Insufficient sleep and weekend recovery sleep: classification by a metabolomics-based machine learning ensemble.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
30 Nov 2023
30 Nov 2023
Historique:
received:
30
08
2023
accepted:
23
11
2023
medline:
4
12
2023
pubmed:
1
12
2023
entrez:
30
11
2023
Statut:
epublish
Résumé
Although weekend recovery sleep is common, the physiological responses to weekend recovery sleep are not fully elucidated. Identifying molecular biomarkers that represent adequate versus insufficient sleep could help advance our understanding of weekend recovery sleep. Here, we identified potential molecular biomarkers of insufficient sleep and defined the impact of weekend recovery sleep on these biomarkers using metabolomics in a randomized controlled trial. Healthy adults (n = 34) were randomized into three groups: control (CON: 9-h sleep opportunities); sleep restriction (SR: 5-h sleep opportunities); or weekend recovery (WR: simulated workweek of 5-h sleep opportunities followed by ad libitum weekend recovery sleep and then 2 days with 5-h sleep opportunities). Blood for metabolomics was collected on the simulated Monday immediately following the weekend. Nine machine learning models, including a machine learning ensemble, were built to classify samples from SR versus CON. Notably, SR showed decreased glycerophospholipids and sphingolipids versus CON. The machine learning ensemble showed the highest G-mean performance and classified 50% of the WR samples as insufficient sleep. Our findings show insufficient sleep and recovery sleep influence the plasma metabolome and suggest more than one weekend of recovery sleep may be necessary for the identified biomarkers to return to healthy adequate sleep levels.
Identifiants
pubmed: 38036605
doi: 10.1038/s41598-023-48208-z
pii: 10.1038/s41598-023-48208-z
pmc: PMC10689438
doi:
Substances chimiques
Biomarkers
0
Types de publication
Randomized Controlled Trial
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
21123Subventions
Organisme : NIH HHS
ID : HL109706, HL145099, DK111161, TR001082, DK048520
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK048520
Pays : United States
Organisme : NIDDK NIH HHS
ID : F32 DK111161
Pays : United States
Organisme : NHLBI NIH HHS
ID : K01 HL145099
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL109706
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001082
Pays : United States
Informations de copyright
© 2023. The Author(s).
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