Dataset Information

Leveraging the Metabolic Fingerprint of Sleep Deprivation and Sleep Restriction for Forensic Applications: A Machine Learning Study in Oral Fluid Metabolomics

ABSTRACT:

As sleep loss leads to accidents and impaired safety, a direct metabolic marker would be beneficial for forensic interpretation.

In a sufficiently powered, randomized, controlled, crossover trial under realistic conditions, we examined the salivary metabolome of 20 young men (habitual sleep duration 7–9 h) following three interventions: one night of total sleep deprivation, four consecutive nights of sleep restriction to 6 h, and control (8 h of sleep). Oral fluid specimens were repeatedly collected and analyzed using liquid chromatography coupled to mass spectrometry. Logistic regression models were trained to classify unseen samples without reference samples from the same individual.

Acute sleep deprivation exhibited a unique metabolic fingerprint that could be detected precisely (F0.5 = 0.90) when using only 12 molecular features. This fingerprint was more pronounced in samples collected in the morning/midday hours. Nevertheless, at all time points, the overall correct predictions by far outweighed the incorrect ones. Four nights of sleep restriction did not lead to exploitable metabolic changes.

This study presents a metabolic fingerprint of acute sleep deprivation in oral fluid under realistic conditions and explores practical implications and limitations of its machine learning-aided classification. Metabolomics-based, reference-free sleep loss detection holds potential for applications in forensic, clinical, and occupational contexts.

INSTRUMENT(S): Liquid Chromatography MS - alternating - HILIC

PROVIDER: MTBLS11413 | MetaboLights | 2026-05-21

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	a_MTBLS11413_LC-MS_alternating_hilic_metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS11413_LC-MS_alternating_hilic_metabolite_profiling_v2_maf.tsv	Tabular
	s_MTBLS11413.txt	Txt

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Publications

Leveraging the Metabolic Fingerprint of Sleep Deprivation and Sleep Restriction for Forensic Applications: A Machine Learning Study in Oral Fluid Metabolomics.

Scholz Michael M Steuer Andrea E AE Dobay Akos A Landolt Hans-Peter HP Kraemer Thomas T

Journal of proteome research 20260506

As sleep loss leads to accidents and impaired safety, a direct metabolic marker would be beneficial for forensic interpretation. In a sufficiently powered, randomized, controlled, crossover trial under realistic conditions, we examined the salivary metabolome of 20 young men (habitual sleep duration 7-9 h) following three interventions: one night of total sleep deprivation, four consecutive nights of sleep restriction to 6 h, and control (8 h of sleep). Oral fluid specimens were repeatedly colle ...[more]

PMID: 42090244

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Project description:Extended periods of waking result in physiological impairments in humans, rats, and flies. Sleep homeostasis, the increase in sleep observed following sleep loss, is believed to counter the negative effects of prolonged waking by restoring vital biological processes that are degraded during sleep deprivation. Sleep homeostasis, as with other behaviors, is influenced by both genes and environment. We report here that during periods of starvation, flies remain spontaneously awake but, in contrast to sleep deprivation, do not accrue any of the negative consequences of prolonged waking. Specifically, the homeostatic response and learning impairments that are a characteristic of sleep loss are not observed following prolonged waking induced by starvation. To identify the genes responsible for the protective effects of starvation we conducted transcription profiling of sleep deprived flies that accrue sleep debt compared to starved siblings that do not. Genes involved in lipid metabolism were highly enriched in our dataset of 84 differentially regulated transcripts. Follow up genetic studies established that 6 genes involved in lipid metabolism strongly influence sleep homeostasis. Two of these genes, brummer (bmm) and Lipid storage droplet 2 (Lsd2), are in the same lipolysis pathway but exert antagonistic effects on lipid storage. bmm mutant flies have excess fat stores and display a large homeostatic response following sleep deprivation. In contrast, Lsd2 mutant flies, which phenocopy aspects of starvation as measured by low triglyceride stores, do not exhibit a homeostatic response following sleep loss. Importantly, Lsd2 mutant flies are not learning impaired after sleep deprivation. These results provide the first genetic evidence, to our knowledge, that lipid metabolism plays an important role in regulating the homeostatic response and can protect against neuronal impairments induced by prolonged waking. Two-condition experiments: sleep deprived vs starved. RNA from 8 biological replicates for each condition was pooled in groups of 2 to create 4 samples. Each of the 4 samples is run in duplicate with untreated circadian matched controls.