4.6 Article

COVID-19-specific transcriptomic signature detectable in blood across multiple cohorts

期刊

FRONTIERS IN GENETICS
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.929887

关键词

COVID-19; signature; RNA-seq; single-cell; infection; severity

资金

  1. European Research Council ERC [677943]
  2. European Union [955321]
  3. Academy of Finland [310561, 314443, 329278, 335434, 335611, 341342]
  4. Sigrid Juselius Foundation
  5. University of Turku Graduate School (UTUGS)
  6. Biocenter Finland
  7. ELIXIR Finland
  8. Academy of Finland (AKA) [335611, 329278, 314443, 335434, 335611, 329278, 314443] Funding Source: Academy of Finland (AKA)
  9. Marie Curie Actions (MSCA) [955321] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

This study reanalyzed transcriptome data from multiple independent cohort studies and identified a COVID-19-specific signature consisting of 149 genes. The signature includes signals previously associated with the disease, such as immune response and cell cycle dysregulation, as well as potential new gene candidates related to COVID-19.
The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading across the world despite vast global vaccination efforts. Consequently, many studies have looked for potential human host factors and immune mechanisms associated with the disease. However, most studies have focused on comparing COVID-19 patients to healthy controls, while fewer have elucidated the specific host factors distinguishing COVID-19 from other infections. To discover genes specifically related to COVID-19, we reanalyzed transcriptome data from nine independent cohort studies, covering multiple infections, including COVID-19, influenza, seasonal coronaviruses, and bacterial pneumonia. The identified COVID-19-specific signature consisted of 149 genes, involving many signals previously associated with the disease, such as induction of a strong immunoglobulin response and hemostasis, as well as dysregulation of cell cycle-related processes. Additionally, potential new gene candidates related to COVID-19 were discovered. To facilitate exploration of the signature with respect to disease severity, disease progression, and different cell types, we also offer an online tool for easy visualization of the selected genes across multiple datasets at both bulk and single-cell levels.

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