Blood transcriptome based biomarkers for human circadian phase

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.

Estimating dim light melatonin onset time in children using delta changes in melatonin

We aimed to establish a method for estimating dim light melatonin onset (DLMO) using mathematical slopes calculated from melatonin concentrations at three sampling points before and after sleep in children. The saliva of 30 children (mean age ± SD: 10.2 ± 1.3 years old) was collected under dim-light conditions up to six times every hour starting at 17:30 (t17), namely, 18:30 (t18), 19:30 (t19), 20:30 (t20), 21:30 (t21), 22:30 (t22), and 23:30 (t23), in the evening, and at 6:00 (t30) the following morning. We calculated SLOPE on (mathematical slope between melatonin concentrations at t18 and t20, t21 or t22), SLOPE off (the slope between t20, t21 or t22, and t30), and Δ S L O P E , which is generated by subtracting SLOPE on from SLOPE off . DLMO was estimated by multiple regression analysis with the leave-one-out cross-validation (LOOCV) method using SLOPE on and SLOPE off , and Δ S L O P E . The intraclass correlation coefficient (ICC) between the estimated and measured DLMOs was used as the index of estimation accuracy. DLMOs estimated using multiple regression equations with SLOPE on and SLOPE off yielded significant ICCs for the measured DLMOs, with the largest ICC at t20 (ICC = 0.634). Additionally, the ICC between the estimated and measured DLMOs using the equation with Δ S L O P E was significant, with a larger ICC at t20 (ICC = 0.726) than that of the equation with SLOPE on and SLOPE off . Our results showed that DLMO could be estimated with a certain level of accuracy from salivary melatonin levels at three time points before and after sleep in children.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-023-00493-x.

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.

Tumor circadian clock strength influences metastatic potential and predicts patient prognosis in luminal A breast cancer

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular circadian rhythms in noncancerous and cancerous human breast tissues and their clinical relevance are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time-stamped biopsies with public datasets. For noncancerous breast tissue, inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype-specific changes in circadian organization. Luminal A organoids and informatic ordering of luminal A samples exhibit continued, albeit dampened and reprogrammed rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among luminal A samples. Cycling of EMT pathway genes was markedly increased in high-magnitude luminal A tumors. Surprisingly, patients with high-magnitude tumors had reduced 5-y survival. Correspondingly, 3D luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype-specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis.

Circadian protein expression patterns in healthy young adults

OBJECTIVES

To explore how the blood plasma proteome fluctuates across the 24-hour day and identify a subset of proteins that show endogenous circadian rhythmicity.

METHODS

Plasma samples from 17 healthy adults were collected hourly under controlled conditions designed to unmask endogenous circadian rhythmicity; in a subset of 8 participants, we also collected samples across a day on a typical sleep-wake schedule. A total of 6916 proteins were analyzed from each sample using the SomaScan aptamer-based multiplexed platform. We used differential rhythmicity analysis based on a cosinor model with mixed effects to identify a subset of proteins that showed circadian rhythmicity in their abundance.

RESULTS

One thousand and sixty-three (15%) proteins exhibited significant daily rhythmicity. Of those, 431 (6.2%) proteins displayed consistent endogenous circadian rhythms on both a sleep-wake schedule and under controlled conditions: it included both known and novel proteins. When models were fitted with two harmonics, an additional 259 (3.7%) proteins exhibited significant endogenous circadian rhythmicity, indicating that some rhythmic proteins cannot be solely captured by a simple sinusoidal model. Overall, we found that the largest number of proteins had their peak levels in the late afternoon/evening, with another smaller group peaking in the early morning.

CONCLUSIONS

This study reveals that hundreds of plasma proteins exhibit endogenous circadian rhythmicity in humans. Future analyses will likely reveal novel physiological pathways regulated by circadian clocks and pave the way for improved diagnosis and treatment for patients with circadian disorders and other pathologies. It will also advance efforts to include knowledge about time-of-day, thereby incorporating circadian medicine into personalized medicine.

TimeTeller: A tool to probe the circadian clock as a multigene dynamical system

Recent studies have established that the circadian clock influences onset, progression and therapeutic outcomes in a number of diseases including cancer and heart diseases. Therefore, there is a need for tools to measure the functional state of the molecular circadian clock and its downstream targets in patients. Moreover, the clock is a multi-dimensional stochastic oscillator and there are few tools for analysing it as a noisy multigene dynamical system. In this paper we consider the methodology behind TimeTeller, a machine learning tool that analyses the clock as a noisy multigene dynamical system and aims to estimate circadian clock function from a single transcriptome by modelling the multi-dimensional state of the clock. We demonstrate its potential for clock systems assessment by applying it to mouse, baboon and human microarray and RNA-seq data and show how to visualise and quantify the global structure of the clock, quantitatively stratify individual transcriptomic samples by clock dysfunction and globally compare clocks across individuals, conditions and tissues thus highlighting its potential relevance for advancing circadian medicine.

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.

Current Considerations in the Diagnosis and Treatment of Circadian Rhythm Sleep-Wake Disorders in Children

Circadian Rhythm Sleep-Wake Disorders (CRSWDs) are important sleep disorders whose unifying feature is a mismatch between the preferred or required times for sleep and wakefulness and the endogenous circadian drives for these. Their etiology, presentation, and treatment can be different in pediatric patients as compared to adults. Evaluation of these disorders must be performed while viewed through the lens of a patient's comorbid conditions. Newer methods of assessment promise to provide greater diagnostic clarity and critical insights into how circadian physiology affects overall health and disease states. Effective clinical management of CRSWDs is multimodal, requiring an integrated approach across disciplines. Therapeutic success depends upon appropriately timed nonpharmacologic and pharmacologic interventions. A better understanding of the genetic predispositions for and causes of CRSWDs has led to novel clinical opportunities for diagnosis and improved therapeutics.

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.

Delayed sleep phase disorder during the COVID-19 pandemic and its health implications

Circadian rhythm sleep disorders are alterations that are characterized by a shift in the sleep-wake cycle relative to day and night, such as the delayed sleep phase disorder (DSPD), which is a retard of at least 2 hours in the sleep start. Typically, the patient falls asleep after 2 a.m. and wakes up after 10 a.m. and with symptom of sleep onset insomnia. The prevalence of DSPD in young adults is 0.48%, increasing to 3.3% in adolescents. Interestingly, patients with COVID-19 infection report anxiety due to the intensive care unit lockdown and constant exposure to bright light. In addition, post-COVID patients have an increased risk of developing DSPD. For example, in adolescent post-COVID patients, the prevalence of DSPD increases to 63.3%. Patients with DSPD also have alterations in metabolic health, poor school performance, cognitive impairment, and a higher risk of developing other diseases. The objective of the present review is therefore to describe the characteristics of DSPD during the COVID-19 pandemic and to outline its possible implications for physical health (eg, metabolism) and mental health (eg, anxiety or depression).

Circadian rhythms, gut microbiota, and diet: Possible implications for health

AIMS

Over the past years, interest in chrono-nutrition has grown enormously as the fundamental role of circadian rhythms in regulating most physiological and metabolic processes has become clearer. Recently, the influence of circadian rhythms on the gut microbiota (GM) composition has also emerged, as more than half of the total microbial composition fluctuates rhythmically throughout the day. At the same time, other studies have observed that the GM itself synchronises the host's circadian biological clock through signals of a different nature. Therefore, it has been hypothesised that there is a two-way communication between the circadian rhythms of the host and the GM, but researchers have only just begun to identify some of its action mechanisms. The manuscript aim is, therefore, to gather and combine the latest evidence in the field of chrono-nutrition with the more recent research on the GM, in order to investigate their relationship and their potential impact on human health.

DATA SYNTHESIS

Considering current evidence, a desynchronization of circadian rhythms is closely associated with an alteration in the abundance and functionality of the gut microbiota with consequent deleterious effects on health, such as increased risk of numerous pathologies, including cardiovascular disease, cancer, irritable bowel disease, and depression. A key role in maintaining the balance between circadian rhythms and GM seems to be attributed to meal-timing and diet quality, as well as to certain microbial metabolites, in particular short-chain fatty acids.

CONCLUSIONS

Future studies are needed to decipher the link between the circadian rhythms and specific microbial patterns in relation to different disease frameworks.

Review and standard operating procedures for collection of biospecimens and analysis of biomarkers in new onset refractory status epilepticus

New onset refractory status epilepticus (NORSE), including its subtype with a preceding febrile illness known as febrile infection-related epilepsy syndrome (FIRES), is one of the most severe forms of status epilepticus. The exact causes of NORSE are currently unknown, and there is so far no disease-specific therapy. Identifying the underlying pathophysiology and discovering specific biomarkers, whether immunologic, infectious, genetic, or other, may help physicians in the management of patients with NORSE. A broad spectrum of biomarkers has been proposed for status epilepticus patients, some of which were evaluated for patients with NORSE. Nonetheless, none has been validated, due to significant variabilities in study cohorts, collected biospecimens, applied analytical methods, and defined outcome endpoints, and to small sample sizes. The NORSE Institute established an open NORSE/FIRES biorepository for health-related data and biological samples allowing the collection of biospecimens worldwide, promoting multicenter research and sharing of data and specimens. Here, we suggest standard operating procedures for biospecimen collection and biobanking in this rare condition. We also propose criteria for the appropriate use of previously collected biospecimens. We predict that the widespread use of standardized procedures will reduce heterogeneity, facilitate the future identification of validated biomarkers for NORSE, and provide a better understanding of the pathophysiology and best clinical management for these patients.

Subtype-specific circadian clock dysregulation modulates breast cancer biology, invasiveness, and prognosis

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular rhythms in non-cancerous and cancerous human breast tissues are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time-stamped biopsies with public datasets. For non-cancerous tissue, the inferred order of core-circadian genes matches established physiology. Inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype-specific changes in circadian organization. Luminal A organoids and informatic ordering of Luminal A samples exhibit continued, albeit disrupted rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among Luminal A samples. Cycling of EMT pathway genes was markedly increased in high-magnitude Luminal A tumors. Patients with high-magnitude tumors had reduced 5-year survival. Correspondingly, 3D Luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype-specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis.

Machine learning estimation of human body time using metabolomic profiling

Circadian rhythms influence physiology, metabolism, and molecular processes in the human body. Estimation of individual body time (circadian phase) is therefore highly relevant for individual optimization of behavior (sleep, meals, sports), diagnostic sampling, medical treatment, and for treatment of circadian rhythm disorders. Here, we provide a partial least squares regression (PLSR) machine learning approach that uses plasma-derived metabolomics data in one or more samples to estimate dim light melatonin onset (DLMO) as a proxy for circadian phase of the human body. For this purpose, our protocol was aimed to stay close to real-life conditions. We found that a metabolomics approach optimized for either women or men under entrained conditions performed equally well or better than existing approaches using more labor-intensive RNA sequencing-based methods. Although estimation of circadian body time using blood-targeted metabolomics requires further validation in shift work and other real-world conditions, it currently may offer a robust, feasible technique with relatively high accuracy to aid personalized optimization of behavior and clinical treatment after appropriate validation in patient populations.

Rhythms in barriers and fluids: Circadian clock regulation in the aging neurovascular unit

The neurovascular unit is where two very distinct physiological systems meet: The central nervous system (CNS) and the blood. The permeability of the barriers separating these systems is regulated by time, including both the 24 h circadian clock and the longer processes of aging. An endogenous circadian rhythm regulates the transport of molecules across the blood-brain barrier and the circulation of the cerebrospinal fluid and the glymphatic system. These fluid dynamics change with time of day, and with age, and especially in the context of neurodegeneration. Factors may differ depending on brain region, as can be highlighted by consideration of circadian regulation of the neurovascular niche in white matter. As an example of a potential target for clinical applications, we highlight chaperone-mediated autophagy as one mechanism at the intersection of circadian dysregulation, aging and neurodegenerative disease. In this review we emphasize key areas for future research.

Desynchronizing the sleep---wake cycle from circadian timing to assess their separate contributions to physiology and behaviour and to estimate intrinsic circadian period

Circadian clocks drive cyclic variations in many aspects of physiology, but some daily variations are evoked by periodic changes in the environment or sleep-wake state and associated behaviors, such as changes in posture, light levels, fasting or eating, rest or activity and social interactions; thus, it is often important to quantify the relative contributions of these factors. Yet, circadian rhythms and these evoked effects cannot be separated under typical 24-h day conditions, because circadian phase and the length of time awake or asleep co-vary. Nathaniel Kleitman's forced desynchrony (FD) protocol was designed to assess endogenous circadian rhythmicity and to separate circadian from evoked components of daily rhythms in multiple parameters. Under FD protocol conditions, light intensity is kept low to minimize its impact on the circadian pacemaker, and participants have sleep-wake state and associated behaviors scheduled to an imposed non-24-h cycle. The period of this imposed cycle, Τ, is chosen so that the circadian pacemaker cannot entrain to it and therefore continues to oscillate at its intrinsic period (τ, ~24.15 h), ensuring circadian components are separated from evoked components of daily rhythms. Here we provide detailed instructions and troubleshooting techniques on how to design, implement and analyze the data from an FD protocol. We provide two procedures: one with general guidance for designing an FD study and another with more precise instructions for replicating one of our previous FD studies. We discuss estimating circadian parameters and quantifying the separate contributions of circadian rhythmicity and the sleep-wake cycle, including statistical analysis procedures and an R package for conducting the non-orthogonal spectral analysis method that enables an accurate estimation of period, amplitude and phase.

Sex Inclusion in Transcriptome Studies of Daily Rhythms

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

Why the worsening at rest and worsening at night criteria for Restless Legs Syndrome are listed separately: review of the circadian literature on RLS and suggestions for future directions

The field of circadian research on Restless Legs Syndrome (RLS) and periodic limb movements (PLMs) is reviewed in general. RLS has five obligatory criteria for diagnosis: (1) an urge to move the legs often accompanied by uncomfortable leg sensations; (2) symptoms are worse at rest, i.e., lying or sitting; (3) there is a least partial and temporary relief of symptoms by activity, e.g., walking or stretching or bending the legs; (4) symptoms are worse later in the day or at night; and (5) mimics of RLS such as leg cramps and positional discomfort should be excluded by history and physical. In addition, RLS is frequently accompanied by PLMs, either periodic limb movements of sleep (PLMS) as determined by polysomnography or periodic limb movements while awake (PLMW) as determined by the suggested immobilization test (SIT). Since the criteria for RLS were based upon clinical experience only, an early question after the development of the criteria was whether criteria 2 and 4 were the same or different phenomena. In other words, were RLS patients worse at night only because they were lying down, and were RLS patients worse lying down only because it was night? Early circadian studies performed during recumbency at different times of the day suggest that the uncomfortable sensations, PLMS, and PLMW as well as voluntary movement in response to leg discomfort follow a similar circadian pattern with worsening at night independent of body position and independent of sleep timing or duration. Other studies demonstrated that RLS patients get worse when sitting or lying down independent of the time of day. These studies as a whole suggest that the worsening at rest and the worsening at night criteria for RLS are related but separate phenomena and that criteria 2 and 4 for RLS should be kept separate based upon the circadian studies, as had been the case previously based upon clinical grounds alone. To more fully prove the circadian rhythmicity of RLS, studies should be conducted to see if bright light shifts the signs and symptoms of RLS to a different circadian time in concert with circadian markers.

Inter-layer and inter-subject variability of diurnal gene expression in human skin

The skin is the largest human organ with a circadian clock that regulates its function. Although circadian rhythms in specific functions are known, rhythms in the proximal clock output, gene expression, in human skin have not been thoroughly explored. This work reports 24 h gene expression rhythms in two skin layers, epidermis and dermis, in a cohort of young, healthy adults, who maintained natural, regular sleep-wake schedules. 10% of the expressed genes showed such diurnal rhythms at the population level, of which only a third differed between the two layers. Amplitude and phases of diurnal gene expression varied more across subjects than layers, with amplitude being more variable than phases. Expression amplitudes in the epidermis were larger and more subject-variable, while they were smaller and more consistent in the dermis. Core clock gene expression was similar across layers at the population-level, but were heterogeneous in their variability across subjects. We also identified small sets of biomarkers for internal clock phase in each layer, which consisted of layer-specific non-core clock genes. This work provides a valuable resource to advance our understanding of human skin and presents a novel methodology to quantify sources of variability in human circadian rhythms.

Circadian rhythms and disorders of the timing of sleep

The daily alternation between sleep and wakefulness is one of the most dominant features of our lives and is a manifestation of the intrinsic 24 h rhythmicity underlying almost every aspect of our physiology. Circadian rhythms are generated by networks of molecular oscillators in the brain and peripheral tissues that interact with environmental and behavioural cycles to promote the occurrence of sleep during the environmental night. This alignment is often disturbed, however, by contemporary changes to our living environments, work or social schedules, patterns of light exposure, and biological factors, with consequences not only for sleep timing but also for our physical and mental health. Characterised by undesirable or irregular timing of sleep and wakefulness, in this Series paper we critically examine the existing categories of circadian rhythm sleep-wake disorders and the role of the circadian system in their development. We emphasise how not all disruption to daily rhythms is driven solely by an underlying circadian disturbance, and take a broader, dimensional approach to explore how circadian rhythms and sleep homoeostasis interact with behavioural and environmental factors. Very few high-quality epidemiological and intervention studies exist, and wider recognition and treatment of sleep timing disorders are currently hindered by a scarcity of accessible and objective tools for quantifying sleep and circadian physiology and environmental variables. We therefore assess emerging wearable technology, transcriptomics, and mathematical modelling approaches that promise to accelerate the integration of our knowledge in sleep and circadian science into improved human health.

Beyond the limits of circadian entrainment: Non-24-hour sleep-wake disorder, shift work, and social jet lag

While the vast majority of humans are able to entrain their circadian rhythm to the 24-hour light-dark cycle, there are numerous individuals who are not able to do so due to disease or societal reasons. We use computational and mathematical methods to analyze a well-established model of human circadian rhythms to address cases where individuals do not entrain to the 24-hour light-dark cycle, leading to misalignment of their circadian phase. For each case, we provide a mathematically justified strategy for how to minimize circadian misalignment. In the case of non-24-hour sleep-wake disorder, we show why appropriately timed bright light therapy induces entrainment. With regard to shift work, we explain why reentrainment times following transitions between day and night shifts are asymmetric, and how higher light intensity enables unusually rapid reentrainment after certain transitions. Finally, with regard to teenagers who engage in compensatory catch-up sleep on weekends, we propose a rule of thumb for sleep and wake onset times that minimizes circadian misalignment due to this type of social jet lag. In all cases, the primary mathematical approach involves understanding the dynamics of entrainment maps that measure the phase of the entrained rhythm with respect to the daily onset of lights.

Diurnal and circadian rhythmicity of the human blood transcriptome overlaps with organ- and tissue-specific expression of a non-human primate

Background

Twenty-four-hour rhythmicity in mammalian tissues and organs is driven by local circadian oscillators, systemic factors, the central circadian pacemaker and light-dark cycles. At the physiological level, the neural and endocrine systems synchronise gene expression in peripheral tissues and organs to the 24-h-day cycle, and disruption of such regulation has been shown to lead to pathological conditions. Thus, monitoring rhythmicity in tissues/organs holds promise for circadian medicine; however, most tissues and organs are not easily accessible in humans and alternative approaches to quantify circadian rhythmicity are needed. We investigated the overlap between rhythmic transcripts in human blood and transcripts shown to be rhythmic in 64 tissues/organs of the baboon, how these rhythms are aligned with light-dark cycles and each other, and whether timing of tissue-specific rhythmicity can be predicted from a blood sample.

Results

We compared rhythmicity in transcriptomic time series collected from humans and baboons using set logic, circular cross-correlation, circular clustering, functional enrichment analyses, and least squares regression. Of the 759 orthologous genes that were rhythmic in human blood, 652 (86%) were also rhythmic in at least one baboon tissue and most of these genes were associated with basic processes such as transcription and protein homeostasis. In total, 109 (17%) of the 652 overlapping rhythmic genes were reported as rhythmic in only one baboon tissue or organ and several of these genes have tissue/organ-specific functions. The timing of human and baboon rhythmic transcripts displayed prominent ‘night’ and ‘day’ clusters, with genes in the dark cluster associated with translation. Alignment between baboon rhythmic transcriptomes and the overlapping human blood transcriptome was significantly closer when light onset, rather than midpoint of light, or end of light period, was used as phase reference point. The timing of overlapping human and baboon rhythmic transcriptomes was significantly correlated in 25 tissue/organs with an average earlier timing of 3.21 h (SD 2.47 h) in human blood.

Conclusions

The human blood transcriptome contains sets of rhythmic genes that overlap with rhythmic genes of tissues/organs in baboon. The rhythmic sets vary across tissues/organs, but the timing of most rhythmic genes is similar in human blood and baboon tissues/organs. These results have implications for development of blood transcriptome-based biomarkers for circadian rhythmicity in tissues and organs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01258-7.

Integrated molecular and behavioural data reveal deep circadian disruption in response to artificial light at night in male Great tits (Parus major)

Globally increasing levels of artificial light at night (ALAN) are associated with shifting rhythms of behaviour in many wild species. However, it is unclear whether changes in behavioural timing are paralleled by consistent shifts in the molecular clock and its associated physiological pathways. Inconsistent shifts between behavioural and molecular rhythms, and between different tissues and physiological systems, disrupt the circadian system, which coordinates all major body functions. We therefore compared behavioural, transcriptional and metabolomic responses of captive great tits (Parus major) to three ALAN intensities or to dark nights, recording activity and sampling brain, liver, spleen and blood at mid-day and midnight. ALAN advanced wake-up time, and this shift was paralleled by advanced expression of the clock gene BMAL1 in all tissues, suggesting close links between behaviour and clock gene expression across tissues. However, further analysis of gene expression and metabolites revealed that clock shifts were inconsistent across physiological systems. Untargeted metabolomic profiling showed that only 9.7% of the 755 analysed metabolites followed the behavioural shift. This high level of desynchronization indicates that ALAN disrupted the circadian system on a deep, easily overlooked level. Thus, circadian disruption could be a key mediator of health impacts of ALAN on wild animals.

Circadian Rhythm Effects on the Molecular Regulation of Physiological Systems

Nearly every system within the body contains an intrinsic cellular circadian clock. The circadian clock contributes to the regulation of a variety of homeostatic processes in mammals through the regulation of gene expression. Circadian disruption of physiological systems is associated with pathophysiological disorders. Here, we review the current understanding of the molecular mechanisms contributing to the known circadian rhythms in physiological function. This article focuses on what is known in humans, along with discoveries made with cell and rodent models. In particular, the impact of circadian clock components in metabolic, cardiovascular, endocrine, musculoskeletal, immune, and central nervous systems are discussed. © 2021 American Physiological Society. Compr Physiol 11:1-30, 2021.

A multidisciplinary perspective on the complex interactions between sleep, circadian, and metabolic disruption in cancer patients

Sleep is a basic need that is frequently set aside in modern societies. This leads to profound but complex physiological maladaptations in the body commonly referred to as circadian disruption, which recently has been characterized as a carcinogenic factor and reason for poor treatment outcomes, shortened survival, and reduced quality of life in cancer patients. As sleep and circadian physiology in cancer patients spans several disciplines including nursing science, neurology, oncology, molecular biology and medical technology, there is a lack of comprehensive and integrated approaches to deal with this serious and growing issue and at best a fractionated understanding of only part of the problem among researchers within each of these segments. Here, we take a multidisciplinary approach to comprehensively review the diagnosis and impact of sleep and circadian disruption in cancer patients. We discuss recent discoveries on molecular regulation of the circadian clock in healthy and malignant cells, the neurological and endocrine pathways controlling sleep and circadian rhythmicity, and their inputs to and outputs from the organism. The benefits and drawbacks of the various technologies, devices, and instruments used to assess sleep and circadian function, as well as the known consequences of sleep disruption and how sleep can be corrected in cancer patients, will be analyzed. We will throughout the review highlight the extensive crosstalk between sleep, circadian rhythms, and metabolic pathways involved in malignancy and identify current knowledge gaps and barriers for addressing the issue of sleep and circadian disruption in cancer patients. By addressing these issues, we hope to provide a foundation for further research as well as better and more effective care for the patients in the future.

Understanding Circadian Mechanisms of Sudden Cardiac Death: A Report From the National Heart, Lung, and Blood Institute Workshop, Part 2: Population and Clinical Considerations

Sudden cardiac death (SCD) is the sudden, unexpected death due to abrupt loss of heart function secondary to cardiovascular disease. In certain populations living with cardiovascular disease, SCD follows a distinct 24-hour pattern in occurrence, suggesting day/night rhythms in behavior, the environment, and endogenous circadian rhythms result in daily spans of increased vulnerability. The National Heart, Lung, and Blood Institute convened a workshop, Understanding Circadian Mechanisms of Sudden Cardiac Death to identify fundamental questions regarding the role of the circadian rhythms in SCD. Part 2 summarizes research gaps and opportunities in the areas of population and clinical research identified in the workshop. Established research supports a complex interaction between circadian rhythms and physiological responses that increase the risk for SCD. Moreover, these physiological responses themselves are influenced by several biological variables, including the type of cardiovascular disease, sex, age, and genetics, as well as environmental factors. The emergence of new noninvasive biotechnological tools that continuously measure key cardiovascular variables, as well as the identification of biomarkers to assess circadian rhythms, hold promise for generating large-scale human data sets that will delineate which subsets of individuals are most vulnerable to SCD. Additionally, these data will improve our understanding of how people who suffer from circadian disruptions develop cardiovascular diseases that increase the risk for SCD. Emerging strategies to identify new biomarkers that can quantify circadian health (eg, environmental, behavioral, and internal misalignment) may lead to new interventions and therapeutic targets to prevent the progression of cardiovascular diseases that cause SCD.

Challenges and Opportunities for Applying Wearable Technology to Sleep

Wearable technology has a history in sleep research dating back to the 1970s. Because modern wearable technology is relatively cheap and widely used by the general population, this represents an opportunity to leverage wearable devices to advance sleep medicine and research. However, there is a lack of published validation studies designed to quantify device performance against accepted gold standards, especially across different populations. Recommendations for conducting performance assessments and using wearable devices are now published with the goal of standardizing wearable device implementation and advancing the field.

Understanding the association between sleep, shift work and COVID-19 vaccine immune response efficacy: Protocol of the S-CORE study

This protocol describes an innovative study to investigate the relationship between sleep, shift work and the immune response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2; coronavirus disease 2019 [COVID-19]) vaccination. As the COVID-19 pandemic is a global crisis with devastating health, social and economic impacts, there is a pressing need for effective vaccination programmes. Previous influenza and hepatitis vaccination studies suggest that lack of sleep can negatively alter immune responsiveness, while circadian misalignment most likely may also play an important role in the immune response to vaccination. Our present study will be the first to address this question in actual shift workers and in relation to COVID-19 vaccination. We hypothesise that the occurrence of recent night shifts and diminished sleep will negatively alter the immune response to vaccination in shift workers compared to dayworkers. We aim to recruit 50 shift workers and 50 dayworkers. Participants will receive an mRNA-based vaccination, through the Dutch vaccination programme. To assess immune responsiveness, blood will be drawn at baseline (before first vaccination), 10 days after first vaccination, the day prior to the second vaccination; and 28 days, 6 and 12 months after the second vaccination. Actigraphy and daily sleep e-diaries will be implemented for 7 days around each vaccination to assess sleep. The Pittsburgh Sleep Quality Index will be used to monitor sleep in the long term. Optimising the efficacy of the COVID-19 vaccines is of outmost importance and results of this study could provide insights to develop sleep and circadian-based interventions to enhance vaccination immunity, and thereby improve global health.

The circadian clock and diseases of the skin

Organisms have an evolutionarily conserved internal rhythm that helps them anticipate and adapt to daily changes in the environment. Synchronized to the light-dark cycle with a period of around 24 hours, the timing of the circadian clock is set by light-triggering signals sent from the retina to the suprachiasmatic nucleus. Other inputs, including food intake, exercise, and temperature, also affect clocks in peripheral tissues, including skin. Here, we review the intricate interplay between the core clock network and fundamental physiological processes in skin such as homeostasis, regeneration, and immune- and stress responses. We illustrate the effect of feeding time on the skin circadian clock and skin functions, a previously overlooked area of research. We then discuss works that relate the circadian clock and its disruption to skin diseases, including skin cancer, sunburn, hair loss, aging, infections, inflammatory skin diseases, and wound healing. Finally, we highlight the promise of circadian medicine for skin disease prevention and management.

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.

The endogenous circadian system worsens asthma at night independent of sleep and other daily behavioral or environmental cycles

Asthma often worsens at night. To determine if the endogenous circadian system contributes to the nocturnal worsening of asthma, independent of sleep and other behavioral and environmental day/night cycles, we studied patients with asthma (without steroid use) over 3 wk in an ambulatory setting (with combined circadian, environmental, and behavioral effects) and across the circadian cycle in two complementary laboratory protocols performed in dim light, which separated circadian from environmental and behavioral effects: 1) a 38-h "constant routine," with continuous wakefulness, constant posture, 2-hourly isocaloric snacks, and 2) a 196-h "forced desynchrony" incorporating seven identical recurring 28-h sleep/wake cycles with all behaviors evenly scheduled across the circadian cycle. Indices of pulmonary function varied across the day in the ambulatory setting, and both laboratory protocols revealed significant circadian rhythms, with lowest function during the biological night, around 4:00 AM, uncovering a nocturnal exacerbation of asthma usually unnoticed or hidden by the presence of sleep. We also discovered a circadian rhythm in symptom-based rescue bronchodilator use (β2-adrenergic agonist inhaler) whereby inhaler use was four times more likely during the circadian night than day. There were additive influences on asthma from the circadian system plus sleep and other behavioral or environmental effects. Individuals with the lowest average pulmonary function tended to have the largest daily circadian variations and the largest behavioral cycle effects on asthma. When sleep was modeled to occur at night, the summed circadian, behavioral/environmental cycle effects almost perfectly matched the ambulatory data. Thus, the circadian system contributes to the common nocturnal worsening of asthma, implying that internal biological time should be considered for optimal therapy.

Eight-year longitudinal study of whole blood gene expression profiles in individuals undergoing long-term medical follow-up

Blood circulates throughout the body via the peripheral tissues, contributes to host homeostasis and maintains normal physiological functions, in addition to responding to lesions. Previously, we revealed that gene expression analysis of peripheral blood cells is a useful approach for assessing diseases such as diabetes mellitus and cancer because the altered gene expression profiles of peripheral blood cells can reflect the presence and state of diseases. However, no chronological assessment of whole gene expression profiles has been conducted. In the present study, we collected whole blood RNA from 61 individuals (average age at registration, 50 years) every 4 years for 8 years and analyzed gene expression profiles using a complementary DNA microarray to examine whether these profiles were stable or changed over time. We found that the genes with very stable expression were related mostly to immune system pathways, including antigen cell presentation and interferon-related signaling. Genes whose expression was altered over the 8-year study period were principally involved in cellular machinery pathways, including development, signal transduction, cell cycle, apoptosis, and survival. Thus, this chronological examination study showed that the gene expression profiles of whole blood can reveal unmanifested physiological changes.

Identification of a Preliminary Plasma Metabolome-based Biomarker for Circadian Phase in Humans

Measuring individual circadian phase is important to diagnose and treat circadian rhythm sleep-wake disorders and circadian misalignment, inform chronotherapy, and advance circadian science. Initial findings using blood transcriptomics to predict the circadian phase marker dim-light melatonin onset (DLMO) show promise. Alternatively, there are limited attempts using metabolomics to predict DLMO and no known omics-based biomarkers predict dim-light melatonin offset (DLMOff). We analyzed the human plasma metabolome during adequate and insufficient sleep to predict DLMO and DLMOff using one blood sample. Sixteen (8 male/8 female) healthy participants aged 22.4 ± 4.8 years (mean ± SD) completed an in-laboratory study with 3 baseline days (9 h sleep opportunity/night), followed by a randomized cross-over protocol with 9-h adequate sleep and 5-h insufficient sleep conditions, each lasting 5 days. Blood was collected hourly during the final 24 h of each condition to independently determine DLMO and DLMOff. Blood samples collected every 4 h were analyzed by untargeted metabolomics and were randomly split into training (68%) and test (32%) sets for biomarker analyses. DLMO and DLMOff biomarker models were developed using partial least squares regression in the training set followed by performance assessments using the test set. At baseline, the DLMOff model showed the highest performance (0.91 R2 and 1.1 ± 1.1 h median absolute error ± interquartile range [MdAE ± IQR]), with significantly (p < 0.01) lower prediction error versus the DLMO model. When all conditions (baseline, 9 h, and 5 h) were included in performance analyses, the DLMO (0.60 R2; 2.2 ± 2.8 h MdAE; 44% of the samples with an error under 2 h) and DLMOff (0.62 R2; 1.8 ± 2.6 h MdAE; 51% of the samples with an error under 2 h) models were not statistically different. These findings show promise for metabolomics-based biomarkers of circadian phase and highlight the need to test biomarkers that predict multiple circadian phase markers under different physiological conditions.

MYC Ran Up the Clock: The Complex Interplay between MYC and the Molecular Circadian Clock in Cancer

The MYC oncoprotein and its family members N-MYC and L-MYC are known to drive a wide variety of human cancers. Emerging evidence suggests that MYC has a bi-directional relationship with the molecular clock in cancer. The molecular clock is responsible for circadian (~24 h) rhythms in most eukaryotic cells and organisms, as a mechanism to adapt to light/dark cycles. Disruption of human circadian rhythms, such as through shift work, may serve as a risk factor for cancer, but connections with oncogenic drivers such as MYC were previously not well understood. In this review, we examine recent evidence that MYC in cancer cells can disrupt the molecular clock; and conversely, that molecular clock disruption in cancer can deregulate and elevate MYC. Since MYC and the molecular clock control many of the same processes, we then consider competition between MYC and the molecular clock in several select aspects of tumor biology, including chromatin state, global transcriptional profile, metabolic rewiring, and immune infiltrate in the tumor. Finally, we discuss how the molecular clock can be monitored or diagnosed in human tumors, and how MYC inhibition could potentially restore molecular clock function. Further study of the relationship between the molecular clock and MYC in cancer may reveal previously unsuspected vulnerabilities which could lead to new treatment strategies.

Light-based methods for predicting circadian phase in delayed sleep-wake phase disorder

Methods for predicting circadian phase have been developed for healthy individuals. It is unknown whether these methods generalize to clinical populations, such as delayed sleep-wake phase disorder (DSWPD), where circadian timing is associated with functional outcomes. This study evaluated two methods for predicting dim light melatonin onset (DLMO) in 154 DSWPD patients using ~ 7 days of sleep-wake and light data: a dynamic model and a statistical model. The dynamic model has been validated in healthy individuals under both laboratory and field conditions. The statistical model was developed for this dataset and used a multiple linear regression of light exposure during phase delay/advance portions of the phase response curve, as well as sleep timing and demographic variables. Both models performed comparably well in predicting DLMO. The dynamic model predicted DLMO with root mean square error of 68 min, with predictions accurate to within ± 1 h in 58% of participants and ± 2 h in 95%. The statistical model predicted DLMO with root mean square error of 57 min, with predictions accurate to within ± 1 h in 75% of participants and ± 2 h in 96%. We conclude that circadian phase prediction from light data is a viable technique for improving screening, diagnosis, and treatment of DSWPD.

Importance of circadian timing for aging and longevity

Dietary restriction (DR) decreases body weight, improves health, and extends lifespan. DR can be achieved by controlling how much and/or when food is provided, as well as by adjusting nutritional composition. Because these factors are often combined during DR, it is unclear which are necessary for beneficial effects. Several drugs have been utilized that target nutrient-sensing gene pathways, many of which change expression throughout the day, suggesting that the timing of drug administration is critical. Here, we discuss how dietary and pharmacological interventions promote a healthy lifespan by influencing energy intake and circadian rhythms.

Circadian clocks link physiologic processes to environmental conditions and a mismatch between internal and external rhythms has negative effects on organismal health. In this review, the authors discuss the interactions between circadian clocks and dietary interventions targeted to promote healthy aging.

Workshop report. Circadian rhythm sleep-wake disorders: gaps and opportunities

This White Paper presents the results from a workshop cosponsored by the Sleep Research Society (SRS) and the Society for Research on Biological Rhythms (SRBR) whose goals were to bring together sleep clinicians and sleep and circadian rhythm researchers to identify existing gaps in diagnosis and treatment and areas of high-priority research in circadian rhythm sleep-wake disorders (CRSWD). CRSWD are a distinct class of sleep disorders caused by alterations of the circadian time-keeping system, its entrainment mechanisms, or a misalignment of the endogenous circadian rhythm and the external environment. In these disorders, the timing of the primary sleep episode is either earlier or later than desired, irregular from day-to-day, and/or sleep occurs at the wrong circadian time. While there are incomplete and insufficient prevalence data, CRSWD likely affect at least 800,000 and perhaps as many as 3 million individuals in the United States, and if Shift Work Disorder and Jet Lag are included, then many millions more are impacted. The SRS Advocacy Taskforce has identified CRSWD as a class of sleep disorders for which additional high-quality research could have a significant impact to improve patient care. Participants were selected for their expertise and were assigned to one of three working groups: Phase Disorders, Entrainment Disorders, and Other. Each working group presented a summary of the current state of the science for their specific CRSWD area, followed by discussion from all participants. The outcome of those presentations and discussions are presented here.

Chronotype-specific Sleep in Two Versus Four Consecutive Shifts

The study aimed to explore chronotype-specific effects of two versus four consecutive morning or night shifts on sleep-wake behavior. Sleep debt and social jetlag (a behavioral proxy of circadian misalignment) were estimated from sleep diary data collected for 5 weeks in a within-subject field study of 30 rotating night shift workers (29.9 ± 7.3 years, 60% female). Mixed models were used to examine whether effects of shift sequence length on sleep are dependent on chronotype, testing the interaction between sequence length (two vs. four) and chronotype (determined from sleep diaries). Analyses of two versus four morning shifts showed no significant interaction effects with chronotype. In contrast, increasing the number of night shifts from two to four increased sleep debt in early chronotypes, but decreased sleep debt in late types, with no change in intermediate ones. In early types, the higher sleep debt was due to accumulated sleep loss over four night shifts. In late types, sleep duration did not increase over the course of four night shifts, so that adaptation is unlikely to explain the observed lower sleep debt. Late types instead had increased sleep debt after two night shifts, which was carried over from two preceding morning shifts in this schedule. Including naps did not change the findings. Social jetlag was unaffected by the number of consecutive night shifts. Our results suggest that consecutive night shifts should be limited in early types. For other chronotypes, working four night shifts might be a beneficial alternative to working two morning and two night shifts. Studies should record shift sequences in rotating schedules.

Circadian Effects of Drug Responses

Circadian rhythms describe physiological systems that repeat themselves with a cycle of approximately 24 h. Our understanding of the cellular and molecular origins of these oscillations has improved dramatically, allowing us to appreciate the significant role these oscillations play in maintaining physiological homeostasis. Circadian rhythms allow living organisms to predict and efficiently respond to a dynamically changing environment, set by repetitive day/night cycles. Since circadian rhythms underlie almost every aspect of human physiology, it is unsurprising that they also influence the response of a living organism to disease, stress, and therapeutics. Therefore, not only do the mechanisms that maintain health and disrupt homeostasis depend on our internal circadian clock, but also the way drugs are perceived and function depends on these physiological rhythms. We present a holistic view of the therapeutic process, discussing components such as disease state, pharmacokinetics, and pharmacodynamics, as well as adverse reactions that are critically affected by circadian rhythms. We outline challenges and opportunities in moving toward personalized medicine approaches that explore and capitalize on circadian rhythms for the benefit of the patient.

Asking the Clock: How to Use Information from Questionnaires for Circadian Phenotyping

With the emergence of big data science, the question how we can easily collect meaningful information about circadian clock phenotypes in large human cohorts imposes itself. Here, we describe potentials and limitations of using questionnaires, specifically the Munich ChronoType Questionnaire (MCTQ), to characterize such circadian phenotypes. We also discuss scenarios when alternative methods might be more appropriate.

Minimally Invasive Ways of Determining Circadian Rhythms in Humans

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

Prolonged, Controlled Daytime versus Delayed Eating Impacts Weight and Metabolism

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

An Optimal Time for Treatment-Predicting Circadian Time by Machine Learning and Mathematical Modelling

Tailoring medical interventions to a particular patient and pathology has been termed personalized medicine. The outcome of cancer treatments is improved when the intervention is timed in accordance with the patient's internal time. Yet, one challenge of personalized medicine is how to consider the biological time of the patient. Prerequisite for this so-called chronotherapy is an accurate characterization of the internal circadian time of the patient. As an alternative to time-consuming measurements in a sleep-laboratory, recent studies in chronobiology predict circadian time by applying machine learning approaches and mathematical modelling to easier accessible observables such as gene expression. Embedding these results into the mathematical dynamics between clock and cancer in mammals, we review the precision of predictions and the potential usage with respect to cancer treatment and discuss whether the patient's internal time and circadian observables, may provide an additional indication for individualized treatment timing. Besides the health improvement, timing treatment may imply financial advantages, by ameliorating side effects of treatments, thus reducing costs. Summarizing the advances of recent years, this review brings together the current clinical standard for measuring biological time, the general assessment of circadian rhythmicity, the usage of rhythmic variables to predict biological time and models of circadian rhythmicity.

Therapeutics on the clock: Circadian medicine in the treatment of chronic inflammatory diseases

The circadian clock is a collection of endogenous oscillators with a periodicity of ~ 24 h. Recently, our understanding of circadian rhythms and their regulation at genomic and physiologic scales has grown significantly. Knowledge of the circadian influence on biological processes has provided new possibilities for novel pharmacological strategies. Directly targeting the biological clock or its downstream targets, and/or using timing as a variable in drug therapy are now important pharmacological considerations. The circadian machinery mediates many aspects of the inflammatory response and, reciprocally, an inflammatory environment can disrupt circadian rhythms. Therefore, intense interest exists in leveraging circadian biology as a means to treat chronic inflammatory diseases such as sepsis, asthma, rheumatoid arthritis, osteoarthritis, and cardiovascular disease, which all display some type of circadian signature. The purpose of this review is to evaluate the crosstalk between circadian rhythms, inflammatory diseases, and their pharmacological treatment. Evidence suggests that carefully rationalized application of chronotherapy strategies - alone or in combination with small molecule modulators of circadian clock components - can improve efficacy and reduce toxicity, thus warranting further investigation and use.

How to tell time: advances in decoding circadian phase from omics snapshots

The ability of organisms to keep track of external time, by means of the circadian clock interacting with the environment, is essential for health. The focus of this review is recent methods to detect the internal circadian time of an omics sample. Before reaching our main topic, we introduce the circadian clock, its hierarchical structure, and its main functions; we will also explain the notion of internal time, or circadian phase, and how it differs from the geophysical time. We then focus on the role played by the clock in the maintenance of human heath, in particular in the context of cancer. Thereafter, we analyze an important methodological question: how to infer the circadian phase of unlabeled omics snapshot measurements. Answering this question could both significantly increase our understanding of the circadian clock and allow the use of this knowledge in biomedical applications. We review existing methods, focusing on the more recent ones, following a historical trajectory. We explain the basic concepts underlying the methods, as well as some crucial technical aspects of each. We conclude by reporting how some of these methods have, more or less effectively, enabled furthering our understanding of the clock and given insights regarding potential biomedical applications.

Chronotype distribution in the Chinese population

Purpose:

Individual chronotypes are reported to be closely associated with mood, health status, and even disease progression. However, no reports of chronotype distribution in the Chinese population have been made available to date.

Methods:

We performed a chronotype survey using the classic Morningness–Eveningness Questionnaire both online and offline. The webpage-based online survey was distributed via a social network application on mobile phones. The offline survey was distributed to local primary and middle schools. A total of 9476 questionnaires were collected, of which 8395 were valid. The mean age of the participants was 30.38 ± 11.47 years, and 37.38% were male.

Results:

Overall, the Chinese chronotypes showed a near-normal distribution with a slight shift toward eveningness. When analyzed in different age groups, the overall Chinese population was shown to be “latest” in their early twenties. In the young population, two significant points of change in chronotype were identified at the ages of 10 and 16 years. The chronotype composition remained relatively stable during early adulthood (from 17 to 28 years of age).

Conclusion:

This study generated the first overview of chronotype distribution in the Chinese population and will serve as essential background data for future studies.

A population-based gene expression signature of molecular clock phase from a single epidermal sample

BACKGROUND

For circadian medicine to influence health, such as when to take a drug or undergo a procedure, a biomarker of molecular clock phase is required--one that is easily measured and generalizable across a broad population. It is not clear that any circadian biomarker yet satisfies these criteria.

METHODS

We analyzed 24-h molecular rhythms in human dermis and epidermis at three distinct body sites, leveraging both longitudinal (n = 20) and population (n = 154) data. We applied cyclic ordering by periodic structure (CYCLOPS) to order the population samples where biopsy time was not recorded. With CYCLOPS-predicted phases, we used ZeitZeiger to discover potential biomarkers of clock phase.

RESULTS

Circadian clock function was strongest in the epidermis, regardless of body site. We identified a 12-gene expression signature that reported molecular clock phase to within 3 h (mean error = 2.5 h) from a single sample of epidermis--the skin's most superficial layer. This set performed well across body sites, ages, sexes, and detection platforms.

CONCLUSIONS

This research shows that the clock in epidermis is more robust than dermis regardless of body site. To encourage ongoing validation of this putative biomarker in diverse populations, diseases, and experimental designs, we developed SkinPhaser--a user-friendly app to test biomarker performance in datasets ( https://github.com/gangwug/SkinPhaser ).