Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery

Extensive dynamic changes in the human transcriptome and its circadian organization during prolonged bed rest

Physiological and molecular processes including the transcriptome change across the 24-h day, driven by molecular circadian clocks and behavioral and systemic factors. It is not known how the temporal organization of the human transcriptome responds to a long-lasting challenge. This may, however, provide insights into adaptation, disease, and recovery. We investigated the human 24-h time series transcriptome in 20 individuals during a 90-day constant bed rest protocol. We show that the protocol affected 91% of the transcriptome with 76% of the transcriptome still affected after 10 days of recovery. Dimensionality-reduction approaches revealed that many affected transcripts were associated with mRNA translation and immune function. The number, amplitude, and phase of rhythmic transcripts, including clock genes, varied significantly across the challenge. These findings of long-lasting changes in the temporal organization of the transcriptome have implications for understanding the mechanisms underlying health consequences of conditions such as microgravity and bed rest.

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.

Sleep deprivation and aging are metabolically linked across tissues

STUDY OBJECTIVES

Insufficient sleep is a concerning hallmark of modern society because sleep deprivation (SD) is a risk factor for neurodegenerative and cardiometabolic disorders. SD imparts an aging-like effect on learning and memory, although little is known about possible common molecular underpinnings of SD and aging. Here, we examine this question by profiling metabolic features across different tissues after acute SD in young adult and aged mice.

METHODS

Young adult and aged mice were subjected to acute SD for 5 hours. Blood plasma, hippocampus, and liver samples were subjected to UPLC-MS/MS-based metabolic profiling.

RESULTS

SD preferentially impacts peripheral plasma and liver profiles (e.g. ketone body metabolism) whereas the hippocampus is more impacted by aging. We further demonstrate that aged animals exhibit SD-like metabolic features at baseline. Hepatic alterations include parallel changes in nicotinamide metabolism between aging and SD in young animals. Overall, metabolism in young adult animals is more impacted by SD, which in turn induces aging-like features. A set of nine metabolites was classified (79% correct) based on age and sleep status across all four groups.

CONCLUSIONS

Our metabolic observations demonstrate striking parallels to previous observations in studies of learning and memory and define a molecular metabolic signature of sleep loss and aging.

Study on the active ingredients and mechanism of Jiaotai Pill in the treatment of primary insomnia based on network pharmacology and GEO statistics: A review

OBJECTIVE

To explore the active components and mechanism of Jiaotai Pill (JTP) in the treatment of primary insomnia (PI) based on gene expression omnibus.

METHODS

The main active components of Jiaotai Pills were obtained by TCMSP and literature mining, and the targets of the active components of Jiaotai Pills were predicted. The targets were verified and standardized by Uniprot database. PI-related targets were obtained from GeneCards, OMIM, DrugBank, PharmGKB, and TTD databases. Obtaining an intersection action target point of the Jiaotai pill and the PI by using a Venny diagram; Gene chip data (GSE208668) was downloaded from gene expression omnibus database, and then gene probe enrichment analysis (GSEA) was used to screen the differentially expressed genes between PI patients and normal controls, and molecular docking was used to virtually verify the screened differentially expressed genes with potential active compounds.

RESULTS

21 active components and 263 potential targets of Jiaotai Pill were screened by database analysis and literature mining, 112 of which were intersected with PI. Molecular docking results showed that quercetin, EGCG, kaempferol, R-kanatin, stigmasterol, berberine and other core active components had good docking activity with related differential genes.

CONCLUSION

Jiaotai Pill can regulate the release of inflammatory factors through multiple active ingredients, multiple disease targets, multiple biological pathways and multiple pathways to achieve the purpose of treating PI, which provides a theoretical basis for the clinical treatment of PI and broadens the clinical use of Jiaotai Pill.

Identification of Potential Diagnostic Biomarkers From Circulating Cells During the Course of Sleep Deprivation-Related Myocardial Infarction Based on Bioinformatics Analyses

Background

Myocardial infarction (MI) is the leading cause of death from non-infectious diseases worldwide and results in rapid deterioration due to the sudden rupture of plaques associated with atherosclerosis, a chronic inflammatory disease. Sleep is a key factor that regulates immune homeostasis of the body. The imbalance in circulating immune cells caused by sleep deprivation (SD) may represent a risk factor leading to the rapid deterioration of plaques and MI. Therefore, it is of profound significance to identify diagnostic biomarkers for preventing SD-related MI.

Methods

In the present study, we identified coexpressed differentially expressed genes (co-DEGs) between peripheral blood mononuclear cells from MI and SD samples (compared to controls) from a public database. LASSO regression analysis was applied to identify significant diagnostic biomarkers from co-DEGs. Moreover, receiver operating characteristic (ROC) curve analysis was performed to test biomarker accuracy and diagnostic ability. We further analyzed immune cell enrichment in MI and SD samples using the CIBERSORT algorithm, and the correlation between biomarkers and immune cell composition was assessed. We also investigated whether diagnostic biomarkers are involved in immune cell signaling pathways in SD-related MI processes.

Results

A total of 10 downregulated co-DEGs from the sets of MI-DEGs and SD-DEGs were overlapped. After applying LASSO regression analysis, SYTL2, KLRD1, and C12orf75 were selected and validated as diagnostic biomarkers using ROC analysis. Next, we found that resting NK cells were downregulated in both the MI samples and SD samples, which is similar to the changes noted for SYTL2. Importantly, SYTL2 was strongly positively correlated not only with resting NK cells but also with most genes related to NK cell markers in the MI and SD datasets. Moreover, SYTL2 was highly associated with genes in NK cell signaling pathways, including the MAPK signaling pathway, cytotoxic granule movement and exocytosis, and NK cell activation. Furthermore, GSEA and KEGG analyses provided evidence that the DEGs identified from MI samples with low vs. high SYTL2 expression exhibited a strong association with the regulation of the immune response and NK cell-mediated cytotoxicity.

Conclusion

In conclusion, SYTL2, KLRD1, and C12orf75 represent potential diagnostic biomarkers of MI. The association between SYTL2 and resting NK cells may be critically involved in SD-related MI development and occurrence.

Human blood serum proteome changes after 6 hours of sleep deprivation at night

Background

The aim of this study was to discover significantly changed proteins in human blood serum after loss of 6 h sleep at night. Furthermore, to reveal affected biological process- and molecular function categories that might be clinically relevant, by exploring systems biological databases.

Methods

Eight females were recruited by volunteer request. Peripheral venous whole blood was sampled at 04:00 am, after 6 h of sleep and after 6 h of sleep deprivation. We used within-subjects design (all subjects were their own control). Blood serum from each subject was depleted before protein digestion by trypsin and iTRAQ labeling. Labled peptides were analyzed by mass spectrometry (LTQ OritrapVelos Elite) connected to a LC system (Dionex Ultimate NCR-3000RS).

Results

We identified 725 proteins in human blood serum. 34 proteins were significantly differentially expressed after 6 h of sleep deprivation at night. Out of 34 proteins, 14 proteins were up-regulated, and 20 proteins were down-regulated. We emphasized the functionality of the 16 proteins commonly differentiated in all 8 subjects and the relation to pathological conditions. In addition, we discussed Histone H4 (H4) and protein S100-A6/Calcyclin (S10A6) that were upregulated more than 1.5-fold. Finally, we discussed affected biological process- and molecular function categories.

Conclusions

Overall, our study suggest that acute sleep deprivation, at least in females, affects several known biological processes- and molecular function categories and associates to proteins that also are changed under pathological conditions like impaired coagulation, oxidative stress, immune suppression, neurodegenerative related disorder, and cancer. Data are available via ProteomeXchange with identifier PXD021004.

Nature Versus Nurture: What Can be Learned from the Oldest-Old's Claims About Longevity?

Beneficial genetic or environmental factors that influence the length and quality of life can be evaluated while studying supercentenarians. The oldest-old can withstand serious/fatal illnesses more than their peers and/or their aging rate is decreased. Supercentenarians are an interesting group of individuals whose lifestyle is not particularly healthy according to the common guidelines, namely some of them seem to have similar harmful behaviors, but still manage to stay healthier for longer, and while eventually dying from the same degenerative diseases as the general population, they develop symptoms 20-30 years later. As there are not many supercentenarians by definition, it is worthwhile to diligently collect their data to enable future meta-analyses on larger samples; much can be learned from supercentenarians' habits and lifestyle choices about the aging process. Contributions of genetics, lifestyle choices, and epigenetics to their extended life span are discussed here.

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.

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.

Unique transcriptional signatures of sleep loss across independently evolved cavefish populations

Animals respond to sleep loss with compensatory rebound sleep, and this is thought to be critical for the maintenance of physiological homeostasis. Sleep duration varies dramatically across animal species, but it is not known whether evolutionary differences in sleep duration are associated with differences in sleep homeostasis. The Mexican cavefish, Astyanax mexicanus, has emerged as a powerful model for studying the evolution of sleep. While eyed surface populations of A. mexicanus sleep approximately 8 hr each day, multiple blind cavefish populations have converged on sleep patterns that total as little as 2 hr each day, providing the opportunity to examine whether the evolution of sleep loss is accompanied by changes in sleep homeostasis. Here, we examine the behavioral and molecular response to sleep deprivation across four independent populations of A. mexicanus. Our behavioral analysis indicates that surface fish and all three cavefish populations display robust recovery sleep during the day following nighttime sleep deprivation, suggesting sleep homeostasis remains intact in cavefish. We profiled transcriptome-wide changes associated with sleep deprivation in surface fish and cavefish. While the total number of differentially expressed genes was not greater for the surface population, the surface population exhibited the highest number of uniquely differentially expressed genes than any other population. Strikingly, a majority of the differentially expressed genes are unique to individual cave populations, suggesting unique expression responses are exhibited across independently evolved cavefish populations. Together, these findings suggest sleep homeostasis is intact in cavefish despite a dramatic reduction in overall sleep duration.

Longitudinal transcriptome-wide gene expression analysis of sleep deprivation treatment shows involvement of circadian genes and immune pathways

Therapeutic sleep deprivation (SD) rapidly induces robust, transient antidepressant effects in a large proportion of major mood disorder patients suffering from a depressive episode, but underlying biological factors remain poorly understood. Research suggests that these patients may have altered circadian molecular genetic 'clocks' and that SD functions through 'resetting' dysregulated genes; additional factors may be involved, warranting further investigation. Leveraging advances in microarray technology enabling the transcriptome-wide assessment of gene expression, this study aimed to examine gene expression changes accompanying SD and recovery sleep in patients suffering from an episode of depression. Patients (N = 78) and controls (N = 15) underwent SD, with blood taken at the same time of day before SD, after one night of SD and after recovery sleep. A transcriptome-wide gene-by-gene approach was used, with a targeted look also taken at circadian genes. Furthermore, gene set enrichment, and longitudinal gene set analyses including the time point after recovery sleep, were conducted. Circadian genes were significantly affected by SD, with patterns suggesting that molecular clocks of responders and non-responders, as well as patients and controls respond differently to chronobiologic stimuli. Notably, gene set analyses revealed a strong widespread effect of SD on pathways involved in immune function and inflammatory response, such as those involved in cytokine and especially in interleukin signalling. Longitudinal gene set analyses showed that in responders these pathways were upregulated after SD; in non-responders, little response was observed. Our findings emphasize the close relationship between circadian, immune and sleep systems and their link to etiology of depression at the transcriptomic level.

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.

The Sleep-Immune Crosstalk in Health and Disease

Sleep and immunity are bidirectionally linked. Immune system activation alters sleep, and sleep in turn affects the innate and adaptive arm of our body's defense system. Stimulation of the immune system by microbial challenges triggers an inflammatory response, which, depending on its magnitude and time course, can induce an increase in sleep duration and intensity, but also a disruption of sleep. Enhancement of sleep during an infection is assumed to feedback to the immune system to promote host defense. Indeed, sleep affects various immune parameters, is associated with a reduced infection risk, and can improve infection outcome and vaccination responses. The induction of a hormonal constellation that supports immune functions is one likely mechanism underlying the immune-supporting effects of sleep. In the absence of an infectious challenge, sleep appears to promote inflammatory homeostasis through effects on several inflammatory mediators, such as cytokines. This notion is supported by findings that prolonged sleep deficiency (e.g., short sleep duration, sleep disturbance) can lead to chronic, systemic low-grade inflammation and is associated with various diseases that have an inflammatory component, like diabetes, atherosclerosis, and neurodegeneration. Here, we review available data on this regulatory sleep-immune crosstalk, point out methodological challenges, and suggest questions open for future research.

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.

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.

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.

Transcriptional Signatures of Sleep Duration Discordance in Monozygotic Twins

Introduction

Habitual short sleep duration is associated with adverse metabolic, cardiovascular, and inflammatory effects. Co-twin study methodologies account for familial (eg, genetics and shared environmental) confounding, allowing assessment of subtle environmental effects, such as the effect of habitual short sleep duration on gene expression. Therefore, we investigated gene expression in monozygotic twins discordant for actigraphically phenotyped habitual sleep duration.

Methods

Eleven healthy monozygotic twin pairs (82% female; mean age 42.7 years; SD = 18.1), selected based on subjective sleep duration discordance, were objectively phenotyped for habitual sleep duration with 2 weeks of wrist actigraphy. Peripheral blood leukocyte (PBL) RNA from fasting blood samples was obtained on the final day of actigraphic measurement and hybridized to Illumina humanHT-12 microarrays. Differential gene expression was determined between paired samples and mapped to functional categories using Gene Ontology. Finally, a more comprehensive gene set enrichment analysis was performed based on the entire PBL transcriptome.

Results

The mean 24-hour sleep duration of the total sample was 439.2 minutes (SD = 46.8 minutes; range 325.4-521.6 minutes). Mean within-pair sleep duration difference per 24 hours was 64.4 minutes (SD = 21.2; range 45.9-114.6 minutes). The twin cohort displayed distinctive pathway enrichment based on sleep duration differences. Habitual short sleep was associated with up-regulation of genes involved in transcription, ribosome, translation, and oxidative phosphorylation. Unexpectedly, genes down-regulated in short sleep twins were highly enriched in immuno-inflammatory pathways such as interleukin signaling and leukocyte activation, as well as developmental programs, coagulation cascade, and cell adhesion.

Conclusions

Objectively assessed habitual sleep duration in monozygotic twin pairs appears to be associated with distinct patterns of differential gene expression and pathway enrichment. By accounting for familial confounding and measuring real life sleep duration, our study shows the transcriptomic effects of habitual short sleep on dysregulated immune response and provides a potential link between sleep deprivation and adverse metabolic, cardiovascular, and inflammatory outcomes.

Gastrointestinal Transcriptomic Response of Metabolic Vitamin B12 Pathways in Roux-en-Y Gastric Bypass

OBJECTIVES

Vitamin B12 (B12) deficiency after Roux-en-Y gastric bypass (RYGB) is highly prevalent and may contribute to postoperative complications. Decreased production of intrinsic factor owing to gastric fundus removal is thought to have a major role, but other components of B12 metabolism may also be affected. We evaluated changes in the expression levels of multiple B12 pathway-encoding genes in gastrointestinal (GI) tissues to evaluate the potential roles in contributing to post-RYGB B12 deficiency.

METHODS

During double-balloon enteroscopy, serial GI biopsies were collected from 20 obese women (age, 46.9±6.2 years; body mass index, 46.5±5.3 kg/m2) with adult-onset type 2 diabetes (fasting plasma glucose ≥126 mg/dl; hemoglobin A1c≥6.5%) before and, at the same site, 3 months after RYGB. Gene expression levels were assessed by the Affymetrix Human GeneChip 1.0 ST microarray. Findings were validated by real-time quantitative PCR (RT-qPCR).

RESULTS

Gene expression levels with significant changes (P≤0.05) included: transcobalamin I (TCN1) in remnant (-1.914-fold) and excluded (-1.985-fold) gastric regions; gastric intrinsic factor (GIF) in duodenum (-0.725-fold); and cubilin (CUBN) in duodenum (+0.982-fold), jejunum (+1.311-fold), and ileum (+0.685-fold). Validation by RT-qPCR confirmed (P≤0.05) observed changes for TCN1 in the remnant gastric region (-0.132-fold) and CUBN in jejunum (+2.833-fold).

CONCLUSIONS

RYGB affects multiple pathway-encoding genes that may be associated with postoperative B12 deficiency. Decreased TCN1 levels seem to be the main contributing factor. Increased CUBN levels suggest an adaptive genetic reprogramming of intestinal tissue aiming to compensate for impaired intestinal B12 delivery.

Association between sleep deficiency and cardiometabolic disease: implications for health disparities

BACKGROUND

Cardiometabolic diseases, which include obesity, diabetes, hypertension, and cardiovascular disease, are associated with reduced quality of life and reduced life expectancy. Unfortunately, there are racial/ethnic and socioeconomic disparities associated with these diseases such that minority populations, such as African Americans and Hispanics, and those of lower socioeconomic status, experience a greater burden. Several reports have indicated that there are differences in sleep duration and quality that mirror the disparities in cardiometabolic disease. The goal of this paper is to review the association between sleep and cardiometabolic disease risk because of the possibility that suboptimal sleep may partially mediate the cardiometabolic disease disparities.

METHODS

We review both experimental studies that have restricted sleep duration or impaired sleep quality and examined biomarkers of cardiometabolic disease risk, including glucose metabolism and insulin sensitivity, appetite regulation and food intake, and immune function. We also review observational studies that have examined the association between habitual sleep duration and quality, and the prevalence or risk of obesity, diabetes, hypertension, and cardiovascular disease.

CONCLUSION

Many experimental and observational studies do support an association between suboptimal sleep and increased cardiometabolic disease risk.

How sleep and wakefulness influence circadian rhythmicity: effects of insufficient and mistimed sleep on the animal and human transcriptome

The mammalian circadian system is a multi-oscillator, hierarchically organised system where a central pacemaker synchronises behavioural, physiological and gene expression rhythms in peripheral tissues. Epidemiological studies show that disruption of this internal synchronisation by short sleep and shift work is associated with adverse health outcomes through mechanisms that remain to be elucidated. Here, we review recent animal and human studies demonstrating the profound effects of insufficient and mistimed sleep on the rhythms of gene expression in central and peripheral tissues. In mice, sleep restriction leads to an ~80% reduction in circadian transcripts in the brain and profound disruption of the liver transcriptome. In humans, sleep restriction leads to a 1.9% reduction in circadian transcripts in whole blood, and when sleep is displaced to the daytime, 97% of rhythmic genes become arrhythmic and one-third of all genes show changes in temporal expression profiles. These changes in mice and humans include a significant reduction in the circadian regulation of transcription and translation and core clock genes in the periphery, while at the same time rhythms within the suprachiasmatic nucleus are not disrupted. Although the physiological mediators of these sleep disruption effects on the transcriptome have not been established, altered food intake, changes in hormones such as cortisol, and changes in body and brain temperature may play important roles. Processes and molecular pathways associated with these disruptions include metabolism, immune function, inflammatory and stress responses, and point to the molecular mechanisms underlying the established adverse health outcomes associated with short sleep duration and shift work, such as metabolic syndrome and cancer.

Sleep deprivation and gene expression

Sleep occurs in a wide range of animal species as a vital process for the maintenance of homeostasis, metabolic restoration, physiological regulation, and adaptive cognitive functions in the central nervous system. Long-term perturbations induced by the lack of sleep are mostly mediated by changes at the level of transcription and translation. This chapter reviews studies in humans, rodents, and flies to address the various ways by which sleep deprivation affects gene expression in the nervous system, with a focus on genes related to neuronal plasticity, brain function, and cognition. However, the effects of sleep deprivation on gene expression and the functional consequences of sleep loss are clearly not restricted to the cognitive domain but may include increased inflammation, expression of stress-related genes, general impairment of protein translation, metabolic imbalance, and thermal deregulation.

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

STUDY OBJECTIVES

To address whether changes in gene expression in blood cells with sleep loss are different in individuals resistant and sensitive to sleep deprivation.

DESIGN

Blood draws every 4 h during a 3-day study: 24-h normal baseline, 38 h of continuous wakefulness and subsequent recovery sleep, for a total of 19 time-points per subject, with every 2-h psychomotor vigilance task (PVT) assessment when awake.

SETTING

Sleep laboratory.

PARTICIPANTS

Fourteen subjects who were previously identified as behaviorally resistant (n = 7) or sensitive (n = 7) to sleep deprivation by PVT.

INTERVENTION

Thirty-eight hours of continuous wakefulness.

MEASUREMENTS AND RESULTS

We found 4,481 unique genes with a significant 24-h diurnal rhythm during a normal sleep-wake cycle in blood (false discovery rate [FDR] < 5%). Biological pathways were enriched for biosynthetic processes during sleep. After accounting for circadian effects, two genes (SREBF1 and CPT1A, both involved in lipid metabolism) exhibited small, but significant, linear changes in expression with the duration of sleep deprivation (FDR < 5%). The main change with sleep deprivation was a reduction in the amplitude of the diurnal rhythm of expression of normally cycling probe sets. This reduction was noticeably higher in behaviorally resistant subjects than sensitive subjects, at any given P value. Furthermore, blood cell type enrichment analysis showed that the expression pattern difference between sensitive and resistant subjects is mainly found in cells of myeloid origin, such as monocytes.

CONCLUSION

Individual differences in behavioral effects of sleep deprivation are associated with differences in diurnal amplitude of gene expression for genes that show circadian rhythmicity.

Human longevity is associated with regular sleep patterns, maintenance of slow wave sleep, and favorable lipid profile

Some individuals are able to successfully reach very old ages, reflecting higher adaptation against age-associated effects. Sleep is one of the processes deeply affected by aging; however few studies evaluating sleep in long-lived individuals (aged over 85) have been reported to date. The aim of this study was to characterize the sleep patterns and biochemical profile of oldest old individuals (N = 10, age 85–105 years old) and compare them to young adults (N = 15, age 20–30 years old) and older adults (N = 13, age 60–70 years old). All subjects underwent full-night polysomnography, 1-week of actigraphic recording and peripheral blood collection. Sleep electroencephalogram spectral analysis was also performed. The oldest old individuals showed lower sleep efficiency and REM sleep when compared to the older adults, while stage N3 percentage and delta power were similar across the groups. Oldest old individuals maintained strictly regular sleep-wake schedules and also presented higher HDL-cholesterol and lower triglyceride levels than older adults. The present study revealed novel data regarding specific sleep patterns and maintenance of slow wave sleep in the oldest old group. Taken together with the favorable lipid profile, these results contribute with evidence to the importance of sleep and lipid metabolism regulation in the maintenance of longevity in humans.

Mistimed sleep disrupts circadian regulation of the human transcriptome

Circadian organization of the mammalian transcriptome is achieved by rhythmic recruitment of key modifiers of chromatin structure and transcriptional and translational processes. These rhythmic processes, together with posttranslational modification, constitute circadian oscillators in the brain and peripheral tissues, which drive rhythms in physiology and behavior, including the sleep-wake cycle. In humans, sleep is normally timed to occur during the biological night, when body temperature is low and melatonin is synthesized. Desynchrony of sleep-wake timing and other circadian rhythms, such as occurs in shift work and jet lag, is associated with disruption of rhythmicity in physiology and endocrinology. However, to what extent mistimed sleep affects the molecular regulators of circadian rhythmicity remains to be established. Here, we show that mistimed sleep leads to a reduction of rhythmic transcripts in the human blood transcriptome from 6.4% at baseline to 1.0% during forced desynchrony of sleep and centrally driven circadian rhythms. Transcripts affected are key regulators of gene expression, including those associated with chromatin modification (methylases and acetylases), transcription (RNA polymerase II), translation (ribosomal proteins, initiation, and elongation factors), temperature-regulated transcription (cold inducible RNA-binding proteins), and core clock genes including CLOCK and ARNTL (BMAL1). We also estimated the separate contribution of sleep and circadian rhythmicity and found that the sleep-wake cycle coordinates the timing of transcription and translation in particular. The data show that mistimed sleep affects molecular processes at the core of circadian rhythm generation and imply that appropriate timing of sleep contributes significantly to the overall temporal organization of the human transcriptome.

Sick and tired: how molecular regulators of human sleep schedules and duration impact immune function

Why do we need to sleep? What regulates when we sleep? And what dictates the number of hours we require? These are often viewed as three separate biological questions. Here, we propose they share molecular etiologies, whereby regulators of sleep schedules and sleep duration also govern the physiological purposes of sleep. To support our hypothesis, we review Mendelian human genetic variants sufficient to advance sleep-wake onset (PER2) and shorten sleep length (DEC2), and evaluate their emerging roles in immune responses that may rely on a sound night of slumber.

More than hormones: sex differences in cardiovascular parameters after sleep loss in rats

Although the influence of sex on sleep pattern and cardiovascular parameters is well known, knowledge regarding the effects of sleep loss on heart responses in both sexes is scarce. The present study investigated the effects of paradoxical sleep deprivation (PSD) and chronic sleep restriction (SR) on cardiovascular parameters and adrenocorticotropic hormone (ACTH) levels in male and female rats. Both groups were randomly assigned to PSD for 96 h, SR for 21 days or home-cage control. Mean arterial pressure (MAP), heart rate (HR), baroreflex sensitivity (bradycardia and tachycardia responses) and ACTH levels were evaluated. The results showed that PSD induced a significant increase in HR and ACTH levels in both sexes, although male rats presented higher levels of ACTH hormone compared to females. In addition to sex-specific responses, PSD decreased the tachycardia only in male rats. SR, induced a significant increase in MAP and decrease in bradycardia in both sexes. Male rats were more affected by sleep deprivation protocols than females for MAP, bradycardia response, and ACTH levels. The results showed that the effects of sleep loss on cardiovascular parameters are associated with the protocol of sleep deprivation and that sex can modulate these effects. We suggested this experimental model as a suitable tool for further investigations of the relationship between cardiovascular parameters and sleep.