Evaluation of maternal-infant dyad inflammatory cytokines in pregnancies affected by maternal SARS-CoV-2 infection in early and late gestation

  1. Elizabeth S. Taglauer
  2. Yashoda Dhole
  3. Jeffery Boateng
  4. Jennifer Snyder-Cappione
  5. Samantha E. Parker
  6. Katherine Clarke
  7. Lillian Juttukonda
  8. Jean Devera
  9. Jessica Hunnewell
  10. Elizabeth Barnett
  11. Hongpeng Jia
  12. Christina Yarrington
  13. Vishakha Sabharwal
  14. Elisha M. Wachman

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Abstract

No abstract available

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  1. Version published to 10.1038/s41372-022-01391-9
  2. ScreenIT

    SciScore for 10.1101/2021.12.26.472655: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Patients were excluded from this cohort if they had received COVID-19 vaccination by the time of delivery, or if they were deemed unable to provide informed consent and agree to study procedures for any medical or social reason.
    IRB: This study was approved by the Boston University Medical Campus Institutional Review Board.
    Sex as a biological variableThis hospital delivers a significant proportion of pregnant patients from minority groups with comorbidities such as hypertension and obesity and having public insurance, which are characteristics associated with severe SARS-CoV-2 disease (18, 19).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Written informed consent or REDCap e-consent was obtained from all participants.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    All statistical analysis was performed using SAS software V9.4 (SAS Analytics).
    SAS
    suggested: (SASqPCR, RRID:SCR_003056)
    Graphical data for cytokine levels was created using Prism Software (Graphpad)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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:
    The current study has several limitations. First, our cohorts were of moderate sample size and we did not evaluate a complete repertoire of COVID-19 related clinical variables (i.e. c-reactive protein (CRP) levels, white blood cell count). As only a small subset of our cohort had these labs available, they were not included as part of this analysis. Our cohort also had a larger proportion of patients with maternal SARS-CoV-2 infections in early gestation as compared with late gestation. Ongoing analysis with larger cohorts will be required to characterize the cytokine profiles of early vs late pregnancy SARS-CoV-2 infections more completely. As the majority of studies on COVID-19 in pregnancy contain samples exclusively from late pregnancy (3rd trimester) infections, our study highlights the importance of incorporating patients with SARS-CoV-2 infection at multiple gestational stages of pregnancy for ongoing studies in this field. In particular, multivariate analysis to correlate anti-viral antibodies with cytokine profiles will be informative to identify how these inflammatory signatures impact maternal and infant SARS-CoV-2 responses, particularly in relation to gestational timing of maternal infection. This study supports a growing body of evidence that perinatal alterations resulting from maternal COVID-19 in pregnancy have a risk of impacting the health of infants even in the absence of fetal SARS-CoV-2 transmission. Indeed, of all our clinical parameters evaluated betwe...

    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.

    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 10.1101/2021.12.26.472655v1 on bioRxiv