Effects of insufficient sleep on circadian rhythmicity and expression amplitude of the human blood transcriptome

Association between sleep duration and long-term changes in novel anthropometric and atherogenic indices: a cohort study

BACKGROUND

Adequate sleep is a crucial aspect of overall health. While existing research has highlighted the impact of factors like obesity and lipid profiles on sleep patterns, limited attention has been given to exploring the relationship between sleep duration with novel anthropometric and atherogenic indices.

METHODS

This study was part of the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) cohort study. 7,449 participants' sleep duration was assessed at baseline using a questionnaire, and they were followed for 10 years to calculate novel anthropometric and atherogenic indices.

RESULTS

Participants who slept over 9 h had a 41.7% higher likelihood of reduced body shape index (ABSI) (ABSI < 0.086, OR: 1.417, P = 0.021) and a 49.5% greater chance of a lower weight-adjusted-waist index (WWI) (WWI < 12, OR: 1.495, P = 0.011). In contrast, less than 6 h of sleep was associated with a 40.1% decrease in the odds of reduced ABSI (OR: 0.599, P < 0.001) and a 32.7% lower likelihood of reduced WWI (OR: 0.673, P < 0.001). Long sleepers also had a 31.3% lower chance of body adiposity index (BAI) < 37.5 (OR: 0.687, P = 0.027) and a 27% reduced chance of high-density lipoprotein (HDL) < 55 mg/dl (OR: 0.730, P = 0.037). Shortened sleep decreased the odds of a lower abdominal volume index (AVI) (AVI < 21) by 19.1% (OR: 0.809, P = 0.010).

CONCLUSION

Longer sleep durations were associated with lower ABSI and WWI, while shorter sleep durations correlated with increased ABSI, WWI, and AVI. Additionally, extended sleep was associated with elevated HDL levels, although it also contributed to increased BAI.

Dose-response relationship between nighttime sleep duration and intrinsic capacity declines among Chinese elderly: a cross-sectional study from CHARLS

BACKGROUND

Intrinsic capacity is a crucial indicator of adverse outcomes and has predictive value for diseases and mortality. The objective of this study is to assess the association between nighttime sleep duration and intrinsic capacity in older Chinese adults.

METHODS

Data were collected from the China Health and Retirement Longitudinal Study (CHARLS) spanning the years 2008-2020. Minimally sufficient adjustment was made for confounding factors identified through a Directed Acyclic Graphs (DAGs), and multivariate logistic regression analysis was conducted to determine the relationship between nighttime sleep duration and intrinsic capacity. Restricted cubic splines (RCS) were used to assess the nonlinear relationship between nighttime sleep duration and intrinsic capacity in this population. Finally, subgroup analysis and interaction effect analysis were performed.

RESULTS

Among the 4994 older adults, 3118 (62.4%) experienced a decline in intrinsic capacity. After adjusting for confounding factors, nighttime sleep duration was associated with an increased risk of intrinsic capacity decline (P < 0.001), exhibiting a nonlinear J-shaped pattern.

CONCLUSIONS

For Chinese older adults, increased nighttime sleep duration shows a nonlinear, J-shaped dose-response relationship with the risk of intrinsic capacity decline. Our study provides important insights into the intrinsic capacity and health self-management of older adults.

Changes in gene expression in healthcare workers during night shifts: implications for immune response and health risks

BACKGROUND

Shift work is common in healthcare, especially in emergency and intensive care, to maintain the quality of patient care. Night shifts are linked to health risks such as cardiovascular disease, metabolic disorders, and poor mental health. It has been suggested that inflammatory responses due to the disruption of circadian rhythm may contribute to health risks, but the detailed mechanisms remain unclear. This study aimed to analyze changes in gene expression in whole blood of healthcare workers before and after a night shift and investigate the molecular pathogenesis of these changes and their impact on health.

METHODS

This was a single-center, prospective, observational study of four medical doctors working night shifts in the emergency department. Blood samples from the subjects were collected before and after the night shift, and RNA sequencing was performed to analyze changes in gene expression in whole blood. The data obtained were analyzed via Ingenuity Pathway Analysis (IPA) core analysis that included canonical pathway analysis, upstream regulator analysis, and functional network analysis. RNA bulk deconvolution was performed to estimate the relative abundance of immune cells. The IPA analysis match feature was also used to assess similarities of gene expression patterns with other diseases.

RESULTS

We identified 302 upregulated and 78 downregulated genes (p < 0.05, |log2-fold change|> 0.5) as genes whose expression changed after the night shift. Canonical pathway analysis revealed that Toll-like receptors and other innate immune response pathways were activated. Upstream regulator analysis and functional network analysis also consistently indicated a predicted activation of innate immune and inflammatory responses. RNA bulk deconvolution showed changes in the proportions of several immune cells. IPA analysis match indicated that gene expression patterns after night shifts were highly correlated with several diseases, including major depressive disorder, in terms of immune and inflammatory responses.

CONCLUSION

The results revealed that innate immune and inflammatory responses are elicited after night shifts in healthcare workers and that gene expression patterns correlate with several diseases in terms of immune and inflammatory responses. These findings suggest that shift work may affect health risks through innate immune and inflammatory responses.

A novel Bayesian hierarchical model for detecting differential circadian pattern in transcriptomic applications

Circadian rhythm plays a critical role in regulating various physiological processes, and disruptions in these rhythms have been linked to a wide range of diseases. Identifying molecular biomarkers showing differential circadian (DC) patterns between biological conditions or disease status is important for disease prevention, diagnosis, and treatment. However, circadian pattern is characterized by three key components: amplitude, phase, and MESOR, which poses a great challenge for DC analysis. Existing statistical methods focus on detecting differential shape (amplitude and phase) but often overlook MESOR difference. Additionally, these methods lack flexibility to incorporate external knowledge such as differential circadian information from similar clinical and biological context to improve the current DC analysis. To address these limitation, we introduce a novel Bayesian hierarchical model, BayesDCirc, designed for detecting differential circadian patterns in a two-group experimental design, which offer the advantage of testing MESOR difference and incorporating external knowledge. Benefiting from explicitly testing MESOR within the Bayesian modeling framework, BayesDCirc demonstrates superior FDR control over existing methods, with further performance improvement by leveraging external knowledge of DC genes. Applied to two real datasets, BayesDCirc successfully identify key circadian genes, particularly with external knowledge incorporated. The R package "BayesDCirc" for the method is publicly available on GitHub at https://github.com/lichen-lab/BayesDCirc.

Time for bed: diet, sleep and obesity in children and adults

Sufficient sleep is necessary for optimal health, daytime performance and wellbeing and the amount required is age-dependent and decreases across the lifespan. Sleep duration is usually affected by age and several different cultural, social, psychological, behavioural, pathophysiological and environmental factors. This review considers how much sleep children and adults need, why this is important, what the consequences are of insufficient sleep and how we can improve sleep. A lack of the recommended amount of sleep for a given age group has been shown to be associated with detrimental effects on health including effects on metabolism, endocrine function, immune function and haemostatic pathways. Obesity has increased worldwide in the last few decades and the WHO has now declared it a global epidemic. A lack of sleep is associated with an increased risk of obesity in children and adults, which may lead to future poor health outcomes. Data from studies in both children and adults suggest that the relationship between sleep and obesity may be mediated by several different mechanisms including alterations in appetite and satiety, sleep timing, circadian rhythm and energy balance. Moreover, there is evidence to suggest that improvements in sleep, in both children and adults, can be beneficial for weight management and diet and certain foods might be important to promote sleep. In conclusion this review demonstrates that there is a wide body of evidence to suggest that sleep and obesity are causally related and recommends that further research is required to inform policy, and societal change.

Time-restricted feeding modulates gene expression related with rhythm and inflammation in Mongolian gerbils

Time-restricted feeding (TRF) has the potential to modulate circadian rhythm and widely studied in humans and laboratory mice. However, less is known about the physiological responses to TRF in wild mammals. Here, we used Mongolian gerbils, Meriones unguiculatus, to explore the effect of 6-week TRF on gene expression related with circadian rhythm and inflammation. The TRF gerbils had higher cumulative food intake than the ad libitum (AL) group, but body mass, feeding frequency/time and metabolic rate did not differ between groups. In the hypothalamus, downregulation of rhythm-related genes Per3, Cry1 and Dbp was detected in the daytime-restricted feeding (DRF) group and Cry1 was downregulated in the nighttime-restricted feeding (NRF) group. In the liver, the expression of Per1/3, Rev-erbα/β and Dbp was lower, and Bmal1 was higher in the DRF than in AL group, while NRF gerbils showed no changes. In the colon, the expression of Bmal1 and Cry1 was higher but Per3, Rev-erbα/β and Dbp were lower in the DRF than in AL group. Further, the expression of inflammation-related genes such as NF-κB, IL-1β, IL-18 and Nlrp3 was lower in the liver of DRF gerbils, and IL-1β was lower both in the hypothalamus and liver of NRF gerbils. Moreover, the genes related with inflammation such as NF-κB, Nlrp3, IL-10/18/1β and Tnf-α were positively or negatively correlated with multiple rhythm-related genes in the central and peripheral organs. In conclusion, TRF, particularly DRF, could modulate rhythm-related genes in the central and peripheral tissues and reduce hepatic expression of inflammation-related genes in gerbils.

Sleep Deficiency and Cardiometabolic Disease

Epidemiologic studies have demonstrated that short sleep duration is associated with an increased risk of cardio-metabolic health outcomes including cardiovascular disease mortality, coronary heart disease, type 2 diabetes mellitus, hypertension, and metabolic syndrome. Experimental sleep restriction studies have sought to explain these findings. This review describes the main evidence of these associations and possible mechanisms explaining them. Whether sleep extension reverses these now widely acknowledged adverse health effects and the feasibility of implementing such strategies on a public health level is discussed.

A Bayesian Framework for Genome-wide Circadian Rhythmicity Biomarker Detection

Circadian rhythms are endogenous ∼24-hour cycles that significantly influence physiological and behavioral processes. These rhythms are governed by a transcriptional-translational feedback loop of core circadian genes and are essential for maintaining overall health. The study of circadian rhythms has expanded into various omics datasets, necessitating accurate analytical methodology for circadian biomarker detection. Here, we introduce a novel Bayesian framework for the genome-wide detection of circadian rhythms that is capable of incorporating prior biological knowledge and adjusting for multiple testing issue via a false discovery rate approach. Our framework leverages a Bayesian hierarchical model and employs a reverse jump Markov chain Monte Carlo (rjMCMC) technique for model selection. Through extensive simulations, our method, BayesCircRhy, demonstrated superior false discovery rate control over competing methods, robustness against heavier-tailed error distributions, and better performance compared to existing approaches. The method's efficacy was further validated in two RNA-Sequencing data, including a human resitrcted feeding data and a mouse aging data, where it successfully identified known and novel circadian genes. R package "BayesianCircadian" for the method is publicly available on GitHub https://github.com/jxncdhc/BayesianCircadian .

Identification of key genes and diagnostic model associated with circadian rhythms and Parkinson's disease by bioinformatics analysis

Background

Circadian rhythm disruption is typical in Parkinson's disease (PD) early stage, and it plays an important role in the prognosis of the treatment effect in the advanced stage of PD. There is growing evidence that circadian rhythm genes can influence development of PD. Therefore, this study explored specific regulatory mechanism of circadian genes (C-genes) in PD through bioinformatic approaches.

Methods

Differentially expressed genes (DEGs) between PD and control samples were identified from GSE22491 using differential expression analysis. The key model showing the highest correlation with PD was derived through WGCNA analysis. Then, DEGs, 1,288 C-genes and genes in key module were overlapped for yielding differentially expressed C-genes (DECGs), and they were analyzed for LASSO and SVM-RFE for yielding critical genes. Meanwhile, from GSE22491 and GSE100054, receiver operating characteristic (ROC) was implemented on critical genes to identify biomarkers, and Gene Set Enrichment Analysis (GSEA) was applied for the purpose of exploring pathways involved in biomarkers. Eventually, immune infiltrative analysis was applied for understanding effect of biomarkers on immune microenvironment, and therapeutic drugs which could affect biomarkers expressions were also predicted. Finally, we verified the expression of the genes by q-PCR.

Results

Totally 634 DEGs were yielded between PD and control samples, and MEgreen module had the highest correlation with PD, thus it was defined as key model. Four critical genes (AK3, RTN3, CYP4F2, and LEPR) were identified after performing LASSO and SVM-RFE on 18 DECGs. Through ROC analysis, AK3, RTN3, and LEPR were identified as biomarkers due to their excellent ability to distinguish PD from control samples. Besides, biomarkers were associated with Parkinson's disease and other functional pathways.

Conclusion

Through bioinformatic analysis, the circadian rhythm related biomarkers were identified (AK3, RTN3 and LEPR) in PD, contributing to studies related to PD treatment.

Associations between habitual sleep characteristics and cardiometabolic disease risk in corporate executives

OBJECTIVES

Corporate executive job demands may lead to poor sleep habits, increasing their risk for cardiometabolic disease. This study aimed to describe and explore associations between objectively measured habitual sleep characteristics and cardiometabolic disease risk of corporate executives, while accounting for occupational, psychological, and lifestyle factors.

METHODS

Habitual sleep was measured using wrist-worn actigraphy and a sleep diary over seven consecutive days in 61 (68.3% men) corporate executives aged 46.4 ± 8.7years. A composite cardiometabolic disease risk score was determined using body mass index, waist circumference, blood pressure and fasting glucose and lipid concentrations. Prediction models were built using a backward stepwise selection approach to explore associations between sleep characteristics and cardiometabolic disease risk factors adjusting for occupational, psychological, and lifestyle covariates.

RESULTS

Average total sleep time was 6.60 ± 0.75 hours, with 51.7% of participants reporting poor sleep quality and 26.2% extending their weekend sleep. Adjusted models showed that lower sleep efficiency (β = -0.25, 95%CI: -0.43; -0.08, P = .006), shorter weekday total sleep time (β = -1.37, 95% CI: -2.41, -0.32; P = .011) and catch-up sleep (β = 0.84, 95%CI: 0.08, 1.60, P = .002) were associated with higher cardiometabolic disease risk scores. Adjusted models also found that shorter average time-in-bed (ß=-2.00, 95%CI: -3.76; -0.18, P = .031), average total sleep time (ß=1.98, 95%CI: -3.70; -0.25, P = .025) and weekday total sleep time (β = -2.13, 95%CI: -3.56; -0.69, P = .025) as well as catch-up sleep (β = 1.67, 95% CI: 0.52; 2.83; P = .012) were all associated with a higher body mass index.

CONCLUSION

Corporate executives who compromise sleep duration during the working week may increase their risk for obesity and future cardiometabolic disease.

Circadian gene signatures in the progression of obesity based on machine learning and Mendelian randomization analysis

Objective

Obesity, a global health concern, is associated with a spectrum of chronic diseases and cancers. Our research sheds light on the regulatory role of circadian genes in obesity progression, providing insight into the immune landscape of obese patients, and introducing new avenues for therapeutic interventions.

Methods

Expression files of multiple datasets were retrieved from the GEO database. By 80 machine-learning algorithm combinations and Mendelian randomization analysis, we discovered the key circadian genes contributing to and protecting against obesity. Subsequently, an immune infiltration analysis was conducted to examine the alterations in immune cell types and their abundance in the body and to investigate the relationships between circadian genes and immune cells. Furthermore, we delved into the molecular mechanisms of key genes implicated in obesity.

Results

Our study identified three key circadian genes (BHLHE40, PPP1CB, and CSNK1E) associated with obesity. BHLHE40 was found to promote obesity through various pathways, while PPP1CB and CSNK1E counteracted lipid metabolism disorders, and modulated cytokines, immune receptors, T cells, and monocytes.

Conclusion

In conclusion, the key circadian genes (BHLHE40, CSNK1E, and PPP1CB) may serve as novel biomarkers for understanding obesity pathogenesis and have significant correlations with infiltrating immune cells, thus providing potential new targets for obese prevention and treatment.

Prenatal opioid exposure significantly impacts placental protein kinase C (PKC) and drug transporters, leading to drug resistance and neonatal opioid withdrawal syndrome

Background

Neonatal Opioid Withdrawal Syndrome (NOWS) is a consequence of in-utero exposure to prenatal maternal opioids, resulting in the manifestation of symptoms like irritability, feeding problems, tremors, and withdrawal signs. Opioid use disorder (OUD) during pregnancy can profoundly impact both mother and fetus, disrupting fetal brain neurotransmission and potentially leading to long-term neurological, behavioral, and vision issues, and increased infant mortality. Drug resistance complicates OUD and NOWS treatment, with protein kinase regulation of drug transporters not fully understood.

Methods

DNA methylation levels of ATP-binding cassette (ABC) and solute carrier (SLC) drug transporters, along with protein kinase C (PKC) genes, were assessed in 96 placental samples using the Illumina Infinium MethylationEPIC array (850K). Samples were collected from three distinct groups: 32 mothers with infants prenatally exposed to opioids who needed pharmacological intervention for NOWS, 32 mothers with prenatally opioid-exposed infants who did not necessitate NOWS treatment, and 32 mothers who were not exposed to opioids during pregnancy.

Results

We identified 69 significantly differentially methylated SLCs, with 24 hypermethylated and 34 hypomethylated, and 11 exhibiting both types of methylation changes including SLC13A3, SLC15A2, SLC16A11, SLC16A3, SLC19A2, and SLC26A1. We identified methylation changes in 11 ABC drug transporters (ABCA1, ABCA12, ABCA2, ABCB10, ABCB5, ABCC12, ABCC2, ABCC9, ABCE1, ABCC7, ABCB3): 3 showed hypermethylation, 3 hypomethylation, and 5 exhibited both. Additionally, 7 PKC family genes (PRKCQ, PRKAA1, PRKCA, PRKCB, PRKCH, PRKCI, and PRKCZ) showed methylation changes. These genes are associated with 13 pathways involved in NOWS, including ABC transporters, bile secretion, pancreatic secretion, insulin resistance, glutamatergic synapse, and gastric acid secretion.

Conclusion

We report epigenetic changes in PKC-related regulation of drug transporters, which could improve our understanding of clinical outcomes like drug resistance, pharmacokinetics, drug-drug interactions, and drug toxicity, leading to maternal relapse and severe NOWS. Novel drugs targeting PKC pathways and transporters may improve treatment outcomes for OUD in pregnancy and NOWS.

Model integration of circadian- and sleep-wake-driven contributions to rhythmic gene expression reveals distinct regulatory principles

Analyses of gene-expression dynamics in research on circadian rhythms and sleep homeostasis often describe these two processes using separate models. Rhythmically expressed genes are, however, likely to be influenced by both processes. We implemented a driven, damped harmonic oscillator model to estimate the contribution of circadian- and sleep-wake-driven influences on gene expression. The model reliably captured a wide range of dynamics in cortex, liver, and blood transcriptomes taken from mice and humans under various experimental conditions. Sleep-wake-driven factors outweighed circadian factors in driving gene expression in the cortex, whereas the opposite was observed in the liver and blood. Because of tissue- and gene-specific responses, sleep deprivation led to a long-lasting intra- and inter-tissue desynchronization. The model showed that recovery sleep contributed to these long-lasting changes. The results demonstrate that the analyses of the daily rhythms in gene expression must take the complex interactions between circadian and sleep-wake influences into account. A record of this paper's transparent peer review process is included in the supplemental information.

Circadian disruption, clock genes, and metabolic health

A growing body of research has identified circadian-rhythm disruption as a risk factor for metabolic health. However, the underlying biological basis remains complex, and complete molecular mechanisms are unknown. There is emerging evidence from animal and human research to suggest that the expression of core circadian genes, such as circadian locomotor output cycles kaput gene (CLOCK), brain and muscle ARNT-Like 1 gene (BMAL1), period (PER), and cyptochrome (CRY), and the consequent expression of hundreds of circadian output genes are integral to the regulation of cellular metabolism. These circadian mechanisms represent potential pathophysiological pathways linking circadian disruption to adverse metabolic health outcomes, including obesity, metabolic syndrome, and type 2 diabetes. Here, we aim to summarize select evidence from in vivo animal models and compare these results with epidemiologic research findings to advance understanding of existing foundational evidence and potential mechanistic links between circadian disruption and altered clock gene expression contributions to metabolic health-related pathologies. Findings have important implications for the treatment, prevention, and control of metabolic pathologies underlying leading causes of death and disability, including diabetes, cardiovascular disease, and cancer.

Changes in sleep score and leisure-time physical activity, their combination, and all-cause mortality in middle-aged and older Chinese adults: The Dongfeng-Tongji cohort study

OBJECTIVES

To prospectively investigate the associations of longitudinal changes in sleep score and LTPA and their combination with all-cause mortality.

METHODS

Among 12,543 participants (mean age: 66.1 years) from the Dongfeng-Tongji cohort, we calculated sleep score (range, 0-4, integrating bedtime, sleep duration, sleep quality, and midday napping, higher score indicating healthier sleep) and LTPA at baseline (2008-2010) and the first follow-up (2013) surveys and their 5-year changes (defining stable sleep score as no change and stable LTPA as change within 150 min/week). We prospectively documented deaths from the first follow-up survey (2013) through December 31, 2018.

RESULTS

During a mean 5.5-year follow-up, 792 deaths occurred. The 5-year changes in sleep score and LTPA were inversely associated with all-cause mortality risk, regardless of their initial values. When assessing 5-year changes in sleep score and LTPA jointly, compared with the stable sleep score-stable LTPA group, the decreased sleep score-decreased LTPA group had a 40 % (5-85 %) higher all-cause mortality risk, whereas the increased sleep score-increased LTPA group had a 34 % (9-52 %) lower risk. The direction of the joint association was mainly driven by sleep score change. Participants maintaining sleep scores ≥ 3 and LTPA ≥ 150 min/week over 5 years had a 44 % (28-56 %) lower all-cause mortality risk.

CONCLUSIONS

Promoting sleep hygiene and LTPA together may benefit efforts in reducing mortality risk, with particular attention to monitoring long-term sleep health.

Multiplex influences on vigilance and biochemical variables induced by sleep deprivation

Introduction

Sleep loss and sleep deprivation (SD) cause deleterious influences on health, cognition, mood and behaviour. Nevertheless, insufficient sleep and SD are prevalent across many industries and occur in various emergencies. The deleterious consequences of SD have yet to be fully elucidated. This study aimed to assess the extensive influences of SD on physiology, vigilance, and plasma biochemical variables.

Methods

Seventeen volunteers were recruited to participate in a 32.5-h SD experiment. Multiple physiological and cognitive variables, including tympanic temperature, blood oxygen saturation (SaO2), and vigilance were recorded. Urinal/salivary samples were collected and subjected to cortisol or cortisone analysis, and plasma samples were subjected to transcriptomic analysis of circular RNA (circRNA) expression using microarray. Plasma neurotransmitters were measured by targeted metabolic analysis, and the levels of inflammatory factors were assessed by antibody microarray.

Results

The volunteers showed significantly increased sleepiness and decreased vigilance during SD, and the changes in circadian rhythm and plasma biochemistry were observed. The plasma calcium (p = 0.0007) was induced by SD, while ischaemia-modified albumin (IMA, p = 0.0030) and total bile acid (TBA, p = 0.0157) decreased. Differentially expressed circRNAs in plasma were identified, which are involved in multiple signaling pathways including neuronal regulation and immunity. Accordingly, SD induced a decrease in 3-hydroxybutyric acid (3OBH, p = 0.0002) and an increase in thyroxine (T4, p < 0.0001) in plasma. The plasma anti-inflammatory cytokine IL-10 was downregulated while other ten inflammatory factors were upregulated.

Conclusion

This study demonstrates that SD influences biochemical, physiological, cognitive variables, and the significantly changed variables may serve as candidates of SD markers. These findings may further our understanding of the detrimental consequence of sleep disturbance at multiple levels.

Human serum proteomics reveals a molecular signature after one night of sleep deprivation

Study Objectives

Sleep deprivation is highly prevalent and caused by conditions such as night shift work or illnesses like obstructive sleep apnea. Compromised sleep affects cardiovascular-, immune-, and neuronal systems. Recently, we published human serum proteome changes after a simulated night shift. This pilot proteomic study aimed to further explore changes in human blood serum after 6 hours of sleep deprivation at night.

Methods

Human blood serum samples from eight self-declared healthy females were analyzed using Orbitrap Eclipse mass spectrometry (MS-MS) and high-pressure liquid chromatography. We used a within-participant design, in which the samples were taken after 6 hours of sleep at night and after 6 hours of sleep deprivation the following night. Systems biological databases and bioinformatic software were used to analyze the data and comparative analysis were done with other published sleep-related proteomic datasets.

Results

Out of 494 proteins, 66 were found to be differentially expressed proteins (DEPs) after 6 hours of sleep deprivation. Functional enrichment analysis revealed the associations of these DEPs with several biological functions related to the altered regulation of cellular processes such as platelet degranulation and blood coagulation, as well as associations with different curated gene sets.

Conclusions

This study presents serum proteomic changes after 6 hours of sleep deprivation, supports previous findings showing that short sleep deprivation affects several biological processes, and reveals a molecular signature of proteins related to pathological conditions such as altered coagulation and platelet function, impaired lipid and immune function, and cell proliferation. Data are available via ProteomeXchange with identifier PXD045729. This paper is part of the Genetic and other molecular underpinnings of sleep, sleep disorders, and circadian rhythms including translational approaches Collection.

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 regulation and host genetics

Due to the multifactorial and complex nature of rest, we focus on phenotypes related to sleep. Sleep regulation is a multifactorial process. In this chapter, we focus on those phenotypes inherent to sleep that are highly prevalent in the population, and that can be modulated by lifestyle, such as sleep quality and duration, insomnia, restless leg syndrome and daytime sleepiness. We, therefore, leave in the background those phenotypes that constitute infrequent pathologies or for which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Similarly, the regulation of sleep quality is intimately linked to the regulation of the circadian rhythm. Although this relationship is discussed in the sections that require it, the in-depth study of circadian rhythm regulation at the molecular level deserves a separate chapter, and this is how it is dealt with in this volume.

Effect of 60 days of head down tilt bed rest on amplitude and phase of rhythms in physiology and sleep in men

Twenty-four-hour rhythms in physiology and behaviour are shaped by circadian clocks, environmental rhythms, and feedback of behavioural rhythms onto physiology. In space, 24 h signals such as those associated with the light-dark cycle and changes in posture, are weaker, potentially reducing the robustness of rhythms. Head down tilt (HDT) bed rest is commonly used to simulate effects of microgravity but how HDT affects rhythms in physiology has not been extensively investigated. Here we report effects of -6° HDT during a 90-day protocol on 24 h rhythmicity in 20 men. During HDT, amplitude of light, motor activity, and wrist-temperature rhythms were reduced, evening melatonin was elevated, while cortisol was not affected during HDT, but was higher in the morning during recovery when compared to last session of HDT. During recovery from HDT, time in Slow-Wave Sleep increased. EEG activity in alpha and beta frequencies increased during NREM and REM sleep. These results highlight the profound effects of head-down-tilt-bed-rest on 24 h rhythmicity.

Sleep fragmentation induces heart failure in a hypertrophic cardiomyopathy mouse model by altering redox metabolism

Sleep fragmentation (SF) disrupts normal biological rhythms and has major impacts on cardiovascular health; however, it has never been shown to be a risk factor involved in the transition from cardiac hypertrophy to heart failure (HF). We now demonstrate devastating effects of SF on hypertrophic cardiomyopathy (HCM). We generated a transgenic mouse model harboring a patient-specific myosin binding protein C3 (MYBPC3) variant displaying HCM, and measured the progression of pathophysiology in the presence and absence of SF. SF induces mitochondrial damage, sarcomere disarray, and apoptosis in HCM mice; these changes result in a transition of hypertrophy to an HF phenotype by chiefly targeting redox metabolic pathways. Our findings for the first time show that SF is a risk factor for HF transition and have important implications in clinical settings where HCM patients with sleep disorders have worse prognosis, and strategic intervention with regularized sleep patterns might help such patients.

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.

Circadian Biology and the Neurovascular Unit

Mammalian physiology and cellular function are subject to significant oscillations over the course of every 24-hour day. It is likely that these daily rhythms will affect function as well as mechanisms of disease in the central nervous system. In this review, we attempt to survey and synthesize emerging studies that investigate how circadian biology may influence the neurovascular unit. We examine how circadian clocks may operate in neural, glial, and vascular compartments, review how circadian mechanisms regulate cell-cell signaling, assess interactions with aging and vascular comorbidities, and finally ask whether and how circadian effects and disruptions in rhythms may influence the risk and progression of pathophysiology in cerebrovascular disease. Overcoming identified challenges and leveraging opportunities for future research might support the development of novel circadian-based treatments for stroke.

Circadian disruption dysregulates lung gene expression associated with inflammatory lung injury

Rationale

Circadian systems drive the expression of multiple genes in nearly all cells and coordinate cellular-, tissue-, and system-level processes that are critical to innate immunity regulation.

Objective

We examined the effects of circadian rhythm disorganization, produced by light shift exposure, on innate immunity-mediated inflammatory lung responses including vascular permeability and gene expression in a C57BL/6J murine model of inflammatory lung injury.

Methods

A total of 32 C57BL/6J mice were assigned to circadian phase shifting (CPS) with intratracheal phosphate-buffered saline (PBS), CPS with intratracheal lipopolysaccharide (LPS), control (normal lighting) condition with intratracheal PBS, and control condition with intratracheal LPS. Bronchoalveolar lavage (BAL) protein, cell counts, tissue immunostaining, and differentially expressed genes (DEGs) were measured in lung tissues at 2 and 10 weeks.

Measurements and results

In mice exposed to both CPS and intratracheal LPS, both BAL protein and cell counts were increased at both 2 and 10 weeks compared to mice exposed to LPS alone. Multiple DEGs were identified in CPS-LPS-exposed lung tissues compared to LPS alone and were involved in transcriptional pathways associated with circadian rhythm disruption, regulation of lung permeability, inflammation with Rap1 signaling, and regulation of actin cytoskeleton. The most dysregulated pathways included myosin light chain kinase, MAP kinase, profilin 2, fibroblast growth factor receptor, integrin b4, and p21-activated kinase.

Conclusion

Circadian rhythm disruption results in exacerbated immune response and dysregulated expression of cytoskeletal genes involved in the regulation of epithelial and vascular barrier integrity-the mechanistic underpinnings of acute lung injury. Further studies need to explore circadian disorganization as a druggable target.

Association between sleep traits and biological aging risk: a Mendelian randomization study based on 157 227 cases and 179 332 controls

STUDY OBJECTIVES

To investigate whether sleep traits are associated with the risk of biological aging using a case-control design with Mendelian randomization (MR) analyses.

METHODS

We studied 336 559 participants in the UK Biobank cohort, including 157 227 cases of accelerated biological aging and 179 332 controls. PhenoAge, derived from clinical traits, estimated biological ages, and the discrepancies from chronological age were defined as age accelerations (PhenoAgeAccel). Sleep behaviors were assessed with a standardized questionnaire. propensity score matching matched control participants to age-accelerated participants, and a conditional multivariable logistic regression model estimated odds ratio (OR) and 95% confidence intervals (95% CI). Causal relationships between sleep traits and PhenoAgeAccel were explored using linear and nonlinear MR methods.

RESULTS

A U-shaped association was found between sleep duration and PhenoAgeAccel risk. Short sleepers had a 7% higher risk (OR = 1.07; 95% CI: 1.03 to 1.11), while long sleepers had an 18% higher risk (OR = 1.18; 95% CI: 1.15 to 1.22), compared to normal sleepers (6-8 hours/day). Evening chronotype was linked to higher PhenoAgeAccel risk than morning chronotype (OR = 1.14; 95% CI: 1.10 to 1.18), while no significant associations were found for insomnia or snoring. Morning chronotype had a protective effect on PhenoAgeAccel risk (OR = 0.87, 95% CI: 0.79 to 0.95) per linear MR analysis. Genetically predicted sleep duration showed a U-shaped relationship with PhenoAgeAccel, suggesting a nonlinear association (pnonlinear < 0.001).

CONCLUSIONS

The study suggests that improving sleep can slow biological aging, highlighting the importance of optimizing sleep as an intervention to mitigate aging's adverse effects.

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.

What happens when the lights are left on? Transcriptomic and phenotypic habituation to light pollution

Artificial light at night (ALAN) is a ubiquitous pollutant worldwide. Exposure can induce immediate behavioral and physiological changes in animals, sometimes leading to severe health consequences. Nevertheless, many organisms persist in light-polluted environments and may have mechanisms of habituating, reducing responses to repeated exposure over time, but this has yet to be tested experimentally. Here, we tested whether zebra finches (Taeniopygia guttata) can habituate to dim (0.3 lux) ALAN, measuring behavior, physiology (oxidative stress and telomere attrition), and gene expression in a repeated measures design, over 6 months. We present evidence of tolerance to chronic exposure, persistent behavioral responses lasting 8 weeks post-exposure, and attenuation of responses to re-exposure. Oxidative stress decreased under chronic ALAN. Changes in the blood transcriptome revealed unique responses to past exposure and re-exposure. Results demonstrate organismal resilience to chronic stressors and shed light on the capacity of birds to persist in an increasingly light-polluted world.

Circadian immunity from bench to bedside: a practical guide

The immune system is built to counteract unpredictable threats, yet it relies on predictable cycles of activity to function properly. Daily rhythms in immune function are an expanding area of study, and many originate from a genetically based timekeeping mechanism known as the circadian clock. The challenge is how to harness these biological rhythms to improve medical interventions. Here, we review recent literature documenting how circadian clocks organize fundamental innate and adaptive immune activities, the immunologic consequences of circadian rhythm and sleep disruption, and persisting knowledge gaps in the field. We then consider the evidence linking circadian rhythms to vaccination, an important clinical realization of immune function. Finally, we discuss practical steps to translate circadian immunity to the patient's bedside.

Sleep and allergic diseases among young Chinese adults from the Singapore/Malaysia Cross-Sectional Genetic Epidemiology Study (SMCGES) cohort

BACKGROUND AND OBJECTIVE

Sleep disruption has been shown to affect immune function and thus influence allergic disease manifestation. The specific effects of sleep on allergic diseases, however, are less well-established; hence, in a unique population of young Chinese adults, we investigated the association between sleep and allergic disease.

METHODS

Young Chinese adults recruited from Singapore in the Singapore/Malaysia Cross-Sectional Genetic Epidemiology Study (SMCGES) were analyzed. We used the International Study of Asthma and Allergies in Childhood (ISAAC) protocol and a skin prick test to determine atopic dermatitis (AD), allergic rhinitis (AR), and asthma status. Information regarding total sleep time (TST) and sleep quality (SQ) was also obtained.

RESULTS

Of 1558 participants with a mean age of 25.0 years (SD = 7.6), 61.4% were female, and the mean total sleep time (TST) was 6.8 h (SD = 1.1). The proportions of AD, AR, and asthma were 24.5% (393/1542), 36.4% (987/1551), and 14.7% (227/1547), respectively. 59.8% (235/393) of AD cases suffered from AD-related sleep disturbances, 37.1% (209/564) of AR cases suffered from AR-related sleep disturbances, and 25.1% (57/227) of asthma cases suffered from asthma-related sleep disturbances. Only asthma cases showed a significantly lower mean TST than those without asthma (p = 0.015). Longer TST was significantly associated with lower odds of AR (OR = 0.905, 95% CI = 0.820-0.999) and asthma (OR = 0.852, 95% CI = 0.746-0.972). Linear regression analyses showed that lower TST was significantly associated with asthma (β =  - 0.18, SE = 0.076, p-value = 0.017), and AR when adjusted for AR-related sleep disturbances (β =  - 0.157, SE = 0.065, p-value = 0.016). Only sleep disturbances due to AR were significantly associated with a poorer SQ (OR = 1.962, 95% CI = 1.245-3.089).

CONCLUSIONS

We found that sleep quality, but not sleep duration was significantly poorer among AD cases, although the exact direction of influence could not be determined. In consideration of the literature coupled with our findings, we posit that TST influences allergic rhinitis rather than vice versa. Finally, the association between TST and asthma is likely mediated by asthma-related sleep disturbances, since mean TST was significantly lower among those with nighttime asthma symptoms. Future studies could consider using objective sleep measurements coupled with differential expression analysis to investigate the pathophysiology of sleep and allergic diseases.

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.

Sleep deprivation reduced LPS-induced IgG2b production by up-regulating BMAL1 and CLOCK expression

Sleep deprivation (SD) weakens the immune system and leads to increased susceptibility to infectious or inflammatory diseases. However, it is still unclear how SD affects humoral immunity. In the present study, sleep disturbance was conducted using an sleep deprivation instrument, and the bacterial endotoxin lipopolysaccharide (LPS) was used to activate the immune response. It was found that SD-pretreatment reduced LPS-induced IgG2b+ B cells and IgG2b isotype antibody production in lymphocytes of spleen. And, SD-pretreatment decreased the proportion of CD4+T cells, production of CD4+T cells derived TGF-β1 and its contribution in helping IgG2b production. Additionally, BMAL1 and CLOCK were selectively up-regulated in lymphocytes after SD. Importantly, BMAL1 and CLOCK deficiency contributed to TGF-β1 expression and production of IgG2b+ B cells. Thus, our results provide a novel insight to explain the involvement of BMAL1 and CLOCK under SD stress condition, and their roles in inhibiting TGF-β1 expression and contributing to reduction of LPS induced IgG2b production.

Sleep and circadian rhythmicity as entangled processes serving homeostasis

Sleep is considered essential for the brain and body. A predominant concept is that sleep is regulated by circadian rhythmicity and sleep homeostasis, processes that were posited to be functionally and mechanistically separate. Here we review and re-evaluate this concept and its assumptions using findings from recent human and rodent studies. Alterations in genes that are central to circadian rhythmicity affect not only sleep timing but also putative markers of sleep homeostasis such as electroencephalogram slow-wave activity (SWA). Perturbations of sleep change the rhythmicity in the expression of core clock genes in tissues outside the central clock. The dynamics of recovery from sleep loss vary across sleep variables: SWA and immediate early genes show an early response, but the recovery of non-rapid eye movement and rapid eye movement sleep follows slower time courses. Changes in the expression of many genes in response to sleep perturbations outlast the effects on SWA and time spent asleep. These findings are difficult to reconcile with the notion that circadian- and sleep-wake-driven processes are mutually independent and that the dynamics of sleep homeostasis are reflected in a single variable. Further understanding of how both sleep and circadian rhythmicity contribute to the homeostasis of essential physiological variables may benefit from the assessment of multiple sleep and molecular variables over longer time scales.

Time-of-day-dependent variation of the human liver transcriptome and metabolome is disrupted in MASLD

Background & Aims

Liver homeostasis is ensured in part by time-of-day-dependent processes, many of them being paced by the molecular circadian clock. Liver functions are compromised in metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), and clock disruption increases susceptibility to MASLD progression in rodent models. We therefore investigated whether the time-of-day-dependent transcriptome and metabolome are significantly altered in human steatotic and MASH livers.

Methods

Liver biopsies, collected within an 8 h-window from a carefully phenotyped cohort of 290 patients and histologically diagnosed to be either normal, steatotic or MASH hepatic tissues, were analyzed by RNA sequencing and unbiased metabolomic approaches. Time-of-day-dependent gene expression patterns and metabolomes were identified and compared between histologically normal, steatotic and MASH livers.

Results

Herein, we provide a first-of-its-kind report of a daytime-resolved human liver transcriptome-metabolome and associated alterations in MASLD. Transcriptomic analysis showed a robustness of core molecular clock components in steatotic and MASH livers. It also revealed stage-specific, time-of-day-dependent alterations of hundreds of transcripts involved in cell-to-cell communication, intracellular signaling and metabolism. Similarly, rhythmic amino acid and lipid metabolomes were affected in pathological livers. Both TNFα and PPARγ signaling were predicted as important contributors to altered rhythmicity.

Conclusion

MASLD progression to MASH perturbs time-of-day-dependent processes in human livers, while the differential expression of core molecular clock components is maintained.

Impact and implications

This work characterizes the rhythmic patterns of the transcriptome and metabolome in the human liver. Using a cohort of well-phenotyped patients (n = 290) for whom the time-of-day at biopsy collection was known, we show that time-of-day variations observed in histologically normal livers are gradually perturbed in liver steatosis and metabolic dysfunction-associated steatohepatitis. Importantly, these observations, albeit obtained across a restricted time window, provide further support for preclinical studies demonstrating alterations of rhythmic patterns in diseased livers. On a practical note, this study indicates the importance of considering time-of-day as a critical biological variable which may significantly affect data interpretation in animal and human studies of liver diseases.

Astrocytic insulin receptor controls circadian behavior via dopamine signaling in a sexually dimorphic manner

Mammalian circadian clocks respond to feeding and light cues, adjusting internal rhythms with day/night cycles. Astrocytes serve as circadian timekeepers, driving daily physiological rhythms; however, it's unknown how they ensure precise cycle-to-cycle rhythmicity. This is critical for understanding why mistimed or erratic feeding, as in shift work, disrupts circadian physiology- a condition linked to type 2 diabetes and obesity. Here, we show that astrocytic insulin signaling sets the free-running period of locomotor activity in female mice and food entrainment in male mice. Additionally, ablating the insulin receptor in hypothalamic astrocytes alters cyclic energy homeostasis differently in male and female mice. Remarkably, the mutants exhibit altered dopamine metabolism, and the pharmacological modulation of dopaminergic signaling partially restores distinct circadian traits in both male and female mutant mice. Our findings highlight the role of astrocytic insulin-dopaminergic signaling in conveying time-of-feeding or lighting cues to the astrocyte clock, thus governing circadian behavior in a sex-specific manner.

Sleep insufficiency, circadian rhythms, and metabolomics: the connection between metabolic and sleep disorders

PURPOSE

US adults who report experiencing insufficient sleep are more likely to suffer from metabolic disorders such as hyperlipidemia, diabetes, and obesity than those with sufficient sleep. Less is understood about the underlying molecular mechanisms connecting these phenomena. A systematic, qualitative review of metabolomics studies exploring metabolic changes in response to sleep insufficiency, sleep deprivation, or circadian disruption was conducted in accordance with PRISMA guidelines.

METHODS

An electronic literature review in the PubMed database was performed considering publications through May 2021 and screening and eligibility criteria were applied to articles retrieved. The following keywords were used: "metabolomics" and "sleep disorders" or "sleep deprivation" or "sleep disturbance" or "circadian rhythm." After screening and addition of studies included from reference lists of retrieved studies, 16 records were identified for review.

RESULTS

Consistent changes in metabolites were observed across studies between individuals experiencing sleep deprivation compared to non-sleep deprived controls. Significant increases in phosphatidylcholines, acylcarnitines, sphingolipids, and other lipids were consistent across studies. Increased levels of amino acids such as tryptophan and phenylalanine were also noted. However, studies were limited to small samples of young, healthy, mostly male participants conducted in short inpatient sessions, limiting generalizability.

CONCLUSION

Changes in lipid and amino acid metabolites accompanying sleep deprivation and/or circadian rhythms may indicate cellular membrane and protein breakdown underlying the connection between sleep disturbance, hyperlipidemia, and other metabolic disorders. Larger epidemiological studies examining changes in the human metabolome in response to chronic insufficient sleep would help elucidate this relationship.

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.

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.

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.

Circadian Disruption in Night Shift Work and Its Association with Chronic Pulmonary Diseases

Globalization and the expansion of essential services over continuous 24 h cycles have necessitated the adaptation of the human workforce to shift-based schedules. Night shift work (NSW) causes a state of desynchrony between the internal circadian machinery and external environmental cues, which can impact inflammatory and metabolic pathways. The discovery of clock genes in the lung has shed light on potential mechanisms of circadian misalignment in chronic pulmonary disease. Here, the current knowledge of circadian clock disruption caused by NSW and its impact on lung inflammation and associated pathophysiology in chronic lung diseases, such as asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, and COVID-19, is reviewed. Furthermore, the limitations of the current understanding of circadian disruption and potential future chronotherapeutic advances are discussed.

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.

Sleep Variability, Eating Timing Variability, and Carotid Intima-Media Thickness in Early Adulthood

Background Day-to-day variability in sleep patterns and eating timing may disrupt circadian rhythms and has been linked with various adverse cardiometabolic outcomes. However, the extent to which variability in sleep patterns and eating timing relate to atherosclerotic development in subclinical stages remains unclear. Methods and Results Generally healthy adults (N=62, 29.3±7.3 years, 66% female) completed 14 days of sleep and dietary assessments via wrist accelerometry and photo-assisted diet records, respectively. Variability in sleep duration, sleep onset, eating onset (time of first caloric consumption), eating offset (time of last caloric consumption), and caloric midpoint (time at which 50% of total daily calories are consumed) were operationalized as the SD across 14 days for each variable. Separate regression models evaluated the cross-sectional associations between sleep and eating variability metrics with end-diastolic carotid intima-media thickness (CIMT) measured via ultrasonography. Models adjusted for age, sex, systolic blood pressure, sleep duration, and total energy intake. Each 60-minute increase in sleep duration SD and sleep onset SD were associated with a 0.049±0.016 mm (P=0.003) and 0.048±0.017 mm (P=0.007) greater CIMT, respectively. Variability in eating onset and offset were not associated with CIMT; however, each 60-minute increase in caloric midpoint SD was associated with a 0.033±0.015 mm greater CIMT (P=0.029). Exploratory post hoc analyses suggested that sleep duration SD and sleep onset SD were stronger correlates of CIMT than caloric midpoint SD. Conclusions Variability in sleep patterns and eating timing are positively associated with clinically relevant increases in CIMT, a biomarker of subclinical atherosclerosis, in early adulthood.

Bedtime, sleep pattern, and incident cardiovascular disease in middle-aged and older Chinese adults: The dongfeng-tongji cohort study

OBJECTIVES

To investigate the associations of bedtime and a low-risk sleep pattern with incident cardiovascular disease (CVD).

METHODS

A total of 31,500 retirees were included from the Dongfeng-Tongji cohort in 2008-2010 and 2013. Sleep information was collected by questionnaires. CVD events were identified through the health care system until December 31, 2018. Cox proportional hazards regression models were performed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

During an average follow-up of 7.2 years, 8324 cases of incident CVD, including 6557 coronary heart disease (CHD) and 1767 stroke, were documented. U-shaped associations of bedtime with the risks of incident CVD and stroke were observed. Compared with bedtime between 10:01 p.m.-11:00 p.m., the HR (95% CI) for CVD was 1.10 (1.01-1.20) for ≤9:00 p.m., 1.07 (1.01-1.13) for 9:01 p.m.-10:00 p.m., and 1.32 (1.11-1.58) for >12:00 a.m., respectively, mainly driven by stroke risk (22%, 14%, and 70% higher for ≤9:00 p.m., 9:01 p.m.-10:00 p.m., and >12:00 a.m., respectively). The number of low-risk sleep factors, namely bedtime between 10:01 p.m.-12:00 a.m., sleep duration of 7-< 8 h/night, good/fair sleep quality, and midday napping ≤60 min, exhibited dose-dependent relationships with CVD, CHD, and stroke risks. Participants with 4 low-risk sleep factors had a respective 24%, 21%, and 30% lower risk of CVD, CHD, and stroke than those with 0-1 low-risk sleep factor.

CONCLUSIONS

Individuals with early or late bedtimes had a higher CVD risk, especially stroke. Having low-risk sleep habits is associated with lower CVD risks.

Bedtime, sleep duration, and sleep quality and all-cause mortality in middle-aged and older Chinese adults: The Dongfeng-Tongji cohort study

OBJECTIVE

This study aims to investigate the associations of bedtime and its combination with sleep duration and sleep quality with all-cause mortality.

METHODS

We conducted a prospective cohort study using data collected from 2008 to 2018 in the Dongfeng-Tongji cohort. Among 40,097 participants aged 62.1 on average at baseline, we applied Cox regression models to assess hazard ratios and 95% confidence intervals for mortality risk.

RESULTS

During a mean follow-up of 8.2years, 4345 deaths were documented. U-shaped associations of bedtime and sleep duration with all-cause mortality were observed. Compared with bedtime between 10:01 PM and 11:00 PM, the hazard ratio (95% confidence interval) for all-cause mortality was 1.34 (1.20-1.49) for ≤9:00 PM, 1.18 (1.09-1.27) for 9:01-10:00 PM, and 1.50 (1.13-2.00) for >12:00 AM, respectively. Participants with sleep duration of <6, 6-<7, 8-<9, and ≥9 h/night had a respective 39%, 21%, 11%, and 25% higher all-cause mortality risk than those sleeping 7-<8 h/night. Additionally, participants with a healthy sleep score of 3, characterized as proper bedtime (10:01 PM-12:00 AM), moderate sleep duration (7-<8h/night), and good/fair sleep quality, had a significantly 36% (hazard ratio, 0.64; 95% confidence interval, 0.56-0.74) lower all-cause mortality risk than those with a score of 0.

CONCLUSIONS

Individuals with early or late bedtimes and short or long sleep duration were at higher all-cause mortality risks. Having healthy sleep habits may significantly reduce death risk.

Dominant constraints on the evolution of rhythmic gene expression

Although the individual transcriptional regulators of the core circadian clock are distinct among different organisms, the autoregulatory feedback loops they form are conserved. This unified design principle explains how daily physiological activities oscillate across species. However, it is unknown whether analogous design principles govern the gene expression output of circadian clocks. In this study, we performed a comparative analysis of rhythmic gene expression in eight diverse species and identified four common distribution patterns of cycling gene expression across these species. We hypothesized that the maintenance of reduced energetic costs constrains the evolution of rhythmic gene expression. Our large-scale computational simulations support this hypothesis by showing that selection against high-energy expenditure completely regenerates all cycling gene patterns. Moreover, we find that the peaks of rhythmic expression have been subjected to this type of selective pressure. The results suggest that selective pressure from circadian regulation efficiently removes unnecessary gene products from the transcriptome, thereby significantly impacting its evolutionary path.

Sleep Deficiency and Cardiometabolic Disease

Epidemiologic studies have demonstrated that short sleep duration is associated with an increased risk of cardio-metabolic health outcomes including cardiovascular disease mortality, coronary heart disease, type 2 diabetes mellitus, hypertension, and metabolic syndrome. Experimental sleep restriction studies have sought to explain these findings. This review describes the main evidence of these associations and possible mechanisms explaining them. Whether sleep extension reverses these now widely acknowledged adverse health effects and the feasibility of implementing such strategies on a public health level is discussed.

Experimental design and power calculation in omics circadian rhythmicity detection using the cosinor model

Circadian clocks are 24-h endogenous oscillators in physiological and behavioral processes. Though recent transcriptomic studies have been successful in revealing the circadian rhythmicity in gene expression, the power calculation for omics circadian analysis have not been fully explored. In this paper, we develop a statistical method, namely CircaPower, to perform power calculation for circadian pattern detection. Our theoretical framework is determined by three key factors in circadian gene detection: sample size, intrinsic effect size and sampling design. Via simulations, we systematically investigate the impact of these key factors on circadian power calculation. We not only demonstrate that CircaPower is fast and accurate, but also show its underlying cosinor model is robust against variety of violations of model assumptions. In real applications, we demonstrate the performance of CircaPower using mouse pan-tissue data and human post-mortem brain data, and illustrate how to perform circadian power calculation using mouse skeleton muscle RNA-Seq pilot as case study. Our method CircaPower has been implemented in an R package, which is made publicly available on GitHub ( https://github.com/circaPower/circaPower).

Age-related changes in circadian regulation of the human plasma lipidome

Aging alters the amplitude and phase of centrally regulated circadian rhythms. Here we evaluate whether peripheral circadian rhythmicity in the plasma lipidome is altered by aging through retrospective lipidomics analysis on plasma samples collected in 24 healthy individuals (9 females; mean ± SD age: 40.9 ± 18.2 years) including 12 younger (4 females, 23.5 ± 3.9 years) and 12 middle-aged older, (5 females, 58.3 ± 4.2 years) individuals every 3 h throughout a 27-h constant routine (CR) protocol, which allows separating evoked changes from endogenously generated oscillations in physiology. Cosinor regression shows circadian rhythmicity in 25% of lipids in both groups. On average, the older group has a ~14% lower amplitude and a ~2.1 h earlier acrophase of the lipid circadian rhythms (both, p ≤ 0.001). Additionally, more rhythmic circadian lipids have a significant linear component in addition to the sinusoidal across the 27-h CR in the older group (44/56) compared to the younger group (18/58, p < 0.0001). Results from individual-level data are consistent with group-average results. Results indicate that prevalence of endogenous circadian rhythms of the human plasma lipidome is preserved with healthy aging into middle-age, but significant changes in rhythmicity include a reduction in amplitude, earlier acrophase, and an altered temporal relationship between central and lipid rhythms.

The effect of off-hours hip surgery on patients' outcomes: a RECORD-compliant retrospective, propensity score-matched cohort study

BACKGROUND

Off-hours working may have negative impacts on the performance of clinicians, leading to possible adverse outcomes of patients. We aimed to explore the impact of off-hours hip surgery on early postoperative outcomes.

METHODS

All patients who underwent hip surgery between January 2015, and December 2020 in our hospital were evaluated in this retrospective cohort study. We measured in-hospital mortality, some postoperative complications, and some intraoperative prognostic indicators. Propensity score matching (PSM) was used to adjust for confounding baseline factors.

RESULTS

We identified 143 patients in the original cohort. After PSM, 266 patients in the on-hours group were matched with 105 similar patients in the off-hours group. Compared with the on-hours group, the off-hours group had more general anesthesia (81.0% vs. 62.4%; RR, 1.30; 95% CI, 1.14 to 1.48; P=0.001), higher amount of intraoperative CRBC (0 U [0-2] vs. 0 U [0-0]; P=0.032) and FFP transfusion (0 mL [0-150] vs. 0 mL [0-0]; P=0.005), higher dosage of intraoperative sufentanil (24.5±14.5 μg vs. 20.7±13.9 μg; P=0.020), higher incidence of postoperative renal dysfunction (13.3% vs. 6.4%; RR, 2.09; 95% CI, 1.07 to 4.08; P=0.029), hypotension (2.9% vs. 0%; P=0.022), and hypoxemia (3.8% vs. 0.4%; RR, 10.13; 95% CI, 1.15 to 89.61; P=0.024), and higher in-hospital mortality (2.9% vs. 0%; P=0.022).

CONCLUSIONS

Off-hours hip surgery was associated with adverse early postoperative prognosis, suggesting that more attention should be paid to off-hours hip surgery.

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.

Identification and validation of a novel prognostic circadian rhythm-related gene signature for stomach adenocarcinoma

Circadian rhythm genes were reported to be strongly associated with the development and prognosis of circadian rhythm disorders related to stomach adenocarcinoma (STAD), which is one of the most prevalent cancers. This study aimed to identify a circadian rhythm-related gene signature that could help predict STAD outcome. Using bioinformatics analysis approaches, 105 genes were examined in 350 patients with STAD. Overall, six hub-type circadian rhythm-associated genes (GNA11, PER1, SOX14, EZH2, MAGED1, and NR1D1) were identified using univariate and multivariate Cox regression analyses. These genes were then used to build a genetic predictive model, which was further validated using a publicly available dataset (GSE26899). Overall, genes associated with the circadian rhythm were found to be substantially correlated with the characteristics of the STAD patients (grade, sex, and M stage). In addition, the circadian rhythm-related gene signature was significantly associated with the MAPK and Notch signaling pathways, which are known risk factors for poorer STAD outcome. Taken together, these findings suggest that the herein proposed prognostic model based on six circadian rhythm-associated genes may have predictive value and potential application for clinical decision-making and for personalized treatment of STAD.