Assessing the influence of sleep and sampling time on metabolites in oral fluid: implications for metabolomics studies
Introduction The human salivary metabolome is a rich source of information for metabolomics studies. Among other influences, individual differences in sleep-wake history and time of day may affect the metabolome. Objectives We aimed to characterize the influence of a single night of sleep deprivatio...
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Published in | Metabolomics Vol. 20; no. 5; p. 97 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
07.08.2024
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 1573-3890 1573-3882 1573-3890 |
DOI | 10.1007/s11306-024-02158-3 |
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Summary: | Introduction
The human salivary metabolome is a rich source of information for metabolomics studies. Among other influences, individual differences in sleep-wake history and time of day may affect the metabolome.
Objectives
We aimed to characterize the influence of a single night of sleep deprivation compared to sufficient sleep on the metabolites present in oral fluid and to assess the implications of sampling time points for the design of metabolomics studies.
Methods
Oral fluid specimens of 13 healthy young males were obtained in Salivette
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devices at regular intervals in both a control condition (repeated 8-hour sleep) and a sleep deprivation condition (total sleep deprivation of 8 h, recovery sleep of 8 h) and their metabolic contents compared in a semi-targeted metabolomics approach.
Results
Analysis of variance results showed factor ‘time’ (i.e., sampling time point) representing the major influencer (median 9.24%, range 3.02–42.91%), surpassing the intervention of sleep deprivation (median 1.81%, range 0.19–12.46%). In addition, we found about 10% of all metabolic features to have significantly changed in at least one time point after a night of sleep deprivation when compared to 8 h of sleep.
Conclusion
The majority of significant alterations in metabolites’ abundances were found when sampled in the morning hours, which can lead to subsequent misinterpretations of experimental effects in metabolomics studies. Beyond applying a within-subject design with identical sample collection times, we highly recommend monitoring participants’ sleep-wake schedules prior to and during experiments, even if the study focus is not sleep-related (e.g., via actigraphy). |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1573-3890 1573-3882 1573-3890 |
DOI: | 10.1007/s11306-024-02158-3 |