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Clinical Neurophysiology Practice 2024
PubMed: 38328387
DOI: 10.1016/j.cnp.2024.01.002 -
Neuroscience and Biobehavioral Reviews Dec 2023Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological.... (Review)
Review
Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological. Although these dimensions often fluctuate in step, they can also dissociate. The current paradigm that views sleep as made of global NREM and REM states fail to account for these dissociations. This conundrum can be dissolved by stressing the existence and significance of the local regulation of sleep. We will review the evidence in animals and humans, healthy and pathological brains, showing different forms of local sleep and the consequences on behavior, cognition, and subjective experience. Altogether, we argue that the notion of local sleep provides a unified account for a host of phenomena: dreaming in REM and NREM sleep, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness. Yet, the physiological origins of local sleep or its putative functions remain unclear. Exploring further local sleep could provide a unique and novel perspective on how and why we sleep.
Topics: Animals; Humans; Sleep; Sleep, REM; Brain; Wakefulness; Cognition; Electroencephalography
PubMed: 37972882
DOI: 10.1016/j.neubiorev.2023.105465 -
Brain : a Journal of Neurology Aug 2023Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of...
Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.
Topics: Male; Humans; Female; Synucleinopathies; Alzheimer Disease; Cerebral Cortical Thinning; REM Sleep Behavior Disorder; Mitochondria; Atrophy
PubMed: 36826230
DOI: 10.1093/brain/awad044 -
Frontiers in Cellular and Infection... 2023Microbiota and their interaction with hosts have been of great interest in brain research in recent years. However, the role of oral microbiota in mental illness and the...
INTRODUCTION
Microbiota and their interaction with hosts have been of great interest in brain research in recent years. However, the role of oral microbiota in mental illness and the underlying mechanism of oral-brain communication remains elusive. Sleep bruxism (SB) is an oral parafunctional activity related to the nervous system and is considered a risk factor for harmful clinical consequences and severe systemic conditions. Exploring the connection between oral microbiota and sleep bruxism may deepen our understanding of the complex relationship between oral-brain axis and provide insights for treatment.
METHODS
In this study, salivary samples were collected from 22 individuals with SB and 21 healthy controls, and metagenomics with metabolomics was performed. Nonparametric Wilcoxon test were applied for the statistical analysis between the two groups. Microbial dysbiosis and altered oral metabolites were found in the SB individuals.
RESULTS
The characteristic metabolite N-acetylglucosamine (GlcNAc) (VIP=8.4823, P<0.05) was correlated to a statistically lower Streptococcus mitis level in SB individuals. Salivary IFN-g level and IFN-g/IL-4 ratio were detected with significant changes in a chip assay. Amino acid metabolism pathways were upregulated, and the pathway with the largest number of differentially expressed genes is related to amino-tRNA charging pathway, while the most significantly enriched pathway is related to arginine biosynthesis. Neurotransmitter-associated pathways with glutamatergic and GABAergic synapses and cardiovascular system-related pathways were enriched in the SB group.
DISCUSSION
These results indicate a possible neuroimmune regulatory network of oral-brain communication in SB, which helps explain the mechanism of the oral microbiome with the host in sleep bruxers and provides a reference for early clinical and therapeutic intervention to improve the diagnosis and treatment of SB and similar diseases.
Topics: Humans; Sleep Bruxism; Sleep; Brain; Risk Factors
PubMed: 38125907
DOI: 10.3389/fcimb.2023.1321855 -
Annals of Clinical and Translational... Sep 2023Synucleinopathies-related disorders such as Lewy body dementia (LBD) and isolated/idiopathic REM sleep behavior disorder (iRBD) have been associated with...
Synucleinopathies-related disorders such as Lewy body dementia (LBD) and isolated/idiopathic REM sleep behavior disorder (iRBD) have been associated with neuroinflammation. In this study, we examined whether the human leukocyte antigen (HLA) locus plays a role in iRBD and LBD. In iRBD, HLA-DRB1*11:01 was the only allele passing FDR correction (OR = 1.57, 95% CI = 1.27-1.93, p = 2.70e-05). We also discovered associations between iRBD and HLA-DRB1 70D (OR = 1.26, 95%CI = 1.12-1.41, p = 8.76e-05), 70Q (OR = 0.81, 95%CI = 0.72-0.91, p = 3.65e-04) and 71R (OR = 1.21, 95%CI = 1.08-1.35, p = 1.35e-03). Position 71 (p = 0.00102) and 70 (p = 0.00125) were associated with iRBD. Our results suggest that the HLA locus may have different roles across synucleinopathies.
Topics: Humans; Lewy Body Disease; REM Sleep Behavior Disorder; Synucleinopathies; HLA-DRB1 Chains; HLA Antigens
PubMed: 37401389
DOI: 10.1002/acn3.51841 -
World Journal of Clinical Cases Dec 2023Artificial intelligence (AI) has impacted many areas of healthcare. AI in healthcare uses machine learning, deep learning, and natural language processing to analyze... (Review)
Review
Artificial intelligence (AI) has impacted many areas of healthcare. AI in healthcare uses machine learning, deep learning, and natural language processing to analyze copious amounts of healthcare data and yield valuable outcomes. In the sleep medicine field, a large amount of physiological data is gathered compared to other branches of medicine. This field is primed for innovations with the help of AI. A good quality of sleep is crucial for optimal health. About one billion people are estimated to have obstructive sleep apnea worldwide, but it is difficult to diagnose and treat all the people with limited resources. Sleep apnea is one of the major contributors to poor health. Most of the sleep apnea patients remain undiagnosed. Those diagnosed with sleep apnea have difficulty getting it optimally treated due to several factors, and AI can help in this situation. AI can also help in the diagnosis and management of other sleep disorders such as insomnia, hypersomnia, parasomnia, narcolepsy, shift work sleep disorders, periodic leg movement disorders, In this manuscript, we aim to address three critical issues about the use of AI in sleep medicine: (1) How can AI help in diagnosing and treating sleep disorders? (2) How can AI fill the gap in the care of sleep disorders? and (3) What are the ethical and legal considerations of using AI in sleep medicine?
PubMed: 38130791
DOI: 10.12998/wjcc.v11.i34.8106 -
Journal of Child Psychology and... Oct 2023Sleep difficulties are common in children with attention-deficit/hyperactivity disorder (ADHD). However, sleep problems are multifaceted and little is known about the...
BACKGROUND
Sleep difficulties are common in children with attention-deficit/hyperactivity disorder (ADHD). However, sleep problems are multifaceted and little is known about the variation in sleep difficulties across children with ADHD. We examined the profiles of sleep difficulties in children with ADHD and associated clinical factors (e.g. co-occurring mental health conditions, stimulant use and parent mental health).
METHODS
Data from two harmonised studies of children with ADHD (total: N = 392, ages 5-13 years) were used. Parents completed measures of children's sleep, co-occurring mental health conditions and their own mental health. Both parents and teachers completed measures of child ADHD symptoms and emotional and conduct symptoms. Latent profile analysis was used to identify sleep profiles, and multinomial logistic regression assessed clinical correlates of the groups.
RESULTS
Five sleep profiles were identified: (a) insomnia/delayed sleep phase (36%), (b) generalised sleep difficulties at sleep onset and overnight (25%), (c) high anxious/bedtime resistance difficulties (11%), (d) overnight sleep difficulties including obstructive sleep apnoea and parasomnias (5%) and (e) no sleep difficulties (22%). Compared with the group without sleep difficulties, the generalised, anxious/bedtime resistance and insomnia/delayed sleep phase sleep had greater parent-reported emotional and conduct symptoms, co-occurring anxiety and increased parent mental health difficulties. The generalised and anxious/bedtime resistance groups also had greater parent-reported ADHD symptoms, with the anxious/bedtime resistance sleep group also having more frequent co-occurring depression and teacher-reported emotional symptoms.
CONCLUSIONS
The sleep difficulties experienced by children with ADHD are varied. Supports to help children with ADHD need to consider the particular profiles of sleep difficulties experienced and broader clinical characteristics. Tailored intervention approaches are likely needed (including a need to address parent mental health).
Topics: Humans; Child; Attention Deficit Disorder with Hyperactivity; Sleep Initiation and Maintenance Disorders; Sleep Wake Disorders; Anxiety; Sleep; Parents
PubMed: 37272196
DOI: 10.1111/jcpp.13835