Blood-gene expression reveals reduced circadian rhythmicity in individuals resistant to sleep deprivation

TrACES of time: Towards estimating time-of-day of bloodstain deposition by targeted RNA sequencing

In forensic molecular biology, the main task consists of identifying individuals who contributed to biological traces recovered from (potential) crime scenes. However, to support evidence-based reconstruction of the course of activities having taken place at the scene, contextualising information regarding how and when a biological trace was deposited is oftentimes required. Here we present the development of a forensic molecular biological analysis procedure for the prediction of the time-of-day at which a bloodstain has been deposited by targeted quantification of selected mRNA markers. Time-of-day candidate prediction markers with diurnally rhythmic expression have previously been identified by whole transcriptome sequencing. Here, we build on our previous findings by establishing a targeted cDNA sequencing protocol on an Ion S5 massively parallel sequencing device for the targeted gene expression quantification of 69 time-of-day candidate prediction markers. Based on expression measurements of these markers in 408 blood samples (from 51 individuals deposited at eight time points over a day), we establish and compare different statistical methods to predict time of deposition. The most suitable model employing penalised regression achieved a root mean squared error of 3 h and 44 min with 78 % of predictions being correct within ± 4 h (evaluated by five-fold cross-validation), showing pronounced inter-individual differences. While the prediction accuracies of the method in its current state limit its use in the evaluative stage of a criminal trial, the method may nonetheless provide valuable information in the investigative phase. Our study provides the first prediction model for time-of-day of bloodstain deposition based on targeted RNA sequencing and thus represents an important step towards forensic trace deposition timing. It thereby relevantly contributes to the growing knowledge on Transcriptomic Analyses for the Contextualisation of Evidential Stains (TrACES).

Exploratory Analysis of Sleep Deprivation Effects on Gene Expression and Regional Brain Metabolism

Introduction

Sleep deprivation affects cognitive performance and immune function, yet its mechanisms and biomarkers remain unclear. This study explored the relationships among gene expression, brain metabolism, sleep deprivation, and sex differences.

Methods

Fluorodeoxyglucose-18 positron emission tomography measured brain metabolism in regions of interest, and RNA analysis of blood samples assessed gene expression pre- and post-sleep deprivation. Mixed model regression and principal component analysis identified significant genes and regional metabolic changes.

Results

There were 23 and 28 differentially expressed probe sets for the main effects of sex and sleep deprivation, respectively, and 55 probe sets for their interaction (FDR-corrected p < 0.05). Functional analysis of genes affected by sleep deprivation revealed pathway enrichment in nucleoplasm- and UBL conjugation-related genes. Genes with significant sex effects mapped to chromosomes Y and 19 (Benjamini-Hochberg FDR p < 0.05), with 11 genes (4%) and 29 genes (10.5%) involved, respectively. Differential gene expression highlighted sex-based differences in innate and adaptive immunity. For brain metabolism, sleep deprivation resulted in significant decreases in the left insula, left medial prefrontal cortex (BA32), left somatosensory cortex (BA1/2), and left motor premotor cortex (BA6) and increases in the right inferior longitudinal fasciculus, right primary visual cortex (BA17), right amygdala, left cerebellum, and bilateral pons.

Conclusion

Sleep deprivation broadly impacts brain metabolism, gene expression, and immune function, revealing cellular stress responses and hemispheric vulnerability. These findings enhance our understanding of the molecular and functional effects of sleep deprivation.

Glucose Challenge Uncovers Temporal Fungibility of Metabolic Homeostasis over a day:night cycle

Rhythmicity is a cornerstone of behavioral and biological processes, especially metabolism, yet the mechanisms behind metabolite cycling remain elusive. This study uncovers a robust oscillation in key metabolite pathways downstream of glucose in humans. A purpose-built 13C6-glucose isotope tracing platform was used to sample Drosophila every 4h and probe these pathways, revealing a striking peak in biosynthesis shortly after lights-on in wild-type flies. A hyperactive mutant (fumin) demonstrates increased Krebs cycle labelling and dawn-specific glycolysis labelling. Surprisingly, neither underlying feeding rhythms nor the presence of food availability explain the rhythmicity of glucose processing across genotypes, suggesting a robust internal mechanism for metabolic control of glucose processing. These results align with clinical data highlighting detrimental effects of mistimed energy intake. Our approach offers a unique insight into the dynamic range of daily metabolic processing and provides a mechanistic foundation for exploring circadian metabolic homeostasis in disease contexts.

tauFisher predicts circadian time from a single sample of bulk and single-cell pseudobulk transcriptomic data

As the circadian clock regulates fundamental biological processes, disrupted clocks are often observed in patients and diseased tissues. Determining the circadian time of the patient or the tissue of focus is essential in circadian medicine and research. Here we present tauFisher, a computational pipeline that accurately predicts circadian time from a single transcriptomic sample by finding correlations between rhythmic genes within the sample. We demonstrate tauFisher's performance in adding timestamps to both bulk and single-cell transcriptomic samples collected from multiple tissue types and experimental settings. Application of tauFisher at a cell-type level in a single-cell RNAseq dataset collected from mouse dermal skin implies that greater circadian phase heterogeneity may explain the dampened rhythm of collective core clock gene expression in dermal immune cells compared to dermal fibroblasts. Given its robustness and generalizability across assay platforms, experimental setups, and tissue types, as well as its potential application in single-cell RNAseq data analysis, tauFisher is a promising tool that facilitates circadian medicine and research.

Investigation of the shared biological mechanisms and common biomarker APTAF1 of sleep deprivation and mild cognitive impairment using integrated bioinformatics analysis

Introduction: The relationship between sleep loss and cognitive impairment has long been widely recognized, but there is still a lack of complete understanding of the underlying mechanisms and potential biomarkers. The purpose of this study is to further explore the shared biological mechanisms and common biomarkers between sleep loss and cognitive impairment. Methods: The mitochondria-related genes and gene expression data were downloaded from the MitoCarta3.0 and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed mitochondrial-related genes by combing the differentially expressed genes (DEGs) in sleep deprivation (SD) and mild cognitive impairment (MCI) datasets with mitochondria-related gene lists. Shared DEGs were then further analyzed for enrichment analysis. Next, the common biomarker was identified using two machine learning techniques and further validated using two independent GEO datasets. Then GSEA and GSVA were conducted to analyze the functional categories and pathways enriched for the common biomarker. Finally, immune infiltration analysis was used to investigate the correlation of immune cell infiltration with the common biomarker in SD and MCI. Results: A total of 32 mitochondrial-related differentially expressed genes were identified in SD and MCI. GO analysis indicated that these genes were significantly enriched for mitochondrial transport, and KEGG analysis showed they were mainly involved in pathways of neurodegenerative diseases. In addition, ATPAF1, which was significantly down-regulated in both SD and MCI, was identified through machine learning algorithms as the common biomarker with favorable diagnostic performance. GSEA and GSVA revealed that ATPAF1 was mainly involved in metabolic pathways, such as oxidative phosphorylation, acetylcholine metabolic process, valine, leucine and isoleucine degradation. Immune infiltration analysis showed that the expression of ATPAF1 was correlated with changes in immune cells, especially those key immune cell types associated with SD and MCI. Discussion: This study firstly revealed that mitochondrial dysfunction may be the common pathogenesis of sleep loss and mild cognitive impairment and identified ATPAF1 as a possible biomarker and therapeutic target involved in SD and MCI.

Sleep quality and associated factors among university students in Africa: a systematic review and meta-analysis study

Background

Poor sleep quality significantly impacts academic performance in university students. However, inconsistent and inconclusive results were found in a study on sleep among university students in several African nations. Therefore, this study aimed to estimate the pooled prevalence and associated factors of poor sleep quality among university students in Africa.

Methods

The databases PubMed, Scopus, Cochrane Library, Science Direct, African Journal Online, and Google Scholar were searched to identify articles. A total of 35 primary articles from 11 African countries were assessed and included in this systematic review and meta-analysis. Data were extracted by using a Microsoft Excel spreadsheet and exported to STATA version 14 for analysis. The I2 test was used to assess the statistical heterogeneity. A random effect meta-analysis model was employed with 95% confidence intervals. Funnel plots analysis and Egger regression tests were used to check the presence of publication bias. A subgroup analysis and a sensitivity analysis were done.

Results

A total of 16,275 study participants from 35 studies were included in this meta-analysis and systematic review. The overall pooled prevalence of poor sleep quality among university students in Africa was 63.31% (95% CI: 56.91-65.71) I2 = 97.2. The subgroup analysis shows that the combined prevalence of poor sleep quality in East, North, West, and South Africa were 61.31 (95% CI: 56.91-65.71), 62.23 (95% CI: 54.07-70.39), 54.43 (95% CI: 47.39-61.48), and 69.59 (95% CI: 50.39-88.80) respectively. Being stressed (AOR= 2.39; 95% CI: 1.63 to 3.51), second academic year (AOR= 3.10; 95% CI: 2.30 to 4.19), use of the electronic device at bedtime (AOR= 3.97 95% CI: 2.38 to 6.61)) and having a comorbid chronic illness (AOR = 2.71; 95% CI: 1.08, 6.82) were factors significantly associated with poor sleep quality.

Conclusion

This study shows that there is a high prevalence of poor sleep quality among university students in Africa. Being stressed, in the second year, using electronic devices at bedtime, and having chronic illness were factors associated with poor sleep quality. Therefore, addressing contributing factors and implementing routine screenings are essential to reduce the burden of poor sleep quality.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023493140.

Accurate detection of acute sleep deprivation using a metabolomic biomarker-A machine learning approach

Sleep deprivation enhances risk for serious injury and fatality on the roads and in workplaces. To facilitate future management of these risks through advanced detection, we developed and validated a metabolomic biomarker of sleep deprivation in healthy, young participants, across three experiments. Bi-hourly plasma samples from 2 × 40-hour extended wake protocols (for train/test models) and 1 × 40-hour protocol with an 8-hour overnight sleep interval were analyzed by untargeted liquid chromatography-mass spectrometry. Using a knowledge-based machine learning approach, five consistently important variables were used to build predictive models. Sleep deprivation (24 to 38 hours awake) was predicted accurately in classification models [versus well-rested (0 to 16 hours)] (accuracy = 94.7%/AUC 99.2%, 79.3%/AUC 89.1%) and to a lesser extent in regression (R2 = 86.1 and 47.8%) models for within- and between-participant models, respectively. Metabolites were identified for replicability/future deployment. This approach for detecting acute sleep deprivation offers potential to reduce accidents through "fitness for duty" or "post-accident analysis" assessments.

Platform-independent estimation of human physiological time from single blood samples

Abundant epidemiological evidence links circadian rhythms to human health, from heart disease to neurodegeneration. Accurate determination of an individual's circadian phase is critical for precision diagnostics and personalized timing of therapeutic interventions. To date, however, we still lack an assay for physiological time that is accurate, minimally burdensome to the patient, and readily generalizable to new data. Here, we present TimeMachine, an algorithm to predict the human circadian phase using gene expression in peripheral blood mononuclear cells from a single blood draw. Once trained on data from a single study, we validated the trained predictor against four independent datasets with distinct experimental protocols and assay platforms, demonstrating that it can be applied generalizably. Importantly, TimeMachine predicted circadian time with a median absolute error ranging from 1.65 to 2.7 h, regardless of systematic differences in experimental protocol and assay platform, without renormalizing the data or retraining the predictor. This feature enables it to be flexibly applied to both new samples and existing data without limitations on the transcriptomic profiling technology (microarray, RNAseq). We benchmark TimeMachine against competing approaches and identify the algorithmic features that contribute to its performance.

Plasma and cerebrospinal fluid proteomic signatures of acutely sleep-deprived humans: an exploratory study

STUDY OBJECTIVES

Acute sleep deprivation affects both central and peripheral biological processes. Prior research has mainly focused on specific proteins or biological pathways that are dysregulated in the setting of sustained wakefulness. This exploratory study aimed to provide a comprehensive view of the biological processes and proteins impacted by acute sleep deprivation in both plasma and cerebrospinal fluid (CSF).

METHODS

We collected plasma and CSF from human participants during one night of sleep deprivation and controlled normal sleep conditions. One thousand and three hundred proteins were measured at hour 0 and hour 24 using a high-scale aptamer-based proteomics platform (SOMAscan) and a systematic biological database tool (Metascape) was used to reveal altered biological pathways.

RESULTS

Acute sleep deprivation decreased the number of upregulated and downregulated biological pathways and proteins in plasma but increased upregulated and downregulated biological pathways and proteins in CSF. Predominantly affected proteins and pathways were associated with immune response, inflammation, phosphorylation, membrane signaling, cell-cell adhesion, and extracellular matrix organization.

CONCLUSIONS

The identified modifications across biofluids add to evidence that acute sleep deprivation has important impacts on biological pathways and proteins that can negatively affect human health. As a hypothesis-driving study, these findings may help with the exploration of novel mechanisms that mediate sleep loss and associated conditions, drive the discovery of new sleep loss biomarkers, and ultimately aid in the identification of new targets for intervention to human diseases.

tauFisher accurately predicts circadian time from a single sample of bulk and single-cell transcriptomic data

As the circadian clock regulates fundamental biological processes, disrupted clocks are often observed in patients and diseased tissues. Determining the circadian time of the patient or the tissue of focus is essential in circadian medicine and research. Here we present tau-Fisher, a computational pipeline that accurately predicts circadian time from a single transcriptomic sample by finding correlations between rhythmic genes within the sample. We demonstrate tauFisher's out-standing performance in both bulk and single-cell transcriptomic data collected from multiple tissue types and experimental settings. Application of tauFisher at a cell-type level in a single-cell RNA-seq dataset collected from mouse dermal skin implies that greater circadian phase heterogeneity may explain the dampened rhythm of collective core clock gene expression in dermal immune cells compared to dermal fibroblasts. Given its robustness and generalizability across assay platforms, experimental setups, and tissue types, as well as its potential application in single-cell RNA-seq data analysis, tauFisher is a promising tool that facilitates circadian medicine and research.

TrACES of time: Transcriptomic analyses for the contextualization of evidential stains - Identification of RNA markers for estimating time-of-day of bloodstain deposition

Obtaining forensically relevant information beyond who deposited a biological stain on how and under which circumstances it was deposited is a question of increasing importance in forensic molecular biology. In the past few years, several studies have been produced on the potential of gene expression analysis to deliver relevant contextualizing information, e.g. on nature and condition of a stain as well as aspects of stain deposition timing. However, previous attempts to predict the time-of-day of sample deposition were all based on and thus limited by previously described diurnal oscillators. Herein, we newly approached this goal by applying current sequencing technologies and statistical methods to identify novel candidate markers for forensic time-of-day predictions from whole transcriptome analyses. To this purpose, we collected whole blood samples from ten individuals at eight different time points throughout the day, performed whole transcriptome sequencing and applied biostatistical algorithms to identify 81 mRNA markers with significantly differential expression as candidates to predict the time of day. In addition, we performed qPCR analysis to assess the characteristics of a subset of 13 candidate predictors in dried and aged blood stains. While we demonstrated the general possibility of using the selected candidate markers to predict time-of-day of sample deposition, we also observed notable variation between different donors and storage conditions, highlighting the relevance of employing accurate quantification methods in combination with robust normalization procedures.This study's results are foundational and may be built upon when developing a targeted assay for time-of-day predictions from forensic blood samples in the future.

FABP7: a glial integrator of sleep, circadian rhythms, plasticity, and metabolic function

Sleep and circadian rhythms are observed broadly throughout animal phyla and influence neural plasticity and cognitive function. However, the few phylogenetically conserved cellular and molecular pathways that are implicated in these processes are largely focused on neuronal cells. Research on these topics has traditionally segregated sleep homeostatic behavior from circadian rest-activity rhythms. Here we posit an alternative perspective, whereby mechanisms underlying the integration of sleep and circadian rhythms that affect behavioral state, plasticity, and cognition reside within glial cells. The brain-type fatty acid binding protein, FABP7, is part of a larger family of lipid chaperone proteins that regulate the subcellular trafficking of fatty acids for a wide range of cellular functions, including gene expression, growth, survival, inflammation, and metabolism. FABP7 is enriched in glial cells of the central nervous system and has been shown to be a clock-controlled gene implicated in sleep/wake regulation and cognitive processing. FABP7 is known to affect gene transcription, cellular outgrowth, and its subcellular localization in the fine perisynaptic astrocytic processes (PAPs) varies based on time-of-day. Future studies determining the effects of FABP7 on behavioral state- and circadian-dependent plasticity and cognitive processes, in addition to functional consequences on cellular and molecular mechanisms related to neural-glial interactions, lipid storage, and blood brain barrier integrity will be important for our knowledge of basic sleep function. Given the comorbidity of sleep disturbance with neurological disorders, these studies will also be important for our understanding of the etiology and pathophysiology of how these diseases affect or are affected by sleep.

The parasite intraerythrocytic cycle and human circadian cycle are coupled during malaria infection

During infections with the malaria parasites Plasmodium vivax, patients exhibit rhythmic fevers every 48 h. These fever cycles correspond with the time the parasites take to traverse the intraerythrocytic cycle (IEC). In other Plasmodium species that infect either humans or mice, the IEC is likely guided by a parasite-intrinsic clock [Rijo-Ferreiraet al., Science 368, 746-753 (2020); Smith et al., Science 368, 754-759 (2020)], suggesting that intrinsic clock mechanisms may be a fundamental feature of malaria parasites. Moreover, because Plasmodium cycle times are multiples of 24 h, the IECs may be coordinated with the host circadian clock(s). Such coordination could explain the synchronization of the parasite population in the host and enable alignment of IEC and circadian cycle phases. We utilized an ex vivo culture of whole blood from patients infected with P. vivax to examine the dynamics of the host circadian transcriptome and the parasite IEC transcriptome. Transcriptome dynamics revealed that the phases of the host circadian cycle and the parasite IEC are correlated across multiple patients, showing that the cycles are phase coupled. In mouse model systems, host-parasite cycle coupling appears to provide a selective advantage for the parasite. Thus, understanding how host and parasite cycles are coupled in humans could enable antimalarial therapies that disrupt this coupling.

The role of the circadian clock in the development, progression, and treatment of non-alcoholic fatty liver disease

The circadian clock comprises a cellular endogenous timing system coordinating the alignment of physiological processes with geophysical time. Disruption of circadian rhythms has been associated with several metabolic diseases. In this review, we focus on liver as a major metabolic tissue and one of the most well-studied organs with regard to circadian regulation. We summarize current knowledge about the role of local and systemic clocks and rhythms in regulating biological functions of the liver. We discuss how the disruption of circadian rhythms influences the development of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). We also critically evaluate whether NAFLD/NASH may in turn result in chronodisruption. The last chapter focuses on potential roles of the clock system in prevention and treatment of NAFLD/NASH and the interaction of current NASH drug candidates with liver circadian rhythms and clocks. It becomes increasingly clear that paying attention to circadian timing may open new avenues for the optimization of NAFLD/NASH therapies and provide interesting targets for prevention and treatment of these increasingly prevalent disorders.

Sex Inclusion in Transcriptome Studies of Daily Rhythms

Biomedical research on mammals has traditionally neglected females, raising the concern that some scientific findings may generalize poorly to half the population. Although this lack of sex inclusion has been broadly documented, its extent within circadian genomics remains undescribed. To address this gap, we examined sex inclusion practices in a comprehensive collection of publicly available transcriptome studies on daily rhythms. Among 148 studies having samples from mammals in vivo, we found strong underrepresentation of females across organisms and tissues. Overall, only 23 of 123 studies in mice, 0 of 10 studies in rats, and 9 of 15 studies in humans included samples from females. In addition, studies having samples from both sexes tended to have more samples from males than from females. These trends appear to have changed little over time, including since 2016, when the US National Institutes of Health began requiring investigators to consider sex as a biological variable. Our findings highlight an opportunity to dramatically improve representation of females in circadian research and to explore sex differences in daily rhythms at the genome level.

An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling

Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women's Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.

Circadian medicine for aging attenuation and sleep disorders: Prospects and challenges

Aging causes progressive deterioration of daily rhythms in behavioral and metabolic processes and disruption in the regular sleep-wake cycle. Circadian disruption is directly related to diverse age-induced health abnormalities. Rising evidence from various organisms shows that core clock gene mutations cause premature aging, reduced lifespan, and sleeping irregularities. Improving the clock functions and correcting its disruption by pharmacological interventions or time-regulated feeding patterns could be a novel avenue for effective clinical management of aging and sleep disorders. To this end, many drugs for sleep disorders and anti-aging compounds interact with the core clock machinery and alter the circadian output. Evaluation of dosing time-dependency and circadian regulation of drug metabolism for therapeutic improvement of the existing drugs is another fundamental facet of chronomedicine. Multiple studies have demonstrated dose-dependent manipulation of the circadian period and phase-shifting by pharmacologically active compounds. The chronobiology research field is gradually moving towards the development of novel therapeutic strategies based on targeting the molecular clock or dosing time-oriented medications. However, such translational research ventures would require more experimental evidence from studies on humans. This review discusses the impact of circadian rhythms on aging and sleep, emphasizing the potentiality of circadian medicine in aging attenuation and sleep disorders.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Is it time for chronopharmacology in NASH?

Liver homeostasis is strongly influenced by the circadian clock, an evolutionarily conserved mechanism synchronising physiology and behaviour across a 24-hour cycle. Disruption of the clock has been heavily implicated in the pathogenesis of metabolic dysfunction including non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH). Furthermore, many of the current NASH drug candidates specifically target pathways known to be under circadian control including fatty acid synthesis and signalling via the farnesoid X receptor, fibroblast growth factor 19 and 21, peroxisome proliferator-activated receptor α and γ, glucagon-like peptide 1, and the thyroid hormone receptor. Despite this, there has been little consideration of the application of chronopharmacology in NASH, a strategy whereby the timing of drug delivery is informed by biological rhythms in order to maximise efficacy and tolerability. Chronopharmacology has been shown to have significant clinical benefits in a variety of settings including cardiovascular disease and cancer therapy. The rationale for its application in NASH is therefore compelling. However, no clinical trials in NASH have specifically explored the impact of drug timing on disease progression and patient outcomes. This may contribute to the wide variability in reported outcomes of NASH trials and partly explain why even late-phase trials have stalled because of a lack of efficacy or safety concerns. In this opinion piece, we describe the potential for chronopharmacology in NASH, discuss how the major NASH drug candidates are influenced by circadian biology, and encourage greater consideration of the timing of drug administration in the design of future clinical trials.

Disturbance of the Circadian System in Shift Work and Its Health Impact

The various non-standard schedules required of shift workers force abrupt changes in the timing of sleep and light-dark exposure. These changes result in disturbances of the endogenous circadian system and its misalignment with the environment. Simulated night-shift experiments and field-based studies with shift workers both indicate that the circadian system is resistant to adaptation from a day- to a night-oriented schedule, as determined by a lack of substantial phase shifts over multiple days in centrally controlled rhythms, such as those of melatonin and cortisol. There is evidence that disruption of the circadian system caused by night-shift work results not only in a misalignment between the circadian system and the external light-dark cycle, but also in a state of internal desynchronization between various levels of the circadian system. This is the case between rhythms controlled by the central circadian pacemaker and clock genes expression in tissues such as peripheral blood mononuclear cells, hair follicle cells, and oral mucosa cells. The disruptive effects of atypical work schedules extend beyond the expression profile of canonical circadian clock genes and affects other transcripts of the human genome. In general, after several days of living at night, most rhythmic transcripts in the human genome remain adjusted to a day-oriented schedule, with dampened group amplitudes. In contrast to circadian clock genes and rhythmic transcripts, metabolomics studies revealed that most metabolites shift by several hours when working nights, thus leading to their misalignment with the circadian system. Altogether, these circadian and sleep-wake disturbances emphasize the all-encompassing impact of night-shift work, and can contribute to the increased risk of various medical conditions. Here, we review the latest scientific evidence regarding the effects of atypical work schedules on the circadian system, sleep and alertness of shift-working populations, and discuss their potential clinical impacts.

Gene co-expression analysis identifies modules related to insufficient sleep in humans

BACKGROUND

Insufficient sleep and circadian rhythm disruption may cause cancer, obesity, cardiovascular disease, and cognitive impairment. The underlying mechanisms need to be elucidated.

METHOD

Weighted gene co-expression network analysis (WGCNA) was used to identify co-expressed modules. Connectivity Map tool was used to identify candidate drugs based on top connected genes. R ptestg package was utilized to detected module rhythmicity alteration. A hypergeometric test was used to test the enrichment of insomnia SNP signals in modules. Google Scholar was used to validate the modules and hub genes by literature.

RESULTS

We identified a total of 45 co-expressed modules. These modules were stable and preserved. Eight modules were correlated with sleep restriction duration. Module rhythmicity was disrupted in sleep restriction subjects. Hub genes that involve in insufficient sleep also play important roles in sleep disorders. Insomnia GWAS signals were enriched in six modules. Finally, eight drugs associated with sleep disorders were identified.

CONCLUSION

Systems biology method was used to identify sleep-related modules, hub genes, and candidate drugs. Module rhythmicity was altered in sleep insufficient subjects. Thiamphenicol, lisuride, timolol, and piretanide are novel candidates for sleep disorders.

A Study on the Mechanism of Lavender in the Treatment of Insomnia Based on Network Pharmacology

AIMS AND OBJECTIVE

The common disease of insomnia has complex and diverse clinical manifestations. Lavender represents an effective treatment of insomnia, but the molecular mechanism underlying the effectiveness of this treatment is not clear. The purpose of this study is to investigate the active components, target proteins and molecular pathways of lavender in the treatment of insomnia, thus explaining its possible mechanism.

MATERIALS AND METHODS

Firstly, 54 active components of lavender were identified by gas chromatography-mass spectrometry (GC-MS). The target protein of lavender was predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and the target protein of insomnia was predicted by the DisGeNET and DrugBank databases. Then, the "component-target-disease" network diagram was constructed using the Cytoscape 3.7.1 software. KEGG and GO enrichments were analyzed using the R statistical language. Finally, the key target proteins were verified by collecting and verifying the target protein GEO data using the Discovery Studio 3.5 molecular docking verification software.

RESULTS

906 target proteins of lavender were predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and 182 insomnia target proteins were predicted by the DisGeNET and DrugBank databases. The results of GO enrichment analysis showed that it included the reaction process of ammonium ion, the regulation of the membrane potential and the secretion of catecholamine, while the results of KEGG enrichment included the calcium signaling pathway, serotonin synapse, morphine addiction and many more. Finally, using the Discovery Studio3.5 molecular docking verification software, it was verified that the key target proteins are ADRB1 and HLA-DRB1.

CONCLUSION

The components in the lavender essential oil include the Ethyl 2-(5-methyl-5-vinyltetrahydrofuran- 2-yl)propan-2-ylcarbonate (0.774); 5-Oxatricyclo[8.2.0.04,6]dodecane, 4,12,12-trimethyl- 9-methylene-, (1R,4R,6R,10S)-(0.147); P-Cymen-7-ol (0.063); .alpha-Humulenem (0.317); Acetic acid, hexyl ester (1.374); etc. The role lavender plays in the treatment of insomnia might be accomplished through the regulation of the key targets ADRB1 and HLA-DRB1.

Minimally Invasive Ways of Determining Circadian Rhythms in Humans

Circadian rhythm exerts a critical role in mammalian health and disease. A malfunctioning circadian clock can be a consequence, as well as the cause of several pathophysiologies. Clinical therapies and research may also be influenced by the clock. Since the most suitable manner of revealing this rhythm in humans is not yet established, we discuss existing methods and seek to determine the most feasible ones.

Prolonged, Controlled Daytime versus Delayed Eating Impacts Weight and Metabolism

A delayed eating schedule is associated with increased risk of obesity and metabolic dysfunction in humans.^1-9 However, there are no prolonged, highly controlled experimental studies testing the effects of meal timing on weight and metabolism in adults with a body mass index (BMI) of 19-27 kg/m².^10-18 Twelve healthy adults (age: 26.3 ± 3.4 years; BMI: 21.9 ± 1.7 kg/m²; 5 females) participated in a randomized crossover study in free-living conditions. Three meals and two snacks with comparable energy and macronutrient contents were provided during two, 8-week, counterbalanced conditions separated by a 2-week washout period: (1) daytime (intake limited to 0800 h-1900 h) and (2) delayed (intake limited to 1200 h-2300 h). Sleep-wake cycles and exercise levels were held constant. Weight, adiposity, energy expenditure, and circadian profiles of hormones and metabolites were assessed during four inpatient visits occurring before and after each condition. Body weight, insulin resistance (homeostatic model assessment of insulin resistance [HOMA-IR]), trunk-to-leg fat ratio, resting energy expenditure, respiratory quotient, and fasting glucose, insulin, total and high-density lipoprotein (dHDL) cholesterol, and adiponectin decreased on the daytime compared to the delayed schedule. These measures, as well as triglycerides, increased on the delayed compared to the daytime schedule (effect size range: d = 0.397-1.019). Circadian phase and amplitude of melatonin, cortisol, ghrelin, leptin, and glucose were not differentially altered by the eating schedules. Overall, an 8-week daytime eating schedule, compared to a delayed eating schedule, promotes weight loss and improvements in energy metabolism and insulin in adults with BMI 19-27 kg/m², underscoring the efficacy and feasibility of daytime eating as a behavioral modification for real-world conditions.

Novel Approaches for Assessing Circadian Rhythmicity in Humans: A Review

The temporal organization of molecular and physiological processes is driven by environmental and behavioral cycles as well as by self-sustained molecular circadian oscillators. Quantification of phase, amplitude, period, and disruption of circadian oscillators is essential for understanding their contribution to sleep-wake disorders, social jet lag, interindividual differences in entrainment, and the development of chrono-therapeutics. Traditionally, assessment of the human circadian system, and the output of the SCN in particular, has required collection of long time series of univariate markers such as melatonin or core body temperature. Data were collected in specialized laboratory protocols designed to control for environmental and behavioral influences on rhythmicity. These protocols are time-consuming, expensive, and not practical for assessing circadian status in patients or in participants in epidemiologic studies. Novel approaches for assessment of circadian parameters of the SCN or peripheral oscillators have been developed. They are based on machine learning or mathematical model-informed analyses of features extracted from 1 or a few samples of high-dimensional data, such as transcriptomes, metabolomes, long-term simultaneous recording of activity, light exposure, skin temperature, and heart rate or in vitro approaches. Here, we review whether these approaches successfully quantify parameters of central and peripheral circadian oscillators as indexed by gold standard markers. Although several approaches perform well under entrained conditions when sleep occurs at night, the methods either perform worse in other conditions such as shift work or they have not been assessed under any conditions other than entrainment and thus we do not yet know how robust they are. Novel approaches for the assessment of circadian parameters hold promise for circadian medicine, chrono-therapeutics, and chrono-epidemiology. There remains a need to validate these approaches against gold standard markers, in individuals of all sexes and ages, in patient populations, and, in particular, under conditions in which behavioral cycles are displaced.

Genome-wide circadian regulation: A unique system for computational biology

Circadian rhythms are 24-hour oscillations affecting an organism at multiple levels from gene expression all the way to tissues and organs. They have been observed in organisms across the kingdom of life, spanning from cyanobacteria to humans. In mammals, the master circadian pacemaker is located in the hypothalamic suprachiasmatic nuclei (SCN) in the brain where it synchronizes the peripheral oscillators that exist in other tissues. This system regulates the circadian activity of a large part of the transcriptome and recent findings indicate that almost every cell in the body has this clock at the molecular level. In this review, we briefly summarize the different factors that can influence the circadian transcriptome, including light, temperature, and food intake. We then summarize recently identified general principles governing genome-scale circadian regulation, as well as future lines of research. Genome-scale circadian activity represents a fascinating study model for computational biology. For this purpose, systems biology methods are promising exploratory tools to decode the global regulatory principles of circadian regulation.

Longitudinal RNA-Seq Analysis of the Repeatability of Gene Expression and Splicing in Human Platelets Identifies a Platelet SELP Splice QTL

RATIONALE

Longitudinal studies are required to distinguish within versus between-individual variation and repeatability of gene expression. They are uniquely positioned to decipher genetic signal from environmental noise, with potential application to gene variant and expression studies. However, longitudinal analyses of gene expression in healthy individuals-especially with regards to alternative splicing-are lacking for most primary cell types, including platelets.

OBJECTIVE

To assess repeatability of gene expression and splicing in platelets and use repeatability to identify novel platelet expression quantitative trait loci (QTLs) and splice QTLs.

METHODS AND RESULTS

We sequenced the transcriptome of platelets isolated repeatedly up to 4 years from healthy individuals. We examined within and between individual variation and repeatability of platelet RNA expression and exon skipping, a readily measured alternative splicing event. We find that platelet gene expression is generally stable between and within-individuals over time-with the exception of a subset of genes enriched for the inflammation gene ontology. We show an enrichment among repeatable genes for associations with heritable traits, including known and novel platelet expression QTLs. Several exon skipping events were also highly repeatable, suggesting heritable patterns of splicing in platelets. One of the most repeatable was exon 14 skipping of SELP. Accordingly, we identify rs6128 as a platelet splice QTL and define an rs6128-dependent association between SELP exon 14 skipping and race. In vitro experiments demonstrate that this single nucleotide variant directly affects exon 14 skipping and changes the ratio of transmembrane versus soluble P-selectin protein production.

CONCLUSIONS

We conclude that the platelet transcriptome is generally stable over 4 years. We demonstrate the use of repeatability of gene expression and splicing to identify novel platelet expression QTLs and splice QTLs. rs6128 is a platelet splice QTL that alters SELP exon 14 skipping and soluble versus transmembrane P-selectin protein production.

Identifying and validating blood mRNA biomarkers for acute and chronic insufficient sleep in humans: a machine learning approach

Acute and chronic insufficient sleep are associated with adverse health outcomes and risk of accidents. There is therefore a need for biomarkers to monitor sleep debt status. None are currently available. We applied elastic net and ridge regression to transcriptome samples collected in 36 healthy young adults during acute total sleep deprivation and following 1 week of either chronic insufficient (<6 hr) or sufficient sleep (~8.6 hr) to identify panels of mRNA biomarkers of sleep debt status. The size of identified panels ranged from 9 to 74 biomarkers. Panel performance, assessed by leave-one-subject-out cross-validation and independent validation, varied between sleep debt conditions. Using between-subject assessments based on one blood sample, the accuracy of classifying "acute sleep loss" was 92%, but only 57% for classifying "chronic sleep insufficiency." A reasonable accuracy for classifying "chronic sleep insufficiency" could only be achieved by a within-subject comparison of blood samples. Biomarkers for sleep debt status showed little overlap with previously identified biomarkers for circadian phase. Biomarkers for acute and chronic sleep loss also showed little overlap but were associated with common functions related to the cellular stress response, such as heat shock protein activity, the unfolded protein response, protein ubiquitination and endoplasmic reticulum-associated protein degradation, and apoptosis. This characteristic response of whole blood to sleep loss can further aid our understanding of how sleep insufficiencies negatively affect health. Further development of these novel biomarkers for research and clinical practice requires validation in other protocols and age groups.

Sleep-wake-driven and circadian contributions to daily rhythms in gene expression and chromatin accessibility in the murine cortex

The timing and duration of sleep results from the interaction between a homeostatic sleep-wake-driven process and a periodic circadian process, and involves changes in gene regulation and expression. Unraveling the contributions of both processes and their interaction to transcriptional and epigenomic regulatory dynamics requires sampling over time under conditions of unperturbed and perturbed sleep. We profiled mRNA expression and chromatin accessibility in the cerebral cortex of mice over a 3-d period, including a 6-h sleep deprivation (SD) on day 2. We used mathematical modeling to integrate time series of mRNA expression data with sleep-wake history, which established that a large proportion of rhythmic genes are governed by the homeostatic process with varying degrees of interaction with the circadian process, sometimes working in opposition. Remarkably, SD caused long-term effects on gene-expression dynamics, outlasting phenotypic recovery, most strikingly illustrated by a damped oscillation of most core clock genes, including Arntl/Bmal1, suggesting that enforced wakefulness directly impacts the molecular clock machinery. Chromatin accessibility proved highly plastic and dynamically affected by SD. Dynamics in distal regions, rather than promoters, correlated with mRNA expression, implying that changes in expression result from constitutively accessible promoters under the influence of enhancers or repressors. Serum response factor (SRF) was predicted as a transcriptional regulator driving immediate response, suggesting that SRF activity mirrors the build-up and release of sleep pressure. Our results demonstrate that a single, short SD has long-term aftereffects at the genomic regulatory level and highlights the importance of the sleep-wake distribution to diurnal rhythmicity and circadian processes.

Folic Acid Supplementation Suppresses Sleep Deprivation-Induced Telomere Dysfunction and Senescence-Associated Secretory Phenotype (SASP)

Sleep deprivation is reported to cause oxidative stress and is hypothesized to induce subsequent aging-related diseases including chronic inflammation, Alzheimer's disease, and cardiovascular disease. However, how sleep deprivation contributes to the pathogenesis of sleep deficiency disorder remains incompletely defined. Accordingly, more effective treatment methods for sleep deficiency disorder are needed. Thus, to better understand the detailed mechanism of sleep deficiency disorder, a sleep deprivation mouse model was established by the multiple platform method in our study. The accumulation of free radicals and senescence-associated secretory phenotype (SASP) was observed in the sleep-deprived mice. Moreover, our mouse and human population-based study both demonstrated that telomere shortening and the formation of telomere-specific DNA damage are dramatically increased in individuals suffering from sleeplessness. To our surprise, the secretion of senescence-associated cytokines and telomere damage are greatly improved by folic acid supplementation in mice. Individuals with high serum baseline folic acid levels have increased resistance to telomere shortening, which is induced by insomnia. Thus, we conclude that folic acid supplementation could be used to effectively counteract sleep deprivation-induced telomere dysfunction and the associated aging phenotype, which may potentially improve the prognosis of sleeplessness disorder patients.

Circadian and wake-dependent changes in human plasma polar metabolites during prolonged wakefulness: A preliminary analysis

Establishing circadian and wake-dependent changes in the human metabolome are critical for understanding and treating human diseases due to circadian misalignment or extended wake. Here, we assessed endogenous circadian rhythms and wake-dependent changes in plasma metabolites in 13 participants (4 females) studied during 40-hours of wakefulness. Four-hourly plasma samples were analyzed by hydrophilic interaction liquid chromatography (HILIC)-LC-MS for 1,740 metabolite signals. Group-averaged (relative to DLMO) and individual participant metabolite profiles were fitted with a combined cosinor and linear regression model. In group-level analyses, 22% of metabolites were rhythmic and 8% were linear, whereas in individual-level analyses, 14% of profiles were rhythmic and 4% were linear. We observed metabolites that were significant at the group-level but not significant in a single individual, and metabolites that were significant in approximately half of individuals but not group-significant. Of the group-rhythmic and group-linear metabolites, only 7% and 12% were also significantly rhythmic or linear, respectively, in ≥50% of participants. Owing to large inter-individual variation in rhythm timing and the magnitude and direction of linear change, acrophase and slope estimates also differed between group- and individual-level analyses. These preliminary findings have important implications for biomarker development and understanding of sleep and circadian regulation of metabolism.

Shift Work Disrupts Circadian Regulation of the Transcriptome in Hospital Nurses

Circadian misalignment between sleep and behavioral/feeding rhythms is thought to lead to various health impairments in shift workers. Therefore, we investigated how shift work leads to genome-wide circadian dysregulation in hospital nurses. Female nurses from the University of Alabama at Birmingham (UAB) Hospital working night shift ( n = 9; 29.6 ± 11.4 y) and day shift ( n = 8; 34.9 ± 9.4 y) participated in a 9-day study measuring locomotor activity and core body temperature (CBT) continuously. Additionally, cortisol and melatonin were assayed and peripheral blood mononuclear cells (PBMCs) were harvested for RNA extraction every 3 h on a day off from work. We saw phase desynchrony of core body temperature, peak cortisol, and dim light melatonin onset in individual night-shift subjects compared with day-shift subjects. This variability was evident even though day- and night-shift nurses had similar sleep timing and scheduled meal times on days off. Surprisingly, the phase and rhythmicity of the expression of the clock gene, PER1, in PBMCs were similar for day-shift and night-shift subjects. Genome-wide microarray analysis of PBMCs from a subset of nurses revealed distinct gene expression patterns between night-shift and day-shift subjects. Enrichment analysis showed that day-shift subjects expressed pathways involved in generic transcription and regulation of signal transduction, whereas night-shift subjects expressed pathways such as RNA polymerase I promoter opening, the matrisome, and endocytosis. In addition, there was large variability in the number of rhythmic transcripts among subjects, regardless of shift type. Interestingly, the amplitude of the CBT rhythm appeared to be more consistent with the number of cycling transcripts for each of the 6 subjects than was melatonin rhythm. In summary, we show that shift-work patterns affect circadian alignment and gene expression in PBMCs.

Metabolic and cardiovascular consequences of shift work: The role of circadian disruption and sleep disturbances

Shift work, defined as work occurring outside typical daytime working hours, is associated with an increased risk of various non-communicable diseases, including diabetes and cardiovascular disease. Disruption of the internal circadian timing system and concomitant sleep disturbances is thought to play a critical role in the development of these health problems. Indeed, controlled laboratory studies have shown that short-term circadian misalignment and sleep restriction independently impair physiological processes, including insulin sensitivity, energy expenditure, immune function, blood pressure and cardiac modulation by the autonomous nervous system. If allowed to persist, these acute effects may lead to the development of cardiometabolic diseases in the long term. Here, we discuss the evidence for the contributions of circadian disruption and associated sleep disturbances to the risk of metabolic and cardiovascular health problems in shift workers. Improving the understanding of the physiological mechanisms affected by circadian misalignment and sleep disturbance will contribute to the development and implementation of strategies that prevent or mitigate the cardiometabolic impact of shift work.

Response to therapeutic sleep deprivation: a naturalistic study of clinical and genetic factors and post-treatment depressive symptom trajectory

Research has shown that therapeutic sleep deprivation (SD) has rapid antidepressant effects in the majority of depressed patients. Investigation of factors preceding and accompanying these effects may facilitate the identification of the underlying biological mechanisms. This exploratory study aimed to examine clinical and genetic factors predicting response to SD and determine the impact of SD on illness course. Mood during SD was also assessed via visual analogue scale. Depressed inpatients (n = 78) and healthy controls (n = 15) underwent ~36 h of SD. Response to SD was defined as a score of ≤ 2 on the Clinical Global Impression Scale for Global Improvement. Depressive symptom trajectories were evaluated for up to a month using self/expert ratings. Impact of genetic burden was calculated using polygenic risk scores for major depressive disorder. In total, 72% of patients responded to SD. Responders and non-responders did not differ in baseline self/expert depression symptom ratings, but mood differed. Response was associated with lower age (p = 0.007) and later age at life-time disease onset (p = 0.003). Higher genetic burden of depression was observed in non-responders than healthy controls. Up to a month post SD, depressive symptoms decreased in both patients groups, but more in responders, in whom effects were sustained. The present findings suggest that re-examining SD with a greater focus on biological mechanisms will lead to better understanding of mechanisms of depression.

Impact of Shift Work on the Circadian Timing System and Health in Women

Women who do shift work are a sizable part of the workforce. Shift workers experience circadian misalignment due to shifted sleep periods, with potentially far-reaching health consequences, including elevated risk of sleep disturbances, metabolic disorders, and cancer. This review provides an overview of the circadian timing system and presents the sex differences that can be observed in the functioning of this system, which may account for the lower tolerance to shift work for women compared with men. Recent epidemiologic findings on female-specific health consequences of shift work are discussed.

Population-level rhythms in human skin with implications for circadian medicine

Skin is the largest organ in the body and serves important barrier, regulatory, and sensory functions. The epidermal layer shows rhythmic physiological responses to daily environmental variation (e.g., DNA repair). We investigated the role of the circadian clock in the transcriptional regulation of epidermis using a hybrid experimental design, in which a limited set of human subjects (n = 20) were sampled throughout the 24-h cycle and a larger population (n = 219) were sampled once. We found a robust circadian oscillator in human epidermis at the population level using pairwise correlations of clock and clock-associated genes in 298 epidermis samples. We then used CYCLOPS to reconstruct the temporal order of all samples, and identified hundreds of rhythmically expressed genes at the population level in human epidermis. We compared these results with published time-series skin data from mice and found a strong concordance in circadian phase across species for both transcripts and pathways. Furthermore, like blood, epidermis is readily accessible and a potential source of biomarkers. Using ZeitZeiger, we identified a biomarker set for human epidermis that is capable of reporting circadian phase to within 3 hours from a single sample. In summary, we show rhythms in human epidermis that persist at the population scale and describe a path to develop robust single-sample circadian biomarkers.

Universal method for robust detection of circadian state from gene expression

Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly improve diagnosis of circadian disorders and optimize the delivery time of therapeutic treatments. To be useful, such a test must be accurate, minimally burdensome to the patient, and readily generalizable to new data. A major obstacle in development of gene expression biomarker tests is the diversity of measurement platforms and the inherent variability of the data, often resulting in predictors that perform well in the original datasets but cannot be universally applied to new samples collected in other settings. Here, we introduce TimeSignature, an algorithm that robustly infers circadian time from gene expression. We demonstrate its application in data from three independent studies using distinct microarrays and further validate it against a new set of samples profiled by RNA-sequencing. Our results show that TimeSignature is more accurate and efficient than competing methods, estimating circadian time to within 2 h for the majority of samples. Importantly, we demonstrate that once trained on data from a single study, the resulting predictor can be universally applied to yield highly accurate results in new data from other studies independent of differences in study population, patient protocol, or assay platform without renormalizing the data or retraining. This feature is unique among expression-based predictors and addresses a major challenge in the development of generalizable, clinically useful tests.

The effect of sleep deprivation and disruption on DNA damage and health of doctors

Observational studies have highlighted the detrimental health effects of shift work. The mechanisms through which acute sleep deprivation may lead to chronic disease have not been elucidated, but it is thought that increased DNA damage or decreased repair can lead to disease. The objective of this study was to examine the effects of acute sleep deprivation on DNA damage. This was a cross-sectional observational study on 49 healthy, full-time doctors. Baseline blood was sampled from each participant after three consecutive days of adequate sleep. Participants (n = 24) who were required to work overnight on-site had additional blood sampled on a morning after acute sleep deprivation. DNA damage and expression of DNA repair genes were quantified. Information on health, working patterns and sleep diaries were collected. Independent t-tests were used to compare differences between groups and standardised mean differences expressed as Cohen's d. Overnight on-site call participants had lower baseline DNA repair gene expression and more DNA breaks than participants who did not work overnight (d = 1.47, p = 0.0001; and 1.48, p = 0.0001, respectively). In overnight on-site call participants, after acute sleep deprivation, DNA repair gene expression was decreased (d = 0.90, p = 0.0001) and DNA breaks were increased (d = 0.87, p = 0.0018). Sleep deprivation in shift workers is associated with adverse health consequences. Increased DNA damage has been linked to the development of chronic disease. This study demonstrates that disrupted sleep is associated with DNA damage. Furthermore, larger prospective studies looking at relationships between DNA damage and chronic disease development are warranted, and methods to relieve, or repair, DNA damage linked to sleep deprivation should be investigated.

Timing of eating in adults across the weight spectrum: Metabolic factors and potential circadian mechanisms

Timing of eating is recognized as a significant contributor to body weight regulation. Disruption of sleep-wake cycles from a predominantly diurnal (daytime) to a delayed (evening) lifestyle leads to altered circadian rhythms and metabolic dysfunction. This article reviews current evidence for timed and delayed eating in individuals of normal weight and those with overweight or obesity: although some findings indicate a benefit of eating earlier in the daytime on weight and/or metabolic outcomes, results have not been uniformly consistent, and more rigorous and longer-duration studies are needed. We also review potential circadian mechanisms underlying the metabolic- and weight-related changes resulting from timed and delayed eating. Further identification of such mechanisms using deep phenotyping is required to determine targets for medical interventions for obesity and for prevention of metabolic syndrome and diabetes, and to inform clinical guidelines regarding eating schedules for management of weight and metabolic disease.

Phenotyping of PER3 variants reveals widespread effects on circadian preference, sleep regulation, and health

Period3 (Per3) is one of the most robustly rhythmic genes in humans and animals. It plays a significant role in temporal organisation in peripheral tissues. The effects of PER3 variants on many phenotypes have been investigated in targeted and genome-wide studies. PER3 variants, especially the human variable number tandem repeat (VNTR), associate with diurnal preference, mental disorders, non-visual responses to light, brain and cognitive responses to sleep loss/circadian misalignment. Introducing the VNTR into mice alters responses to sleep loss and expression of sleep homeostasis-related genes. Several studies were limited in size and some findings were not replicated. Nevertheless, the data indicate a significant contribution of PER3 to sleep and circadian phenotypes and diseases, which may be connected by common pathways. Thus, PER3-dependent altered light sensitivity could relate to high retinal PER3 expression and may contribute to altered brain response to light, diurnal preference and seasonal mood. Altered cognitive responses during sleep loss/circadian misalignment and changes to slow wave sleep may relate to changes in wake/activity-dependent patterns of hypothalamic gene expression involved in sleep homeostasis and neural network plasticity. Comprehensive characterisation of effects of clock gene variants may provide new insights into the role of circadian processes in health and disease.

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation

Background

Although sleep deprivation is associated with neurobehavioral impairment that may underlie significant risks to performance and safety, there is no reliable biomarker test to detect dangerous levels of impairment from sleep loss in humans. This study employs microarrays and bioinformatics analyses to explore candidate gene expression biomarkers associated with total sleep deprivation (TSD), and more specifically, the phenotype of neurobehavioral impairment from TSD. Healthy adult volunteers were recruited to a sleep laboratory for seven consecutive days (six nights). After two Baseline nights of 10 h time in bed, 11 subjects underwent an Experimental phase of 62 h of continuous wakefulness, followed by two Recovery nights of 10 h time in bed. Another six subjects underwent a well-rested Control condition of 10 h time in bed for all six nights. Blood was drawn for measuring gene expression on days two, four, and six at 4 h intervals from 08:00 to 20:00 h, corresponding to 12 timepoints across one Baseline, one Experimental, and one Recovery day.

Results

Altogether 212 genes changed expression in response to the TSD Treatment, with most genes exhibiting down-regulation during TSD. Also, 28 genes were associated with neurobehavioral impairment as measured by the Psychomotor Vigilance Test. The results support previous findings associating TSD with the immune response and ion signaling, and reveal novel candidate biomarkers such as the Speedy/RINGO family of cell cycle regulators.

Conclusions

This study serves as an important step toward understanding gene expression changes during sleep deprivation. In addition to exploring potential biomarkers for TSD, this report presents novel candidate biomarkers associated with lapses of attention during TSD. Although further work is required for biomarker validation, analysis of these genes may aid fundamental understanding of the impact of TSD on neurobehavioral performance.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4664-3) contains supplementary material, which is available to authorized users.

Simulated night shift work induces circadian misalignment of the human peripheral blood mononuclear cell transcriptome

Misalignment of the endogenous circadian timing system leads to disruption of physiological rhythms and may contribute to the development of the deleterious health effects associated with night shift work. However, the molecular underpinnings remain to be elucidated. Here, we investigated the effect of a 4-day simulated night shift work protocol on the circadian regulation of the human transcriptome. Repeated blood samples were collected over two 24-hour measurement periods from eight healthy subjects under highly controlled laboratory conditions before and 4 days after a 10-hour delay of their habitual sleep period. RNA was extracted from peripheral blood mononuclear cells to obtain transcriptomic data. Cosinor analysis revealed a marked reduction of significantly rhythmic transcripts in the night shift condition compared with baseline at group and individual levels. Subsequent analysis using a mixed-effects model selection approach indicated that this decrease is mainly due to dampened rhythms rather than to a complete loss of rhythmicity: 73% of transcripts rhythmically expressed at baseline remained rhythmic during the night shift condition with a similar phase relative to habitual bedtimes, but with lower amplitudes. Functional analysis revealed that key biological processes are affected by the night shift protocol, most notably the natural killer cell-mediated immune response and Jun/AP1 and STAT pathways. These results show that 4 days of simulated night shifts leads to a loss in temporal coordination between the human circadian transcriptome and the external environment and impacts biological processes related to the adverse health effects associated to night shift work.

Sleep Deprivation and the Epigenome

Sleep deprivation disrupts the lives of millions of people every day and has a profound impact on the molecular biology of the brain. These effects begin as changes within a neuron, at the DNA and RNA level, and result in alterations in neuronal plasticity and dysregulation of many cognitive functions including learning and memory. The epigenome plays a critical role in regulating gene expression in the context of memory storage. In this review article, we begin by describing the effects of epigenetic alterations on the regulation of gene expression, focusing on the most common epigenetic mechanisms: (i) DNA methylation; (ii) histone modifications; and (iii) non-coding RNAs. We then discuss evidence suggesting that sleep loss impacts the epigenome and that these epigenetic alterations might mediate the changes in cognition seen following disruption of sleep. The link between sleep and the epigenome is only beginning to be elucidated, but clear evidence exists that epigenetic alterations occur following sleep deprivation. In the future, these changes to the epigenome could be utilized as biomarkers of sleep loss or as therapeutic targets for sleep-related disorders.

Evidence for widespread dysregulation of circadian clock progression in human cancer

The ubiquitous daily rhythms in mammalian physiology are guided by progression of the circadian clock. In mice, systemic disruption of the clock can promote tumor growth. In vitro, multiple oncogenes can disrupt the clock. However, due to the difficulties of studying circadian rhythms in solid tissues in humans, whether the clock is disrupted within human tumors has remained unknown. We sought to determine the state of the circadian clock in human cancer using publicly available transcriptome data. We developed a method, called the clock correlation distance (CCD), to infer circadian clock progression in a group of samples based on the co-expression of 12 clock genes. Our method can be applied to modestly sized datasets in which samples are not labeled with time of day and coverage of the circadian cycle is incomplete. We used the method to define a signature of clock gene co-expression in healthy mouse organs, then validated the signature in healthy human tissues. By then comparing human tumor and non-tumor samples from twenty datasets of a range of cancer types, we discovered that clock gene co-expression in tumors is consistently perturbed. Subsequent analysis of data from clock gene knockouts in mice suggested that perturbed clock gene co-expression in human cancer is not caused solely by the inactivation of clock genes. Furthermore, focusing on lung cancer, we found that human lung tumors showed systematic changes in expression in a large set of genes previously inferred to be rhythmic in healthy lung. Our findings suggest that clock progression is dysregulated in many solid human cancers and that this dysregulation could have broad effects on circadian physiology within tumors. In addition, our approach opens the door to using publicly available data to infer circadian clock progression in a multitude of human phenotypes.

Omics Approaches in Sleep-Wake Regulation

Although sleep seems an obvious and simple behaviour, it is extremely complex involving numerous interactions both at the neuronal and the molecular levels. While we have gained detailed insight into the molecules and neuronal networks responsible for the circadian organization of sleep and wakefulness, the molecular underpinnings of the homeostatic aspect of sleep regulation are still unknown and the focus of a considerable research effort. In the last 20 years, the development of techniques allowing the simultaneous measurement of hundreds to thousands of molecular targets (i.e. 'omics' approaches) has enabled the unbiased study of the molecular pathways regulated by and regulating sleep. In this chapter, we will review how the different omics approaches, including transcriptomics, epigenomics, proteomics, and metabolomics, have advanced sleep research. We present relevant data in the framework of the two-process model in which circadian and homeostatic processes interact to regulate sleep. The integration of the different omics levels, known as 'systems genetics', will eventually lead to a better understanding of how information flows from the genome, to molecules, to networks, and finally to sleep both in health and disease.

State-dependent metabolic partitioning and energy conservation: A theoretical framework for understanding the function of sleep

Metabolic rate reduction has been considered the mechanism by which sleep conserves energy, similar to torpor or hibernation. This mechanism of energy savings is in conflict with the known upregulation (compared to wake) of diverse functions during sleep and neglects a potential role in energy conservation for partitioning of biological operations by behavioral state. Indeed, energy savings as derived from state-dependent resource allocations have yet to be examined. A mathematical model is presented based on relative rates of energy deployment for biological processes upregulated during either wake or sleep. Using this model, energy savings from sleep-wake cycling over constant wakefulness is computed by comparing stable limit cycles for systems of differential equations. A primary objective is to compare potential energy savings derived from state-dependent metabolic partitioning versus metabolic rate reduction. Additionally, energy conservation from sleep quota and the circadian system are also quantified in relation to a continuous wake condition. As a function of metabolic partitioning, our calculations show that coupling of metabolic operations with behavioral state may provide comparatively greater energy savings than the measured decrease in metabolic rate, suggesting that actual energy savings derived from sleep may be more than 4-fold greater than previous estimates. A combination of state-dependent metabolic partitioning and modest metabolic rate reduction during sleep may enhance energy savings beyond what is achievable through metabolic partitioning alone; however, the relative contribution from metabolic partitioning diminishes as metabolic rate is decreased during the rest phase. Sleep quota and the circadian system further augment energy savings in the model. Finally, we propose that state-dependent resource allocation underpins both sleep homeostasis and the optimization of daily energy conservation across species. This new paradigm identifies an evolutionary selective advantage for the upregulation of central and peripheral biological processes during sleep, presenting a unifying construct to understand sleep function.