Frontiers in Cell and Developmental Biology (Oct 2022)

Transcriptome and DNA methylome analysis of peripheral blood samples reveals incomplete restoration and transposable element activation after 3-months recovery of COVID-19

  • Ying Yin,
  • Ying Yin,
  • Ying Yin,
  • Ying Yin,
  • Xiao-zhao Liu,
  • Xiao-zhao Liu,
  • Xiao-zhao Liu,
  • Qing Tian,
  • Yi-xian Fan,
  • Yi-xian Fan,
  • Yi-xian Fan,
  • Zhen Ye,
  • Tian-qing Meng,
  • Gong-hong Wei,
  • Cheng-liang Xiong,
  • Hong-gang Li,
  • Ximiao He,
  • Ximiao He,
  • Ximiao He,
  • Li-quan Zhou

DOI
https://doi.org/10.3389/fcell.2022.1001558
Journal volume & issue
Vol. 10

Abstract

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Comprehensive analyses showed that SARS-CoV-2 infection caused COVID-19 and induced strong immune responses and sometimes severe illnesses. However, cellular features of recovered patients and long-term health consequences remain largely unexplored. In this study, we collected peripheral blood samples from nine recovered COVID-19 patients (median age of 36 years old) from Hubei province, China, 3 months after discharge as well as 5 age- and gender-matched healthy controls; and carried out RNA-seq and whole-genome bisulfite sequencing to identify hallmarks of recovered COVID-19 patients. Our analyses showed significant changes both in transcript abundance and DNA methylation of genes and transposable elements (TEs) in recovered COVID-19 patients. We identified 425 upregulated genes, 214 downregulated genes, and 18,516 differentially methylated regions (DMRs) in total. Aberrantly expressed genes and DMRs were found to be associated with immune responses and other related biological processes, implicating prolonged overreaction of the immune system in response to SARS-CoV-2 infection. Notably, a significant amount of TEs was aberrantly activated and their activation was positively correlated with COVID-19 severity. Moreover, differentially methylated TEs may regulate adjacent gene expression as regulatory elements. Those identified transcriptomic and epigenomic signatures define and drive the features of recovered COVID-19 patients, helping determine the risks of long COVID-19, and guiding clinical intervention.

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