Effect of sleep deprivation on the human metabolome
Supplementary Material
Author contributions: V.L.R., K.A., M.K., and D.J.S. designed research; S.K.D., J.E.A., V.L.R., B.H., A.M., F.P.R., B.M., and F.I.R. performed research; S.K.D., J.E.A., B.H., N.C., F.I.R., and D.J.S. analyzed data; and S.K.D., J.E.A., V.L.R., K.A., A.E.T., F.I.R., and D.J.S. wrote the paper.
Significance
Sleep restriction and circadian clock disruption are associated with metabolic disorders including obesity and diabetes; this association can be studied by using the powerful tool of metabolomics. By using liquid chromatography/MS metabolomics, we have characterized plasma metabolites that were significantly affected by acute sleep deprivation (mainly lipids and acylcarnitines), all increasing during sleep deprivation. Observed increased levels of serotonin, tryptophan, and taurine may explain the antidepressive effect of sleep deprivation and deserve further study. Clear daily rhythms were observed in most metabolites, with 24 h wakefulness mainly reducing the amplitude of these rhythms. Our results further the understanding of sleep/wake regulation and the associated metabolic processes, and will be vital when using metabolic profiling to identify robust biomarkers for disease states and drug efficacy.
Abstract
Sleep restriction and circadian clock disruption are associated with metabolic disorders such as obesity, insulin resistance, and diabetes. The metabolic pathways involved in human sleep, however, have yet to be investigated with the use of a metabolomics approach. Here we have used untargeted and targeted liquid chromatography (LC)/MS metabolomics to examine the effect of acute sleep deprivation on plasma metabolite rhythms. Twelve healthy young male subjects remained in controlled laboratory conditions with respect to environmental light, sleep, meals, and posture during a 24-h wake/sleep cycle, followed by 24 h of wakefulness. Two-hourly plasma samples collected over the 48 h period were analyzed by LC/MS. Principal component analysis revealed a clear time of day variation with a significant cosine fit during the wake/sleep cycle and during 24 h of wakefulness in untargeted and targeted analysis. Of 171 metabolites quantified, daily rhythms were observed in the majority (n = 109), with 78 of these maintaining their rhythmicity during 24 h of wakefulness, most with reduced amplitude (n = 66). During sleep deprivation, 27 metabolites (tryptophan, serotonin, taurine, 8 acylcarnitines, 13 glycerophospholipids, and 3 sphingolipids) exhibited significantly increased levels compared with during sleep. The increased levels of serotonin, tryptophan, and taurine may explain the antidepressive effect of acute sleep deprivation and deserve further study. This report, to our knowledge the first of metabolic profiling during sleep and sleep deprivation and characterization of 24 h rhythms under these conditions, offers a novel view of human sleep/wake regulation.
Circadian clocks control the timing of most daily biological processes, including cyclic changes in metabolism and the sleep/wake cycle (1). There is a clear link between the circadian timing system and metabolism (2–4), with disrupted circadian rhythms, sleep restriction, and sleep deprivation associated with metabolic disorders (obesity, insulin resistance, diabetes) and cardiovascular disease (5–8). The underlying mechanisms linking metabolic disease, circadian clock misalignment, and sleep restriction are the subject of current research, elucidation of which will require a global “systems” approach (9). Transcriptomic studies have shown that rhythmic gene expression may be affected by sleep restriction, sleep deprivation, and mistimed sleep (10–12), but, as yet, no studies have directly investigated the effect that sleep and sleep deprivation may have on the metabolic profile. Metabolic profiling, or “metabolomics,” is the profiling of small-molecule metabolites and offers the potential to characterize specific metabolic phenotypes associated with disrupted circadian timing and sleep loss. Metabolomics has an advantage over other “omics” techniques, in that it directly samples the metabolic changes in an organism and integrates information from changes at the gene, transcript, and protein levels, as well as posttranslational modification (13). Additionally, metabolomics can provide insight into the combination of genotype and environmental effects, leading to its use in predicting responses to drugs in a “pharmacometabolomic” approach (14, 15).
Daily rhythms have been identified in the metabolomes of mice (16–18) and humans (19). Recent studies conducted in constant routine conditions, in which the impact of exogenous factors such as light, food, posture, and sleep are minimized, have demonstrated endogenous circadian variation in the human metabolome (20, 21), with one study reporting that ∼15% of the metabolites quantified in human plasma and saliva showed circadian variation, particularly amino acids in saliva and fatty acids in plasma (20). These human study protocols aimed to specifically identify circadian variation in the metabolome. However, if metabolic profiling is to be applied in “real-life” clinical settings, and in the identification of robust biomarkers, time-of-day variation in the human metabolome also needs to be characterized, and the effect of sleep, wakefulness, light/dark conditions, and meals on these daily rhythms assessed. Previously, we have characterized significant time of day variation in ∼19% of the metabolite features detected (19). These metabolites included corticosteroids, bilirubin, amino acids, acylcarnitines, and lysophospholipids. Not all of these metabolites, however, have been found to show circadian variation in the constant routine studies (20), suggesting that some metabolites may be affected by light/dark, sleep/wake, or food.
The two-process model of sleep regulation proposes that sleep is driven by a homeostatic component (i.e., process S) and an endogenous circadian oscillator (i.e., process C) (22). The link between the homeostatic and circadian regulation of sleep and metabolic pathways remains ill-defined. Sleep restriction or total sleep deprivation has been shown to reduce the number and the amplitude of genes exhibiting circadian rhythmicity (10, 11, 23). The expression of genes affected by sleep restriction included circadian clock and sleep homeostasis genes, as well those associated with oxidative stress and metabolism. How these changes in the transcriptome translate into changes in the metabolome, however, remains unknown.
Metabolomics can be used not only to study homeostatic regulation but also system perturbations. The metabolic pathways involved in human sleep and during sleep deprivation have not yet been systematically studied by using a metabolomics approach. Since 24 h sleep deprivation primarily affects the homeostatic regulator of sleep, acute total sleep deprivation permits assessment of the metabolic basis of this homeostatic process. The aim of the present study was thus to characterize plasma metabolite rhythms using untargeted and targeted liquid chromatography (LC)/MS metabolomics in healthy male participants during a 24 h wake/sleep cycle followed by 24 h of wakefulness.
Click here to view.Acknowledgments
The authors thank Daniel Barrett, Cheryl Isherwood, and the Surrey Clinical Research Centre medical, clinical, and research teams for their help with the clinical study. This work was supported in part by the Netherlands Forensic Institute, Netherlands Genomics Initiative/Netherlands Organization for Scientific Research within the framework of the Forensic Genomics Consortium Netherlands, the 6th Framework project EUCLOCK (018741), and UK Biotechnology and Biological Sciences Research Council Grant BB/I019405/1. D.J.S. is a Royal Society Wolfson Research Merit Award holder.
Footnotes
Conflict of interest statement: D.J.S. has received research support from Philips Lighting. D.J.S. and B.M. are codirectors of Stockgrand. V.L.R. is a scientific advisor to Lumie and has received research support from Philips Lighting.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1402663111/-/DCSupplemental.
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