Recent advances in sleep genetics

Regulation of Sleep Amount by CRTC1 via Transcription of Crh in Mice

The cAMP response element binding protein (CREB) is required for regulation of daily sleep amount, whereas gain of function of CREB-regulated transcription coactivator 1 (CRTC1) causes severe insomnia in mice. However, the physiological functions of CRTCs and their downstream target genes in the regulation of sleep amount remain unclear. Here, we use an adult brain chimeric (ABC)-expression/knock-out platform for somatic genetic analysis of sleep in adult male mice. ABC expression of constitutively active mutant CRTC1/2CA in the mouse brain neurons significantly reduces the amount of non-rapid eye movement sleep (NREMS) and/or rapid eye movement sleep (REMS). Consistent with the fact that SIK3 phosphorylates and inhibits CRTCs, ABC expression of CRTC1/2/3CA rescues the hypersomnia phenotype of Sleepy (Sik3Slp ) mice. While ABC-Crtc2KO or Crtc3KO causes no sleep phenotype, ABC-Crtc1KO or ABC expression of dominant-negative CRTC (dnCRTC) results in a modest reduction of NREMS amount accompanied with elevated NREMS delta power. Moreover, ABC expression of CRTC1CA or dnCRTC in the excitatory neurons causes bidirectional changes of NREMS/REMS amount and/or NREMS delta power. The ability of CRTC1CA to regulate sleep requires its transactivation domain and CREB-binding domain and is dependent on CREB. Furthermore, we showed that inducible ABC expression of corticotropin-releasing hormone (Crh) and brain-derived neurotrophic factor (Bdnf)-two target genes of CRTCs-significantly reduces daily sleep amount. Notably, ABC-CrhKO , but not BdnfKO , rescues the insomnia phenotype of ABC-CRTC1CA mice. Taken together, these results indicate that the CREB-CRTC1 complex regulates daily sleep amount by modulating the transcription of Crh in the mouse brain neurons.

Voltage Gated Ion Channels and Sleep

Ion channels are integral components of the nervous system, playing a pivotal role in shaping membrane potential, neuronal excitability, synaptic transmission and plasticity. Dysfunction in these channels, such as improper expression or localization, can lead to irregular neuronal excitability and synaptic communication, which may manifest as various behavioral abnormalities, including disrupted rest-activity cycles. Research has highlighted the significant impact of voltage gated ion channels on sleep parameters, influencing sleep latency, duration and waveforms. Furthermore, these ion channels have been implicated in the vulnerability to, and the pathogenesis of, several neurological and psychiatric disorders, including epilepsy, autism, schizophrenia, and Alzheimer's disease (AD). In this comprehensive review, we aim to provide a summary of the regulatory role of three predominant types of voltage-gated ion channels-calcium (Ca2+), sodium (Na+), and potassium (K+)-in sleep across species, from flies to mammals. We will also discuss the association of sleep disorders with various human diseases that may arise from the dysfunction of these ion channels, thereby underscoring the potential therapeutic benefits of targeting specific ion channel subtypes for sleep disturbance treatment.

A Survey on AI-Driven Mouse Behavior Analysis Applications and Solutions

The physiological similarities between mice and humans make them vital animal models in biological and medical research. This paper explores the application of artificial intelligence (AI) in analyzing mice behavior, emphasizing AI's potential to identify and classify these behaviors. Traditional methods struggle to capture subtle behavioral features, whereas AI can automatically extract quantitative features from large datasets. Consequently, this study aims to leverage AI to enhance the efficiency and accuracy of mice behavior analysis. The paper reviews various applications of mice behavior analysis, categorizes deep learning tasks based on an AI pyramid, and summarizes AI methods for addressing these tasks. The findings indicate that AI technologies are increasingly applied in mice behavior analysis, including disease detection, assessment of external stimuli effects, social behavior analysis, and neurobehavioral assessment. The selection of AI methods is crucial and must align with specific applications. Despite AI's promising potential in mice behavior analysis, challenges such as insufficient datasets and benchmarks remain. Furthermore, there is a need for a more integrated AI platform, along with standardized datasets and benchmarks, to support these analyses and further advance AI-driven mice behavior analysis.

Emerging trends and hot spots of sleep and genetic research: a bibliometric analysis of publications from 2002 to 2022 in the field

Background

Sleep is an important biological process and has been linked to many diseases; however, very little is known about which and how genes control and regulate sleep. Although technology has seen significant development, this issue has still not been adequately resolved. Therefore, we conducted a bibliometric analysis to assess the progress in research on sleep quality and associated genes over the past 2 decades. Through our statistical data and discussions, we aimed to provide researchers with better research directions and ideas, thus promoting the advancement of this field.

Methods

On December 29, 2022, we utilized bibliometric techniques, such as co-cited and cluster analysis and keyword co-occurrence, using tools such as CiteSpace, VOSviewer, and the Online Analysis Platform of Literature Metrology (http://bibliometric.com/), to conduct a thorough examination of the relevant publications extracted from the Web of Science Core Collection (WoSCC). Our analysis aimed to identify the emerging trends and hot spots in this field while also predicting their potential development in future.

Results

Cluster analysis of the co-cited literature revealed the most popular terms relating to sleep quality and associated genes in the manner of cluster labels; these included genome-wide association studies (GWAS), circadian rhythms, obstructive sleep apnea (OSA), DNA methylation, and depression. Keyword burst detection suggested that obstructive sleep apnea, circadian clock, circadian genes, and polygenic risk score were newly emergent research hot spots.

Conclusion

Based on this bibliometric analysis of the publications in the last 20 years, a comprehensive analysis of the literature clarified the contributions, changes in research hot spots, and evolution of research techniques regarding sleep quality and associated genes. This research can provide medical staff and researchers with revelations into future directions of the study on the pathological mechanisms of sleep-related diseases.

Doctors' alertness, contentedness and calmness before and after night shifts: a latent profile analysis

BACKGROUND

While night shifts are crucial for patient care, they threaten doctors' well-being and performance. Knowledge of how the impact of night shifts differs for doctors is needed to attenuate the adverse effects of night shifts. This study aimed to obtain more precise insight into doctors' feelings surrounding night shift by: identifying profiles based on doctors' alertness, contentedness and calmness scores before and after night shifts (research question (RQ) 1); assessing how doctors' pre- and post-shift profiles change (RQ2); and determining associations of doctors' demographics and shift circumstances with alertness, contentedness and calmness change (RQ3).

METHODS

Latent Profile Analysis using doctors' pre- and post-shift self-rated alertness, contentedness and calmness scores was employed to identify pre- and post-shift profiles (RQ1). A cross-tabulation revealed pre- and post-shift profile changes (RQ2). Multiple regressions determined associations of demographics (i.e. age, sex, specialty) and night shift circumstances (i.e. hours worked pre-call, hours awake pre-call, shift duration, number of consecutive shifts, total hours of sleep) with alertness, contentedness and calmness change (RQ3).

RESULTS

In total, 211 doctors participated with a mean age of 39.8 ± 10 years; 47.4% was male. The participants included consultants (46.4%) and trainees (53.6%) of the specialties surgery (64.5%) and obstetrics/gynaecology (35.5%). Three pre-shift (Indifferent, Ready, Engaged) and four post-shift profiles (Lethargic, Tired but satisfied, Excited, Mindful) were found. Most doctors changed from Ready to Tired but satisfied, with alertness reducing most. Age, specialty, sleep, shift duration and the number of consecutive shifts associated with alertness, contentedness and calmness changes.

CONCLUSIONS

The results provided nuanced insight into doctors' feelings before and after night shifts. Future research may assess whether specific subgroups benefit from tailored interventions.

A signalling pathway for transcriptional regulation of sleep amount in mice

In mice and humans, sleep quantity is governed by genetic factors and exhibits age-dependent variation1-3. However, the core molecular pathways and effector mechanisms that regulate sleep duration in mammals remain unclear. Here, we characterize a major signalling pathway for the transcriptional regulation of sleep in mice using adeno-associated virus-mediated somatic genetics analysis4. Chimeric knockout of LKB1 kinase-an activator of AMPK-related protein kinase SIK35-7-in adult mouse brain markedly reduces the amount and delta power-a measure of sleep depth-of non-rapid eye movement sleep (NREMS). Downstream of the LKB1-SIK3 pathway, gain or loss-of-function of the histone deacetylases HDAC4 and HDAC5 in adult brain neurons causes bidirectional changes of NREMS amount and delta power. Moreover, phosphorylation of HDAC4 and HDAC5 is associated with increased sleep need, and HDAC4 specifically regulates NREMS amount in posterior hypothalamus. Genetic and transcriptomic studies reveal that HDAC4 cooperates with CREB in both transcriptional and sleep regulation. These findings introduce the concept of signalling pathways targeting transcription modulators to regulate daily sleep amount and demonstrate the power of somatic genetics in mouse sleep research.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

LRRK2 Deficiency Aggravates Sleep Deprivation-Induced Cognitive Loss by Perturbing Synaptic Pruning in Mice

Mutations of the leucine-rich repeat kinase 2 (LRRK2) gene are associated with pronounced sleep disorders or cognitive dysfunction in neurodegenerative diseases. However, the effects of LRRK2 deficiency on sleep rhythms and sleep deprivation-related cognitive changes, and the relevant underlying mechanism, remain unrevealed. In this study, Lrrk2-/- and Lrrk2+/+ mice were subjected to normal sleep (S) or sleep deprivation (SD). Sleep recording, behavioral testing, Golgi-cox staining, immunofluorescence, and real-time PCR were employed to evaluate the impacts of LRRK2 deficiency on sleep behaviors and to investigate the underlying mechanisms. The results showed that after SD, LRRK2-deficient mice displayed lengthened NREM and shortened REM, and reported decreased dendritic spines, increased microglial activation, and synaptic endocytosis in the prefrontal cortex. Meanwhile, after SD, LRRK2 deficiency aggravated cognitive impairments, especially in the recall memory cued by fear conditioning test. Our findings evidence that LRRK2 modulates REM/NREM sleep and its deficiency may exacerbate sleep deprivation-related cognitive disorders by perturbing synaptic plasticity and microglial synaptic pruning in mice.

Adaptive Solutions to the Problem of Vulnerability During Sleep

Sleep is a behavioral state whose quantity and quality represent a trade-off between the costs and benefits this state provides versus the costs and benefits of wakefulness. Like many species, we humans are particularly vulnerable during sleep because of our reduced ability to monitor the external environment for nighttime predators and other environmental dangers. A number of variations in sleep characteristics may have evolved over the course of human history to reduce this vulnerability, at both the individual and group level. The goals of this interdisciplinary review paper are (1) to explore a number of biological/instinctual features of sleep that may have adaptive utility in terms of enhancing the detection of external threats, and (2) to consider relatively recent cultural developments that improve vigilance and reduce vulnerability during sleep and the nighttime. This paper will also discuss possible benefits of the proposed adaptations beyond vigilance, as well as the potential costs associated with each of these proposed adaptations. Finally, testable hypotheses will be presented to evaluate the validity of these proposed adaptations.

Motivational and Valence-Related Modulation of Sleep/Wake Behavior are Mediated by Midbrain Dopamine and Uncoupled from the Homeostatic and Circadian Processes

Motivation and its hedonic valence are powerful modulators of sleep/wake behavior, yet its underlying mechanism is still poorly understood. Given the well-established role of midbrain dopamine (mDA) neurons in encoding motivation and emotional valence, here, neuronal mechanisms mediating sleep/wake regulation are systematically investigated by DA neurotransmission. It is discovered that mDA mediates the strong modulation of sleep/wake states by motivational valence. Surprisingly, this modulation can be uncoupled from the classically employed measures of circadian and homeostatic processes of sleep regulation. These results establish the experimental foundation for an additional new factor of sleep regulation. Furthermore, an electroencephalographic marker during wakefulness at the theta range is identified that can be used to reliably track valence-related modulation of sleep. Taken together, this study identifies mDA signaling as an important neural substrate mediating sleep modulation by motivational valence.

Somatic Genetics Analysis of Sleep in Adult Mice

Classical forward and reverse mouse genetics require germline mutations and, thus, are unwieldy to study sleep functions of essential genes or redundant pathways. It is also time-consuming to conduct EEG/EMG-based mouse sleep screening because of labor-intensive surgeries and genetic crosses. Here, we describe a highly accurate SleepV (video) system and adeno-associated virus (AAV)-based adult brain chimeric (ABC)-expression/KO platform for somatic genetics analysis of sleep in adult male or female mice. A pilot ABC screen identifies CREB and CRTC1, of which constitutive or inducible expression significantly reduces quantity and/or quality of non-rapid eye movement sleep. Whereas ABC-KO of exon 13 of Sik3 by AAV-Cre injection in Sik3-E13flox/flox adult mice phenocopies Sleepy (Sik3 Slp/+ ) mice, ABC-CRISPR of Slp/Sik3 reverses hypersomnia of Sleepy mice, indicating a direct role of SLP/SIK3 kinase in sleep regulation. Multiplex ABC-CRISPR of both orexin/hypocretin receptors causes narcolepsy episodes, enabling one-step analysis of redundant genes in adult mice. Therefore, this somatic genetics approach should facilitate high-throughput analysis of sleep regulatory genes, especially for essential or redundant genes, in adult mice by skipping mouse development and minimizing genetic crosses.SIGNIFICANCE STATEMENT The molecular mechanisms of mammalian sleep regulation remain unclear. Classical germline mouse genetics are unwieldy to study sleep functions of essential genes or redundant pathways. The EEG/EMG-based mouse sleep screening is time-consuming because of labor-intensive surgeries and lengthy genetic crosses. To overcome these "bottlenecks," we developed a highly accurate video-based sleep analysis system and adeno-associated virus-mediated ABC-expression/KO platform for somatic genetics analysis of sleep in adult mice. These methodologies facilitate rapid identification of sleep regulatory genes, but also efficient mechanistic studies of the molecular pathways of sleep regulation in mice.

High-throughput visual assessment of sleep stages in mice using machine learning

STUDY OBJECTIVES

Sleep is an important biological process that is perturbed in numerous diseases, and assessment its substages currently requires implantation of electrodes to carry out electroencephalogram/electromyogram (EEG/EMG) analysis. Although accurate, this method comes at a high cost of invasive surgery and experts trained to score EEG/EMG data. Here, we leverage modern computer vision methods to directly classify sleep substages from video data. This bypasses the need for surgery and expert scoring, provides a path to high-throughput studies of sleep in mice.

METHODS

We collected synchronized high-resolution video and EEG/EMG data in 16 male C57BL/6J mice. We extracted features from the video that are time and frequency-based and used the human expert-scored EEG/EMG data to train a visual classifier. We investigated several classifiers and data augmentation methods.

RESULTS

Our visual sleep classifier proved to be highly accurate in classifying wake, non-rapid eye movement sleep (NREM), and rapid eye movement sleep (REM) states, and achieves an overall accuracy of 0.92 +/- 0.05 (mean +/- SD). We discover and genetically validate video features that correlate with breathing rates, and show low and high variability in NREM and REM sleep, respectively. Finally, we apply our methods to non-invasively detect that sleep stage disturbances induced by amphetamine administration.

CONCLUSIONS

We conclude that machine learning based visual classification of sleep is a viable alternative to EEG/EMG based scoring. Our results will enable non-invasive high-throughput sleep studies and will greatly reduce the barrier to screening mutant mice for abnormalities in sleep.

Genetic Markers of Differential Vulnerability to Sleep Loss in Adults

In this review, we discuss reports of genotype-dependent interindividual differences in phenotypic neurobehavioral responses to total sleep deprivation or sleep restriction. We highlight the importance of using the candidate gene approach to further elucidate differential resilience and vulnerability to sleep deprivation in humans, although we acknowledge that other omics techniques and genome-wide association studies can also offer insights into biomarkers of such vulnerability. Specifically, we discuss polymorphisms in adenosinergic genes (ADA and ADORA2A), core circadian clock genes (BHLHE41/DEC2 and PER3), genes related to cognitive development and functioning (BDNF and COMT), dopaminergic genes (DRD2 and DAT), and immune and clearance genes (AQP4, DQB1*0602, and TNFα) as potential genetic indicators of differential vulnerability to deficits induced by sleep loss. Additionally, we review the efficacy of several countermeasures for the neurobehavioral impairments induced by sleep loss, including banking sleep, recovery sleep, caffeine, and naps. The discovery of reliable, novel genetic markers of differential vulnerability to sleep loss has critical implications for future research involving predictors, countermeasures, and treatments in the field of sleep and circadian science.