Influence of obesity on serum levels of SARS-CoV-2-specific antibodies in COVID-19 patients

  1. Daniela Frasca
  2. Lisa Reidy
  3. Carolyn Cray
  4. Alain Diaz
  5. Maria Romero
  6. Kristin Kahl
  7. Bonnie B. Blomberg

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Abstract

SARS-CoV-2 (Severe Acute Respiratory Syndrome Corona Virus-2), cause of COVID-19 (Coronavirus Disease of 2019), represents a significant risk to people living with pre-existing conditions associated with exacerbated inflammatory responses and consequent dysfunctional immunity. In this paper, we have evaluated the influence of obesity, a condition associated with chronic systemic inflammation, on the secretion of SARS-CoV-2-specific IgG antibodies in the blood of COVID-19 patients. Our hypothesis is that obesity is associated with reduced amounts of specific IgG antibodies. Results have confirmed our hypothesis and have shown that SARS-CoV-2 IgG antibodies are negatively associated with Body Mass Index (BMI) in COVID-19 obese patients, as expected based on the known influence of obesity on humoral immunity. Antibodies in COVID-19 obese patients are also negatively associated with serum levels of pro-inflammatory and metabolic markers of inflammaging and pulmonary inflammation, such as SAA (serum amyloid A protein), CRP (C-reactive protein), and ferritin, but positively associated with NEFA (nonesterified fatty acids). These results altogether could help to identify an inflammatory signature with strong predictive value for immune dysfunction. Inflammatory markers identified may subsequently be targeted to improve humoral immunity in individuals with obesity and in individuals with other chronic inflammatory conditions.

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  1. Version published to 10.1371/journal.pone.0245424
  2. ScreenIT

    SciScore for 10.1101/2020.12.18.20248483: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This research was approved and reviewed by the Institutional Review Board (IRB, protocols #20200504) at the University of Miami, which reviews all human research conducted under the auspices of the University of Miami.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Because the LFD results are not quantitative, only showing the presence or absence of specific IgM/IgG antibodies, we developed a Spike-specific ELISA (see below) to compare anti-Spike values with the other measures.
    anti-Spike
    suggested: None
    ELISA to measure Spike-specific IgG antibodies: Serum IgG antibodies against SARS-CoV-2 Spike protein were measured by an ELISA developed and standardized in our laboratory.
    Spike-specific IgG
    suggested: None
    SARS-CoV-2 Spike protein
    suggested: None
    Software and Algorithms
    SentencesResources
    To examine relationships between variables, bivariate Pearson’s correlation analyses were performed, using GraphPad Prism version 8 software, which was used to construct all graphs.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.12.18.20248483v1 on medRxiv