Attention to time-of-day variability improves the reproducibility of gene expression patterns in multiple sclerosis
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
---|---|
Article number | 103247 |
Journal / Publication | iScience |
Volume | 24 |
Issue number | 11 |
Online published | 9 Oct 2021 |
Publication status | Published - 19 Nov 2021 |
Link(s)
DOI | DOI |
---|---|
Attachment(s) | Documents
Publisher's Copyright Statement
|
Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85122766991&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(a509f899-cf37-4c04-a3bb-e84a44a3851a).html |
Abstract
Low reproducibility in gene expression profiles has been observed in transcriptome studies, and this often limits applying findings to clinical practice. Here, we show time-of-day effects on gene expression and analytical schemes to increase the reproducibility in expression patterns. We recruited patients with relapsing-remitting multiple sclerosis (RRMS) and healthy subjects and collected blood from individuals twice a day, day (2 pm) and night (9 pm). RNA sequencing analyses found that gene expression in RRMS in relapse (Relapse) is significantly changed at night compared with either Relapse at day or RRMS in remission (Remission). Gene set overrepresentation analysis demonstrated that gene sets significantly changed in Relapse at night are enriched to immune responses related to MS pathology. In those gene sets, 68 genes are significantly changed expression in Relapse at night compared with Relapse at day and Remission. This supports that times of sample collections should be standardized to obtain reproducible gene expression patterns.
Research Area(s)
- MARKERS, PACKAGE, INNATE
Citation Format(s)
Attention to time-of-day variability improves the reproducibility of gene expression patterns in multiple sclerosis. / Huang, Suihong; Wu, Tan; Lau, Alexander Y. et al.
In: iScience, Vol. 24, No. 11, 103247, 19.11.2021.
In: iScience, Vol. 24, No. 11, 103247, 19.11.2021.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Download Statistics
No data available