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Identification of salivary microRNA profiles in male mouse model of chronic sleep disorder

Authors :
Yuta Yoshida
Yuhei Yajima
Yuri Fujikura
Haotong Zhuang
Sayaka Higo-Yamamoto
Atsushi Toyoda
Katsutaka Oishi
Source :
Stress, Vol 26, Iss 1, Pp 21-28 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

Chronic sleep disorders (CSD) comprise a potential risk factor for metabolic and cardiovascular diseases, obesity and stroke. Thus, the identification of biomarkers for CSD is an important step in the early prevention of metabolic dysfunctions induced by sleep dysfunction. Diagnostic saliva samples can be easily and noninvasively collected. Thus, we aimed to identify whole microRNA (miRNA) profiles of saliva in control and psychophysiologically stressed CSD mouse models and compare them at Zeitgeber time (ZT) 0 (lights on) and ZT12 (lights off). The findings of two-way ANOVA revealed that the expression of 342 and 109 salivary miRNAs was affected by CSD and the time of day, respectively. Interactions were found in 122 miRNAs among which, we identified 197 (ZT0) and 62 (ZT12) upregulated, and 40 (ZT0) and seven (ZT12) downregulated miRNAs in CSD mice. We showed that miR-30c-5p, which is elevated in the plasma of patients with hypersomnia, was upregulated in the saliva of CSD mice collected at ZT0. The miRNAs, miR-10a-5p, miR-146b-5p, miR-150-5p, and miR-25-3p are upregulated in the serum of humans with poor sleep quality, and these were also upregulated in the saliva of CSD mice collected at ZT0. The miRNAs miR-30c, miR146b-5p, miR150, and miR-25-5p are associated with cardiovascular diseases, and we found that plasma concentrations of brain natriuretic peptides were significantly increased in CSD mice. The present findings showed that salivary miRNA profiles could serve as useful biomarkers for predicting CSD.

Details

Language :
English
ISSN :
10253890 and 16078888
Volume :
26
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Stress
Publication Type :
Academic Journal
Accession number :
edsdoj.49a3122f968242c59d13f3b281116aa6
Document Type :
article
Full Text :
https://doi.org/10.1080/10253890.2022.2156783