acute phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We examine whether there is a lasting association between SARS-CoV-2 infection during pregnancy and peripheral blood cytokine levels. Study design: We conducted a case-control study at the Mount Sinai health system in NYC including 100 SARS-CoV-2 IgG antibody positive people matched to 100 SARS-CoV-2 IgG antibody negative people on age, race/ethnicity, parity, and insurance status. Blood samples were collected at a median gestational age of 34 weeks. Levels of 14 cytokines were measured. Results: Individual cytokine levels and cytokine cluster Eigenvalues did not differ significantly between groups, indicating no persisting maternal cytokine changes after SARS-CoV-2 infection during pregnancy. Conclusion: Our findings suggest that the acute inflammatory response after SARS-CoV-2 infection may be restored to normal values during pregnancy.

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  1. SciScore for 10.1101/2022.01.04.474908: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: All participants provided written informed consent per the institutional review board (IRB)-approved study protocol (IRB at the Icahn School of Medicine at Mount Sinai, protocol IRB-20-03352, April 15, 2020).
    IRB: All participants provided written informed consent per the institutional review board (IRB)-approved study protocol (IRB at the Icahn School of Medicine at Mount Sinai, protocol IRB-20-03352, April 15, 2020).
    Sex as a biological variableAll pregnant people receiving obstetrical care at the Mount Sinai Hospital and Mount Sinai West during the study period are eligible for participation.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The plasma samples were first screened using a low dilution (1:50) for antibodies to SARS-CoV-2 receptor binding domain (RBD).
    SARS-CoV-2 receptor binding domain (RBD).
    suggested: None
    A general limitation in SARS-CoV-2 IgG testing is the possibility of false negatives prior to IgG antibody production onset or in cases where IgG antibody levels revert to zero in the months after infection [25].
    IgG
    suggested: None
    2.5 Statistical analysis: Demographic and clinical characteristics of cases (100 pregnant people with anti-S IgG antibodies) and controls (100 pregnant people with no anti-S IgG antibodies) were compared using either an independent samples t-test or a Mann-Whitney U test for continuous variables and a chi-square test for categorical variables.
    anti-S IgG
    suggested: None
    To examine the association between cytokine levels and antibody titer levels, cases were divided into three groups based on anti-S IgG antibody titer level for ease of interpretation: mild (1:80-1:400), moderate (1:800-1:1600), and high (>1:1600).
    1:800-1:1600
    suggested: None
    Software and Algorithms
    SentencesResources
    The multiplex assay was performed at Eve Technologies using the Bio-Plex™ 200 system (Bio-Rad Laboratories, Inc., Hercules, CA, USA).
    Bio-Rad Laboratories
    suggested: (Bio-Rad Laboratories, RRID:SCR_008426)
    Prior to clustering, each cytokine was scaled and centered; clusters were identified using complete-linkage agglomerative hierarchical clustering with Euclidean distances across cases and controls using the pheatmap v1.0.2 package in R [34].
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    Plots were generated in R using the pheatmap, ggplot2 and corrplot packages, and in GraphPad Prism.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Statistical analyses were performed using SPSS software version 27.0.
    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: We detected the following sentences addressing limitations in the study:
    4.4 Strengths and limitations: This study has several strengths. We used a serological assay with a high sensitivity (95%) and specificity (100%) to establish SARS-CoV-2 exposure [20]. This enabled unbiased recruitment of pregnant people with past SARS-CoV-2 infection, both with and without symptoms. Even though we do not know the exact timing of infection, based on time of sample collection and expected duration of antibodies we can infer that infection occurred during pregnancy. This study is the largest of its kind so far. We investigated a broad panel of cytokines, which allowed us to assess not only individual cytokine responses, but also cytokine clusters. The findings of the current study are also subject to some limitations. The difference in sample size between the second trimester samples compared to the third trimester and labor and delivery samples is due to the current study being an interim analysis of an ongoing prospective cohort study. Future studies based on the entire prospective cohort will include a larger sample for each timepoint. Pregnant people with false negative anti-S IgG antibodies may have been misclassified as unexposed since IgG production onset occurs one week after infection and even though studies have shown sustained IgG antibody levels after 30 weeks of infection [38], IgG antibody levels might incidentally revert to zero in the months after infection [25]. In addition, anti-S IgG antibodies were assessed only once in participants, at a me...

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    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.