2024-03-29T04:59:10Z
https://u-ryukyu.repo.nii.ac.jp/oai
oai:u-ryukyu.repo.nii.ac.jp:02011748
2023-08-03T05:29:15Z
1642838163960:1642838338003
1642838403551:1642838406845
PCA‑based unsupervised feature extraction for gene expression analysis of COVID‑19 patients
Fujisawa, Kota
Shimo, Mamoru
Taguchi, Y.‑H.
Ikematsu, Shinya
Miyata, Ryota
open access
© The Author(s) 2021
Creative Commons Attribution 4.0
https://creativecommons.org/licenses/by/4.0/
Coronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.
論文
Nature Research
2021-08-30
eng
journal article
VoR
http://hdl.handle.net/20.500.12000/49789
http://hdl.handle.net/20.500.12000/49789
https://u-ryukyu.repo.nii.ac.jp/records/2011748
https://doi.org/10.1038/s41598-021-95698-w
https://doi.org/10.1038/s41598-021-95698-w
2045-2322
Scientific Reports
11
https://u-ryukyu.repo.nii.ac.jp/record/2011748/files/s41598-021-95698-w.pdf