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Status |
Public on Nov 03, 2021 |
Title |
Attention to time-of-day variability improves the reproducibility of gene expression patterns in multiple sclerosis |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
Most biomarkers for the diagnosis and prognosis of multiple sclerosis (MS) are not yet clinically available due to low reproducibility. Here, we show that times of day affect gene expression profiles in MS patients. Thus sample collection has to be standardized based on the time-points biomarkers are expressed to increase reproducibility. In this study, we examined transcriptome profiles in whole blood of MS patients collected at two different time-points of the day, around 2 pm as the daytime and 9 pm as the nighttime. We observed the significantly changed gene expression profiles in the relapsing patients at nighttime compared to their daytime samples and the remitting patients at nighttime. Among all DEGs, we focused on differentially expressed genes (DEGs) related to immune responses because of association with clinical outcomes of MS. 68 immune responses-associated DEGs significantly changed their expression in the relapsing patients at nighttime but not in their daytime samples and remitting patients at nighttime. Therefore, this study shows that: 1) gene expresion patterns in relapsing patients are changed compared to remitting patients; 2) altered gene expression patterns in relpasing patients are detected at nighttim; 3) times of day to collect samples from MS patients should be standardized based on the gene expression patterns across a day.
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Overall design |
Seven relapsing-remitting multiple sclerosis (RRMS) patients and three healthy controls who had no history of neurological or psychiatric diseases were recruited. Whole blood was collected two times a day from all individuals: 2 pm (daytime) and 9 pm (nighttime), using the PAXgene Blood RNA tubes. Total RNA was extracted using the PAXgene Blood RNA Kit (all from QIAGEN) and subjected to RNA-sequencing analysis to obtain the gene expression profiles.
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Contributor(s) |
Kim J, Wang X, Huang S, Wu T, Lau AY, Au C, Huang H |
Citation(s) |
34746708 |
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https://0-doi-org.brum.beds.ac.uk/10.1016/j.isci.2021.103247
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Submission date |
May 11, 2020 |
Last update date |
Nov 10, 2021 |
Contact name |
KIM Jin Young |
E-mail(s) |
jinyoung.kim@cityu.edu.hk
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Organization name |
City University of Hong Kong
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Department |
Department of Biomedical Sciences
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Street address |
Tat Chee Avenue, Kowloon, Hong Kong
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City |
Hong Kong |
ZIP/Postal code |
999077 |
Country |
Hong Kong |
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Platforms (1) |
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Samples (20)
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Relations |
BioProject |
PRJNA631782 |
SRA |
SRP261163 |