NREM sleep alpha and sigma activity in Parkinson's disease: evidence for conflicting electrophysiological activity?

Sleep disorders and Parkinson's disease: is there a right direction?

In the last years, the hypothesis of a close relationship between sleep disorders (SDs) and Parkinson's disease (PD) has significantly strengthened. Whether this association is causal has been also highlighted by recent evidence demonstrating a neurobiological link between SDs and PD. Thus, the question is not whether these two chronic conditions are mutually connected, but rather how and when this relationship is expressed. Supporting this, not all SDs manifest with the same temporal sequence in PD patients. Indeed, SDs can precede or occur concomitantly with the onset of the clinical manifestation of PD. This review discusses the existing literature, putting under a magnifying glass the timing of occurrence of SDs in PD-neurodegeneration. Based on this, here, we propose two possible directions for studying the SDs-PD relationship: the first direction, from SDs to PD, considers SDs as potential biomarker/precursor of future PD-neurodegeneration; the second direction, from PD to SDs, considers SDs as concomitant symptoms in manifest PD, mainly related to primary PD-neuropathology and/or parkinsonian drugs. Furthermore, for each direction, we questioned SDs-PD relationship in terms of risk factors, neuronal circuits/mechanisms, and impact on the clinical phenotype and disease progression. Future research is needed to investigate whether targeting sleep may be the winning strategy to treat PD, in the context of a personalized precision medicine.

Quantitative Sleep Electroencephalogram in Parkinson's Disease: A Case-Control Study

BACKGROUND

Sleep disorders are common in Parkinson's disease (PD) and include alterations in sleep-related EEG oscillations.

OBJECTIVE

This case-control study tested the hypothesis that patients with PD would have a lower density of Scalp-Slow Wave (SW) oscillations and higher slow-to-fast frequencies ratio in rapid eye movement (REM) sleep than non-PD controls. Other sleep-related quantitative EEG (qEEG) features were also examined, including SW morphology, sleep spindles, and Scalp-SW spindle phase-amplitude coupling.

METHODS

Polysomnography (PSG)-derived sleep EEG was compared between PD participants (n = 56) and non-PD controls (n = 30). Following artifact rejection, sleep qEEG analysis was performed in frontal and central leads. Measures included SW density and morphological features of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in Non-REM (NREM) and REM. Differences in qEEG features between PD and non-PD controls were compared using two-tailed Welch's t-tests, and correction for multiple comparisons was performed per the Benjamini-Hochberg method.

RESULTS

SW density was lower in PD than in non-PD controls (F = 13.5, p' = 0.003). The PD group also exhibited higher ratio of slow REM EEG frequencies (F = 4.23, p' = 0.013), higher slow spindle peak frequency (F = 24.7, p' <  0.002), and greater SW-spindle coupling angle distribution non-uniformity (strength) (F = 7.30, p' = 0.034).

CONCLUSION

This study comprehensively evaluates sleep qEEG including SW-spindle phase amplitude coupling in PD compared to non-PD controls. These findings provide novel insights into how neurodegenerative disease disrupts electrophysiological sleep rhythms. Considering the role of sleep oscillatory activity on neural plasticity, future studies should investigate the influence of these qEEG markers on cognition in PD.

Altered Motor Performance, Sleep EEG, and Parkinson's Disease Pathology Induced by Chronic Sleep Deprivation in Lrrk2G2019S Mice

Parkinson's disease (PD) is a multifaceted disease in which environmental variables combined with genetic predisposition cause dopaminergic (DAergic) neuron loss in the substantia nigra pars compacta. The mutation of leucine-rich repeat kinase 2 (Lrrk2) is the most common autosomal dominant mutation in PD, and it has also been reported in sporadic cases. A growing body of research suggests that circadian rhythm disruption, particularly sleep-wake abnormality, is common during the early phase of PD. Our present study aimed to evaluate the impact of sleep deprivation (SD) on motor ability, sleep performance, and PD pathologies in Lrrk2G2019S transgenic mice. After two months of SD, Lrrk2G2019S mice at 12 months of age showed an exacerbated PD-like phenotype with motor deficits, a reduced striatal DA level, degenerated DAergic neurons, and altered sleep structure and biological rhythm accompanied by the decreased protein expression level of circadian locomotor output cycles kaput Lrrk2 gene in the brain. All these changes persisted and were even more evident in 18-month-old mice after 6 months of follow-up. Moreover, a significant increase in α-synuclein aggregation was found in SD-treated transgenic mice at 18 months of age. Taken together, our findings indicate that sleep abnormalities, as a risk factor, may contribute to the pathogenesis and progression of PD. Early detection of sleep disorders and improvement of sleep quality may help to delay disease progression and provide long-term clinical benefits.

A Systematic Survey of Research Trends in Technology Usage for Parkinson's Disease

Parkinson's disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The complexity of PD pathology is amplified due to its dependency on patient diaries and the neurologist's subjective assessment of clinical scales. A significant amount of recent research has explored new cost-effective and subjective assessment methods pertaining to PD symptoms to address this challenge. This article analyzes the application areas and use of mobile and wearable technology in PD research using the PRISMA methodology. Based on the published papers, we identify four significant fields of research: diagnosis, prognosis and monitoring, predicting response to treatment, and rehabilitation. Between January 2008 and December 2021, 31,718 articles were published in four databases: PubMed Central, Science Direct, IEEE Xplore, and MDPI. After removing unrelated articles, duplicate entries, non-English publications, and other articles that did not fulfill the selection criteria, we manually investigated 1559 articles in this review. Most of the articles (45%) were published during a recent four-year stretch (2018-2021), and 19% of the articles were published in 2021 alone. This trend reflects the research community's growing interest in assessing PD with wearable devices, particularly in the last four years of the period under study. We conclude that there is a substantial and steady growth in the use of mobile technology in the PD contexts. We share our automated script and the detailed results with the public, making the review reproducible for future publications.

Etiologies of insomnia in Parkinson's disease - Lessons from human studies and animal models

Sleep disorders are integral to Parkinson's disease (PD). Insomnia, an inability to maintain stable sleep, affects most patients and is widely rated as one of the most debilitating facets of this disease. PD insomnia is often perceived as a multifactorial entity - a consequence of several of the disease symptoms, comorbidities and therapeutic strategies. Yet, this view evolved against a backdrop of a relative scarcity of works trying to directly dissect the underlying neural correlates and mechanisms in animal models. The last years have seen the emergence of a wealth of new evidence regarding the neural underpinnings of insomnia in PD. Here, we review early and recent reports from patients and animal models evaluating the etiology of PD insomnia. We start by outlining the phenomenology of PD insomnia and continue to analyze the evidence supporting insomnia as emanating from four distinct subdivisions of etiologies - the symptoms and comorbidities of the disease, the medical therapy, the degeneration of non-dopaminergic cell groups and subsequent alterations in circadian rhythms, and the degeneration of dopaminergic neurons in the brainstem and its resulting effect on the basal ganglia. Finally, we review emerging neuromodulation-based therapeutic avenues for PD insomnia.

Sleep and circadian rhythms in Parkinson's disease and preclinical models

The use of animals as models of human physiology is, and has been for many years, an indispensable tool for understanding the mechanisms of human disease. In Parkinson's disease, various mouse models form the cornerstone of these investigations. Early models were developed to reflect the traditional histological features and motor symptoms of Parkinson's disease. However, it is important that models accurately encompass important facets of the disease to allow for comprehensive mechanistic understanding and translational significance. Circadian rhythm and sleep issues are tightly correlated to Parkinson's disease, and often arise prior to the presentation of typical motor deficits. It is essential that models used to understand Parkinson's disease reflect these dysfunctions in circadian rhythms and sleep, both to facilitate investigations into mechanistic interplay between sleep and disease, and to assist in the development of circadian rhythm-facing therapeutic treatments. This review describes the extent to which various genetically- and neurotoxically-induced murine models of Parkinson's reflect the sleep and circadian abnormalities of Parkinson's disease observed in the clinic.

Can Corticomuscular Coherence Differentiate between REM Sleep Behavior Disorder with or without Parkinsonism?

REM sleep behavior disorder (RBD) could be a predictor of Parkinsonism even before development of typical motor symptoms. This study aims to characterize clinical features and corticomuscular and corticocortical coherence (CMC and CCC, respectively) during sleep in RBD patients with or without Parkinsonism. We enrolled a total of 105 subjects, including 20 controls, 54 iRBD, and 31 RBD+P patients, patients who were diagnosed as idiopathic RBD (iRBD) and RBD with Parkinsonism (RBD+P) in our neurology department. We analyzed muscle atonia index (MAI) and CMC between EEG and chin/limb muscle electromyography (EMG) and CCC during different sleep stages. Although differences in the CMC of iRBD group were observed only during REM sleep, MAI differences between groups were noted during both REM and NREM N2 stage sleep. During REM sleep, CMC was higher and MAI was reduced in iRBD patients compared to controls (p = 0.001, p < 0.001, respectively). Interestingly, MAI was more reduced in RBD+P compared to iRBD patients. In comparison, CCC was higher in iRBD patients compared to controls whereas CCC was lower in RBD+P groups compared to control and iRBD groups in various frequency bands during both NREM N2 and REM sleep stages. Among them, increased CMC during REM sleep revealed correlation between clinical severities of RBD symptoms. Our findings indicate that MAI, CMC, and CCC showed distinctive features in iRBD and RBD+P patients compared to controls, suggesting potential usefulness to understand possible links between these diseases.

Basal Ganglia Local Field Potentials as a Potential Biomarker for Sleep Disturbance in Parkinson's Disease

Sleep disturbances, specifically decreases in total sleep time and sleep efficiency as well as increased sleep onset latency and wakefulness after sleep onset, are highly prevalent in patients with Parkinson's disease (PD). Impairment of sleep significantly and adversely impacts several comorbidities in this patient population, including cognition, mood, and quality of life. Sleep disturbances and other non-motor symptoms of PD have come to the fore as the effectiveness of advanced therapies such as deep brain stimulation (DBS) optimally manage the motor symptoms. Although some studies have suggested that DBS provides benefit for sleep disturbances in PD, the mechanisms by which this might occur, as well as the optimal stimulation parameters for treating sleep dysfunction, remain unknown. In patients treated with DBS, electrophysiologic recording from the stimulating electrode, in the form of local field potentials (LFPs), has led to the identification of several findings associated with both motor and non-motor symptoms including sleep. For example, beta frequency (13–30 Hz) oscillations are associated with worsened bradykinesia while awake and decrease during non-rapid eye movement sleep. LFP investigation of sleep has largely focused on the subthalamic nucleus (STN), though corresponding oscillatory activity has been found in the globus pallidus internus (GPi) and thalamus as well. LFPs are increasingly being recognized as a potential biomarker for sleep states in PD, which may allow for closed-loop optimization of DBS parameters to treat sleep disturbances in this population. In this review, we discuss the relationship between LFP oscillations in STN and the sleep architecture of PD patients, current trends in utilizing DBS to treat sleep disturbance, and future directions for research. In particular, we highlight the capability of novel technologies to capture and record LFP data in vivo, while patients continue therapeutic stimulation for motor symptoms. These technological advances may soon allow for real-time adaptive stimulation to treat sleep disturbances.

The Neurophysiology of Sleep in Parkinson's Disease

Sleep disturbances are among the most common nonmotor complications of Parkinson's disease (PD), can present in prodromal stages, and progress with advancing disease. In addition to being a symptom of neurodegeneration, sleep disturbances may also contribute to disease progression. Currently, limited options exist to modulate sleep disturbances in PD. Studying the neurophysiological changes that affect sleep in PD at the cortical and subcortical level may yield new insights into mechanisms for reversal of sleep disruption. In this article, we review cortical and subcortical recording studies of sleep in PD with a particular focus on dissecting reported electrophysiological changes. These studies show that slow-wave sleep and rapid eye movement sleep are both notably disrupted in PD. We further explore the impact of these electrophysiological changes and discuss the potential for targeting sleep via stimulation therapy to modify PD-related motor and nonmotor symptoms. © 2021 International Parkinson and Movement Disorder Society.

Recent Progress in Non-motor Features of Parkinson's Disease with a Focus on Circadian Rhythm Dysregulation

Parkinson's disease (PD) is the second most common neurodegenerative disease, which manifests with both motor and non-motor symptoms. Circadian rhythm dysregulation, as one of the most challenging non-motor features of PD, usually appears long before obvious motor symptoms. Moreover, the dysregulated circadian rhythm has recently been reported to play pivotal roles in PD pathogenesis, and it has emerged as a hot topic in PD research. In this review, we briefly introduce the circadian rhythm and circadian rhythm-related genes, and then summarize recent research progress on the altered circadian rhythm in PD, ranging from clinical features to the possible causes of PD-related circadian disorders. We believe that future comprehensive studies on the topic may not only help us to explore the mechanisms of PD, but also shed light on the better management of PD.

Sleep in Parkinson's disease: A systematic review and meta-analysis of polysomnographic findings

Polysomnographic studies have been conducted to explore sleep changes in Parkinson's disease (PD), but the relationships between sleep disturbances and PD are imperfectly understood. We conducted a systematic review of the literature exploring polysomnographic differences between PD patients and controls in EMBASE, MEDLINE, All EBM databases, CINAHL, and PsycIFNO. 67 studies were identified for systematic review, 63 of which were used for meta-analysis. Meta-analyses revealed significant reductions in total sleep time, sleep efficiency, N2 percentage, slow wave sleep, rapid eye movement sleep (REM) percentage, and increases in wake time after sleep onset, N1 percentage, REM latency, apnea hypopnea index, and periodic limb movement index in PD patients compared with controls. There were no remarkable differences in sleep continuity or sleep architecture between PD patients with and without REM sleep behavior disorder (RBD). Our study suggests that PD patients have poor sleep quality and quantity. Sex, age, disease duration, presence of RBD, medication status, cognitive impairment, and adaptation night are factors that contributed to heterogeneity between studies.

An overview of sleep and circadian dysfunction in Parkinson's disease

Sleep and circadian alterations are amongst the very first symptoms experienced in Parkinson's disease, and sleep alterations are present in the majority of patients with overt clinical manifestation of Parkinson's disease. However, the magnitude of sleep and circadian dysfunction in Parkinson's disease, and its influence on the pathophysiology of Parkinson's disease remains often unclear and a matter of debate. In particular, the confounding influences of dopaminergic therapy on sleep and circadian dysfunction are a major challenge, and need to be more carefully addressed in clinical studies. The scope of this narrative review is to summarise the current knowledge around both sleep and circadian alterations in Parkinson's disease. We provide an overview on the frequency of excessive daytime sleepiness, insomnia, restless legs, obstructive apnea and nocturia in Parkinson's disease, as well as addressing sleep structure, rapid eye movement sleep behaviour disorder and circadian features in Parkinson's disease. Sleep and circadian disorders have been linked to pathological conditions that are often co-morbid in Parkinson's disease, including cognitive decline, memory impairment and neurodegeneration. Therefore, targeting sleep and circadian alterations could be one of the earliest and most promising opportunities to slow disease progression. We hope that this review will contribute to advance the discussion and inform new research efforts to progress our knowledge in this field.

Sleep-wake disturbances in the premotor and early stage of Parkinson's disease

PURPOSE OF REVIEW

Review of recent literature pertaining to frequency, associations, mechanisms, and overall significance of sleep--wake disturbances (SWD) in the premotor and early phase of Parkinson's disease.

RECENT FINDINGS

SWD are frequent in Parkinson's disease and their prevalence increases with disease progression. Recent studies confirm previous findings that SWD can appear as initial manifestation of Parkinson's disease even decades before motor signs appear and highlight their clinical associations in these early stages. More intriguingly, new evidence underpins their role as risk factors, predictors, or even as driving force for the neurodegenerative process. As our understanding of sleep--wake neurobiology increases, new hypotheses emerge concerning the pathophysiology of SWD in early Parkinson's disease stages involving dopaminergic and nondopaminergic mechanisms.

SUMMARY

SWD are predictors for the development of parkinsonian syndromes including Parkinson's disease. This may offer the opportunity of developing new preventive strategies and interventions at an early stage of this neurodegenerative disease.

Electroencephalographic prodromal markers of dementia across conscious states in Parkinson's disease

In Parkinson's disease, electroencephalographic abnormalities during wakefulness and non-rapid eye movement sleep (spindles) were found to be predictive biomarkers of dementia. Because rapid eye movement sleep is regulated by the cholinergic system, which shows early degeneration in Parkinson's disease with cognitive impairment, anomalies during this sleep stage might mirror dementia development. In this prospective study, we examined baseline electroencephalographic absolute spectral power across three states of consciousness (non-rapid eye movement sleep, rapid eye movement sleep, and wakefulness) in 68 non-demented patients with Parkinson's disease and 44 healthy controls. All participants underwent baseline polysomnographic recordings and a comprehensive neuropsychological assessment. Power spectral analyses were performed on standard frequency bands. Dominant occipital frequency during wakefulness and ratios of slow-to-fast frequencies during rapid eye movement sleep and wakefulness were also computed. At follow-up (an average 4.5 years after baseline), 18 patients with Parkinson's disease had developed dementia and 50 patients remained dementia-free. In rapid eye movement sleep, patients with Parkinson's disease who later developed dementia showed, at baseline, higher absolute power in delta and theta bands and a higher slowing ratio, especially in temporal, parietal, and occipital regions, compared to patients who remained dementia-free and controls. In non-rapid eye movement sleep, lower baseline sigma power in parietal cortical regions also predicted development of dementia. During wakefulness, patients with Parkinson's disease who later developed dementia showed lower dominant occipital frequency as well as higher delta and slowing ratio compared to patients who remained dementia-free and controls. At baseline, higher slowing ratios in temporo-occipital regions during rapid eye movement sleep were associated with poor performance on visuospatial tests in patients with Parkinson's disease. Using receiver operating characteristic curves, we found that best predictors of dementia in Parkinson's disease were rapid eye movement sleep slowing ratios in posterior regions, wakefulness slowing ratios in temporal areas, and lower dominant occipital frequency. These results suggest that electroencephalographic slowing during sleep is a new promising predictive biomarker for Parkinson's disease dementia, perhaps as a marker of cholinergic denervation.

Overnight S100B in Parkinson's Disease: A glimpse into sleep-related neuroinflammation

Calcium-binding protein B (S100B), a primary product of astrocytes, is a proposed marker of Parkinson's Disease (PD) pathophysiology, diagnosis and progression. However, it has also been implicated in sleep disruption, which is very common in PD. To explore the relationship between S100B, disease severity, sleep symptoms and polysomnography (PSG) findings, overnight changes in serum S100B levels were investigated for the first time in PD. 17 fully treated, non-demented, moderately advanced PD patients underwent PSG and clinical assessment of sleep symptoms. Serum S100B samples were collected immediately before and after the PSG. Results are shown as median [interquartile range]. Night and morning S100B levels were similar, but uncorrelated (rs=-0.277, p=0.28). Morning S100B levels, as opposed to night levels, positively correlated with the Unified Parkinson's Disease rating scale (UPDRS) subsections I and II (rs=0.547, p=0.023; rs=0.542, p=0.025). Compared to those with overnight S100B reduction, patients with overnight S100B elevation had higher H&Y scores (2.5 [0.87] vs. 2 [0.25], p=0.035) and worse total Pittsburgh Sleep Quality Index (PSQI) and Parkinson's Disease Sleep Scores (10 [3.2] vs. 8 [4.5], p=0.037; 92.9 [39] vs. 131.4 [28], p=0.034). Correlation between morning S100B levels and total UPDRS score was strengthened after controlling for total PSQI score (rs=0.531, p=0.034; partial rs=0.699, p=0.004, respectively). Overnight S100B variation and morning S100B were associated with PD severity and perceived sleep disruption. S100B is proposed as a putative biomarker for sleep-related neuroinflammation in PD. Noradrenergic-astrocytic dysfunction is hypothesized as a possible mechanism underlying these findings.

Sleep spindle alterations in patients with Parkinson's disease

The aim of this study was to identify changes of sleep spindles (SS) in the EEG of patients with Parkinson's disease (PD). Five sleep experts manually identified SS at a central scalp location (C3-A2) in 15 PD and 15 age- and sex-matched control subjects. Each SS was given a confidence score, and by using a group consensus rule, 901 SS were identified and characterized by their (1) duration, (2) oscillation frequency, (3) maximum peak-to-peak amplitude, (4) percent-to-peak amplitude, and (5) density. Between-group comparisons were made for all SS characteristics computed, and significant changes for PD patients vs. control subjects were found for duration, oscillation frequency, maximum peak-to-peak amplitude and density. Specifically, SS density was lower, duration was longer, oscillation frequency slower and maximum peak-to-peak amplitude higher in patients vs. controls. We also computed inter-expert reliability in SS scoring and found a significantly lower reliability in scoring definite SS in patients when compared to controls. How neurodegeneration in PD could influence SS characteristics is discussed. We also note that the SS morphological changes observed here may affect automatic detection of SS in patients with PD or other neurodegenerative disorders (NDDs).