Longitudinal Study of DNA Methylation and Epigenetic Clocks Prior to and Following Test-Confirmed COVID-19 and mRNA Vaccination

  1. Alina P. S. Pang
  2. Albert T. Higgins-Chen
  3. Florence Comite
  4. Ioana Raica
  5. Christopher Arboleda
  6. Hannah Went
  7. Tavis Mendez
  8. Michael Schotsaert
  9. Varun Dwaraka
  10. Ryan Smith
  11. Morgan E. Levine
  12. Lishomwa C. Ndhlovu
  13. Michael J. Corley

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Abstract

The host epigenetic landscape rapidly changes during SARS-CoV-2 infection, and evidence suggest that severe COVID-19 is associated with durable scars to the epigenome. Specifically, aberrant DNA methylation changes in immune cells and alterations to epigenetic clocks in blood relate to severe COVID-19. However, a longitudinal assessment of DNA methylation states and epigenetic clocks in blood from healthy individuals prior to and following test-confirmed non-hospitalized COVID-19 has not been performed. Moreover, the impact of mRNA COVID-19 vaccines upon the host epigenome remains understudied. Here, we first examined DNA methylation states in the blood of 21 participants prior to and following test-confirmed COVID-19 diagnosis at a median time frame of 8.35 weeks; 756 CpGs were identified as differentially methylated following COVID-19 diagnosis in blood at an FDR adjusted p -value < 0.05. These CpGs were enriched in the gene body, and the northern and southern shelf regions of genes involved in metabolic pathways. Integrative analysis revealed overlap among genes identified in transcriptional SARS-CoV-2 infection datasets. Principal component-based epigenetic clock estimates of PhenoAge and GrimAge significantly increased in people over 50 following infection by an average of 2.1 and 0.84 years. In contrast, PCPhenoAge significantly decreased in people fewer than 50 following infection by an average of 2.06 years. This observed divergence in epigenetic clocks following COVID-19 was related to age and immune cell-type compositional changes in CD4 + T cells, B cells, granulocytes, plasmablasts, exhausted T cells, and naïve T cells. Complementary longitudinal epigenetic clock analyses of 36 participants prior to and following Pfizer and Moderna mRNA-based COVID-19 vaccination revealed that vaccination significantly reduced principal component-based Horvath epigenetic clock estimates in people over 50 by an average of 3.91 years for those who received Moderna. This reduction in epigenetic clock estimates was significantly related to chronological age and immune cell-type compositional changes in B cells and plasmablasts pre- and post-vaccination. These findings suggest the potential utility of epigenetic clocks as a biomarker of COVID-19 vaccine responses. Future research will need to unravel the significance and durability of short-term changes in epigenetic age related to COVID-19 exposure and mRNA vaccination.

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  1. Version published to 10.3389/fgene.2022.819749
  2. ScreenIT

    SciScore for 10.1101/2021.12.01.21266670: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    In vitro SARS-CoV-2 infection and exposure: SARS-CoV-2 virus (isolate USA-WA1/2020 (BEI resources; NR-52281) was propagated and titrated in Vero E6 cell lines.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Calu-3 cells were infected for 96 hrs.
    Calu-3
    suggested: None
    Software and Algorithms
    SentencesResources
    analyses: Raw Methylation EPIC array IDAT intensity data was loaded and preprocessed in the R statistical programming language (http://www.r-project.org) using The Chip Analysis Methylation Pipeline (ChAMP, version 2.8.3)(Tian et al., 2017)
    http://www.r-project.org
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Methylation beta-values ranging from 0 -1 (corresponding to unmethylated to methylated signal intensity) for each sample were normalized using the BMIQ function implemented in the ChAMP pipeline.
    ChAMP
    suggested: (ChAMP, RRID:SCR_012891)
    Genes related to differentially methylated loci were utilized for a COVID-19 gene set analyses from the Enrichr web tool(Kuleshov et al., 2016)
    Enrichr
    suggested: (Enrichr, RRID:SCR_001575)
    Analyses were performed in R 4.1.1 and RStudio Version 1.4.1717.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    Figures were made using GraphPad and corrplot R package.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    De-identified donor PBMC specimens were obtained from Astarte Biological for in vitro exposure to 0.1 MOI SARS-CoV-2 for 60 hrs.
    Astarte Biological
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Despite the strengths of this longitudinal epigenetic study, there are several limitations. First, our longitudinal study design only included two time points to examine changes related to COVID-19 and mRNA vaccination comparing baseline and a short-term follow-up assessment of DNA methylation. future studies will need to study a larger sample size and determine whether these age-related divergent changes to epigenetic clocks are durable following COVID-19 and potentially relate to those with long-COVID-19 syndrome. Additionally, there was variation in the time following confirmed COVID-19 or mRNA COVID-19 vaccination for when the post sample assay for DNA methylation was completed. Yet, given the complete lack of longitudinal DNA methylation studies of COVID-19 and mRNA COVID-19 vaccination we provide discovery findings that are compelling regarding specific DNA methylation changes and epigenetic clocks that warrant further investigation. Future studies that have serial blood collection of participants throughout the course of mRNA- vaccination and even following booster shots will be extremely valuable for epigenetic clock investigations. Recent technological advancements based on Tagmentation-based Indexing of Methylation Sequencing (TIME-Seq) have scaled and reduced the cost of epigenetic age predictions permitting methodology for a more comprehensive study follow-up to our findings (Griffin et al., 2021). We also acknowledge the limited clinical data for participants and...

    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.

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  3. Version published to 10.1101/2021.12.01.21266670 on medRxiv