Neurobiology of Sleep and Circadian Rhythms最新文献

Sleep disturbances are common in neurodevelopmental disorders, but knowledge of molecular factors that govern sleep in young animals is lacking. Evidence across species, including Drosophila, suggests that juvenile sleep has distinct functions and regulatory mechanisms in comparison to sleep in maturity. In flies, manipulation of most known adult sleep regulatory genes is not associated with sleep phenotypes during early developmental (larval) stages. Here, we examine the role of the neurodevelopmental disorder-associated gene Neurofibromin 1 (Nf1) in sleep during numerous developmental periods. Mutations in Neurofibromin 1 (Nf1) are associated with sleep and circadian disorders in humans and adult flies. We find in flies that Nf1 acts to regulate sleep across the lifespan, beginning during larval stages. Nf1 is required in neurons for this function, as is signaling via the Alk pathway. These findings identify Nf1 as one of a small number of genes positioned to regulate sleep across developmental periods.

The Unified Theory suggests that sleep is a process that developed in eukaryotic animals from a relationship with an endosymbiotic bacterium. Over evolutionary time the bacterium evolved into the modern mitochondrion that continues to exert an effect on sleep patterns, e.g. the bacterium Wolbachia establishes an endosymbiotic relationship with Drosophila and many other species of insects and is able to change the host's behaviour by making it sleep. The hypothesis is supported by other host-parasite relationships, e.g., Trypanosoma brucei which causes day-time sleepiness and night-time insomnia in humans and cattle. For eukaryotes such as Monocercomonoids that don't contain mitochondria we find no evidence of them sleeping.

Mitochondria produce the neurotransmitter gamma aminobutyric acid (GABA), and ornithine a precursor of the neurotransmitter GABA, together with substances such as 3,4dihydroxy phenylalanine (DOPA) a precursor for the neurotransmitter dopamine: These substances have been shown to affect the sleep/wake cycles in animals such as Drosophilia and Hydra.

Eukaryote animals have traded the very positive side of having mitochondria providing aerobic respiration for them with the negative side of having to sleep. NREM (Quiet sleep) is the process endosymbionts have imposed upon their host eukaryotes and REM (Active sleep) is the push-back adaptation of eukaryotes with brains, returning to wakefulness.

The sleep EEG mirrors neuronal connectivity, especially during development when the brain undergoes substantial rewiring. As children grow, the slow-wave activity (SWA; 0.75–4.25 Hz) spatial distribution in their sleep EEG changes along a posterior-to-anterior gradient. Topographical SWA markers have been linked to critical neurobehavioral functions, such as motor skills, in school-aged children. However, the relationship between topographical markers in infancy and later behavioral outcomes is still unclear. This study aims to explore reliable indicators of neurodevelopment in infants by analyzing their sleep EEG patterns. Thirty-one 6-month-old infants (15 female) underwent high-density EEG recordings during nighttime sleep. We defined markers based on the topographical distribution of SWA and theta activity, including central/occipital and frontal/occipital ratios and an index derived from local EEG power variability. Linear models were applied to test whether markers relate to concurrent, later, or retrospective behavioral scores, assessed by the parent-reported Ages & Stages Questionnaire at ages 3, 6, 12, and 24 months. Results indicate that the topographical markers of the sleep EEG power in infants were not significantly linked to behavioral development at any age. Further research, such as longitudinal sleep EEG in newborns, is needed to better understand the relationship between these markers and behavioral development and assess their predictive value for individual differences.

The autonomic nervous system (ANS) and the central nervous system (CNS) interplay during sleep, particularly during phasic events such as micro-arousals, has been the subject of several studies. The underlying mechanisms of such relationship which remain unclear, specifically during daytime sleep, were partly investigated in this study. Napping polysomnography was performed on two occasions at least one week apart in 15 healthy subjects. The following cardiorespiratory variables were extracted from the recordings: tachogram, pulse transit time (PTT), pulse wave amplitude, respiratory cycle amplitude, and frequency. Two experts first detected micro-arousal events, then, cardiorespiratory variables were averaged by 30-s epochs over 2 min centered on the onset of the micro-arousals. We found that in the 30 s preceding the arousal events as detected on the electroencephalogram (EEG) recordings, there was a decrease in tachogram, pulse wave amplitude, and PTT values while the respiratory amplitude increased. These changes were more prominent in stage N2 and N3 sleep than in stage N1. The present findings provide new insights into the autonomic changes during the pre-arousal period in daytime naps, as all the variables investigated suggest a sympathetic physiological origin for the changes.

In mammals, photic information delivered to the suprachiasmatic nucleus (SCN) via the retinohypothalamic tract (RHT) plays a crucial role in synchronizing the master circadian clock located in the SCN to the solar cycle. It is well known that glutamate released from the RHT terminals initiates the synchronizing process by activating ionotropic glutamate receptors (iGluRs) on retinorecipient SCN neurons. The potential role of metabotropic glutamate receptors (mGluRs) in modulating this signaling pathway has received less attention. In this study, using extracellular single-unit recordings in mouse SCN slices, we investigated the possible roles of the G_q/11 protein-coupled mGluRs, mGluR1 and mGluR5, in photic resetting. We found that mGluR1 activation in the early night produced phase advances in neural activity rhythms in the SCN, while activation in the late night produced phase delays. In contrast, mGluR5 activation had no significant effect on the phase of these rhythms. Interestingly, mGluR1 activation antagonized phase shifts induced by glutamate through a mechanism that was dependent upon Ca_V1.3 L-type voltage-gated Ca²⁺ channels (VGCCs). While both mGluR1-evoked phase delays and advances were inhibited by knockout (KO) of Ca_V1.3 L-type VGCCs, different signaling pathways appeared to be involved in mediating these effects, with mGluR1 working via protein kinase G in the early night and via protein kinase A signaling in the late night. We conclude that, in the mouse SCN, mGluR1s function to negatively modulate glutamate-evoked phase shifts.

Sleep deprivation (SD) results in profound cellular and molecular changes in the adult mammalian brain. Some of these changes may result in, or aggravate, brain disease. However, little is known about how SD impacts gene expression in developing animals. We examined the transcriptional response in the prefrontal cortex (PFC) to SD across postnatal development in male mice. We used RNA sequencing to identify functional gene categories that were specifically impacted by SD. We find that SD has dramatically different effects on PFC genes depending on developmental age. Gene expression differences after SD fall into 3 categories: present at all ages (conserved), present when mature sleep homeostasis is first emerging, and those unique to certain ages. Developmentally conserved gene expression was limited to a few functional categories, including Wnt-signaling which suggests that this pathway is a core mechanism regulated by sleep. In younger ages, genes primarily related to growth and development are affected while changes in genes related to metabolism are specific to the effect of SD in adults.

Sleep is an essential component of development. Developmental sleep disruption (DSD) impacts brain maturation and has been associated with significant consequences on socio-emotional development. In humans, poor sleep during infancy and adolescence affects neurodevelopmental outcomes and may be a risk factor for the development of autism spectrum disorder (ASD) or other neuropsychiatric illness. Given the wide-reaching and enduring consequences of DSD, identifying underlying mechanisms is critical to best inform interventions with translational capacity. In rodents, studies have identified some mechanisms and neural circuits by which DSD causes later social, emotional, sensorimotor, and cognitive changes. However, these studies spanned methodological differences, including different developmental timepoints for both sleep disruption and testing, different DSD paradigms, and even different rodent species. In this scoping review on DSD in rodents, we synthesize these various studies into a cohesive framework to identify common neural mechanisms underlying DSD-induced dysfunction in brain and behavior. Ultimately, this review serves the goal to inform the generation of novel translational interventions for human developmental disorders featuring sleep disruption.

Mild traumatic brain injury (mTBI) or concussion is a common injury worldwide leading to substantial medical costs and a high burden on society. In adolescents, falls and sports related trauma are often the causes of mTBI. Importantly, critical brain growth and development occurs during this sensitive period making the prospect of a brain injury a worrying phenomenon. Upwards of 70% of patients report circadian disruption following these injuries and this has been shown to impede recovery. Therefore, we sought to determine if core circadian clock gene expression was disrupted in rat model of repetitive mTBI (RmTBI). Male and female adolescent rats (n = 129) received sham or RmTBI. The animals were then euthanized at different times throughout the day and night. Tissue from the hypothalamus, cerebellum, hippocampus, liver, and small intestine were evaluated for the expression of per1, per2, cry1, clock, bmal1 and rev-erb-α. We found most clock genes varied across the day/night indicating circadian expression patterns. In the hypothalamus we found RmTBI altered the expression of cry1 and bmal1 in addition to sex differences in per2, cry1, clock, bmal1 and rev-erb- α. In the cerebellum, per1, per2, cry1, clock, bmal1 and rev-erb-α rhythms were all knocked out by RmTBI in addition to sex differences in cry1, clock and bmal1 expression. We also detected a significant decrease in overall expression of all clock genes in males in the middle of the night. In the hippocampus we found that RmTBI changed the rhythm of rev-erb-α expression in addition to sex differences in bmal1 expression. In the liver we detected strong rhythms in all genes examined, however only per2 expression was knocked out by RmTBI, in addition we also detected sex differences in per2 and cry1. We also detected an overall decrease in female clock gene expression in the early night. In the small intestine, RmTBI altered cry1 expression and there were sex differences in rev-erb-α. These results indicate that RmTBI alters core circadian clock gene expression in the central and peripheral nervous system in a time, tissue and sex dependent manner. This may be disrupting important phase relationships between the brain and peripheral nervous system and contributing to post-injury symptomology and also highlights the importance for time and sex dependent assessment of injury outcomes.

Circadian rhythm impairment may play a role in Parkinson's disease (PD) pathophysiology. Recent literature associated circadian rhythm features to the risk of developing Parkinson and to its progression through stages. The association between the chronotype and the phenotype should be verified on a clinical and biological point of view. Herein we investigate the chronotype of a sample of 50 PD patients with the Morningness Eveningness Questionnaire and monitor their daily activity with a motion sensor embedded in a smartphone. Fibroblasts were collected from PD patients (n = 5) and from sex/age matched controls (n = 3) and tested for the circadian expression of clock genes (CLOCK, BMAL1, PER1, CRY1), and for cell morphology, proliferation, and death. Our results show an association between the chronotype and the PD phenotype. The most representative clinical chronotypes were “moderate morning” (56%), the “intermediate” (24%) and, in a minor part, the “definite morning” (16%). They differed for axial motor impairment, presence of motor fluctuations and quality of life (p < 0.05). Patients with visuospatial dysfunction and patients with a higher PIGD score had a blunted motor daily activity (p = 0.006 and p = 0.001, respectively), independently by the influence of age and other motor scores. Fibroblasts obtained by PD patients (n = 5) had an impaired BMAL1 cycle compared to controls (n = 3, p = 0.01). Moreover, a PD flat BMAL1 profile was associated with the lowest cell proliferation and the largest cell morphology. This study contributes to the growing literature on CR abnormalities in the pathophysiology of Parkinson's disease providing a link between the clinical and biological patient chronotype and the disease phenomenology.

The human sleep-cycle has been divided into discrete sleep stages that can be recognized in electroencephalographic (EEG) and other bio-signals by trained specialists or machine learning systems. It is however unclear whether these human-defined stages can be re-discovered with unsupervised methods of data analysis, using only a minimal amount of generic pre-processing. Based on EEG data, recorded overnight from sleeping human subjects, we investigate the degree of clustering of the sleep stages using the General Discrimination Value as a quantitative measure of class separability. Virtually no clustering is found in the raw data, even after transforming the EEG signals of each 30-s epoch from the time domain into the more informative frequency domain. However, a Principal Component Analysis (PCA) of these epoch-wise frequency spectra reveals that the sleep stages separate significantly better in the low-dimensional sub-space of certain PCA components. In particular the component C₁(t) can serve as a robust, continuous ‘master variable’ that encodes the depth of sleep and therefore correlates strongly with the ‘hypnogram’, a common plot of the discrete sleep stages over time. Moreover, C₁(t) shows persistent trends during extended time periods where the sleep stage is constant, suggesting that sleep may be better understood as a continuum. These intriguing properties of C₁(t) are not only relevant for understanding brain dynamics during sleep, but might also be exploited in low-cost single-channel sleep tracking devices for private and clinical use.