Quantitative REM Sleep without Atonia in Parkinson's Disease and Essential Tremor

REM sleep behavior disorder and Prodromal Parkinson's Disease in patients with Essential Tremor

Several studies suggested the presence of non-motor symptoms in Essential Tremor (ET), including REM sleep behavioral disorder (RBD). RBD is an essential criterion for Prodromal Parkinson's Disease (PPD), suggesting a link between ET and PD. Our objective was to assess the prevalence and features of ET patients with RBD and PDD. RBD was diagnosed by questionnaire screening, followed by polysomnography. PPD risk factors and prodromic markers were assessed with a structured protocol. Patients were characterized regarding tremor features. ET patients with RBD (ET-RBD) and PPD (ET-PPD) were compared to patients without RBD (ET-nonRBD) and without PPD (ET-nonPPD), respectively. ET-RBD patients were also compared with a group of isolated RBD (iRBD) regarding PPD features. We assessed a total of 64 ET patients. Five (8.3 %) and 4 (6.3 %) had criteria for RBD and PPD, respectively. ET-RBD patients did not differ from ET-nonRBD except for a higher prevalence of PPD. There were no significant differences between ET-RBD and iRBD (n = 12) groups. ET-PPD had a higher prevalence of positive DaT-Scans and RBD compared to ET-nonPPD. Three ET-RBD patients had PPD and 3 ET-PPD had RBD. Both RBD and PPD are more frequent in ET patients than in general aged population but not related with specific tremor features. ET-RBD patients did not differ significantly from iRBD patients, a group prone to develop PD. These data suggest a link between ET and PD and are in accordance with studies showing an increase incidence of lewy-body pathology and PD in ET populations.

Distinguishing essential tremor from Parkinson's disease: clinical and experimental tools

INTRODUCTION

Essential tremor (ET) and Parkinson's disease (PD) are the most common causes of tremor and the most prevalent movement disorders, with overlapping clinical features that can lead to diagnostic challenges, especially in the early stages.

AREAS COVERED

In the present paper, the authors review the clinical and experimental studies and emphasized the major aspects to differentiate between ET and PD, with particular attention to cardinal phenomenological features of these two conditions. Ancillary and experimental techniques, including neurophysiology, neuroimaging, fluid biomarker evaluation, and innovative methods, are also discussed for their role in differential diagnosis between ET and PD. Special attention is given to investigations and tools applicable in the early stages of the diseases, when the differential diagnosis between the two conditions is more challenging. Furthermore, the authors discuss knowledge gaps and unsolved issues in the field.

EXPERT OPINION

Distinguishing ET and PD is crucial for prognostic purposes and appropriate treatment. Additionally, accurate diagnosis is critical for optimizing clinical and experimental research on pathophysiology and innovative therapies. In a few years, integrated technologies could enable accurate, reliable diagnosis from early disease stages or prodromal stages in at-risk populations, but further research combining different techniques is needed.

[Application of Polysomnography in Common Neurodegenerative Diseases]

At present, the etiology and pathogenesis of most neurodegenerative diseases are still not fully understood, which poses challenges for the prevention, diagnosis, and treatment of these diseases. Sleep disorders are one of the common chief complaints of neurodegenerative diseases. When patients suffer from comorbid sleep disorder and neurodegenerative diseases, the severity of their condition increases, the quality of their life drops further, and the difficulty of treatment increases. A large number of studies have been conducted to monitor the sleep of patients with neurodegenerative diseases, and it has been found that there are significant changes in their polysomnography (PSG) results compared to those of healthy control populations. In addition, there are also significant differences between the PSG findings of patients with different neurodegenerative diseases and the differences are closely associated with the pathogenesis and development of the disease. Herein, we discussed the characteristics of the sleep structure of patients with Parkinson's disease, Alzheimer's disease, Huntington's disease, and dementia with Lewy bodies and provided a brief review of the sleep disorders and the PSG characteristics of these patients. The paper will help improve the understanding of the pathogenesis and pathological changes of neurodegenerative diseases, clarify the relationship between sleep disorders and these diseases, improve clinicians' further understanding of these diseases, and provide a basis for future research.

Quantitative Network Comparisons of REM Sleep Without Atonia Across the α-Synucleinopathy Spectrum: A Systematic Review

Purpose

Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is characterized by REM sleep without atonia (RWA) and is regarded as the prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). RWA is also associated with neurodegeneration driven by α-synucleinopathy. However, the level of RWA across the α-synucleinopathy spectrum remains elusive. We aimed to rate the percentage of RWA across the α-synucleinopathy spectrum, encompassing prodromal and overt phenotypes.

Methods

A systematic search was conducted in the PubMed, Embase, Web of Science, and Cochrane Library databases. We included cohort, cross-sectional, and case-control studies comparing the RWA percentage during REM sleep evaluated by tonic chin activity (RWA%-T) or by phasic chin activity (RWA%-P) across the α-synucleinopathy spectrum. Bayesian network meta-analysis was used to combine both direct and indirect evidence regarding the group differences in the RWA%-T and RWA%-P. The surface under the cumulative ranking curve was used to estimate the ranked probability.

Results

Fifteen articles met the inclusion criteria. The investigations included 204 iRBD, 295 PD with RBD (PDwtRBD), 187 PD without RBD (PDwoRBD), 42 MSAwtRBD, 9 DLBwtRBD patients, and 246 controls. MSAwtRBD ranked first in RWA%-T, whereas iRBD ranked first in RWA%-P. RWA% in PDwoRBD patients was comparable to that in the controls and was lower than that in PDwtRBD patients.

Conclusion

Overt phenotypes such as MSAwtRBD and PDwtRBD ranked high in RWA%-T, whereas iRBD, a prodromal type, ranked highest in RWA%-P. Taken together, our data suggest that the percentage of neurodegeneration in RBD patients may be associated with RWA%-T rather than RWA%-P.

Prospero Registration Number

CRD42021276445.

Actigraphy Enables Home Screening of Rapid Eye Movement Behavior Disorder in Parkinson's Disease

OBJECTIVES

Rapid eye movement sleep behavior disorder (RBD) is a potentially harmful, often overlooked sleep disorder affecting up to 70% of Parkinson's disease patients. Current diagnosis relies on nocturnal video-polysomnography, which is an expensive and cumbersome examination requiring specific clinical expertise. Here, we explored the use of wrist actigraphy to enable automatic RBD diagnoses in home settings.

METHODS

A total of 26 Parkinson's disease patients underwent 2-week home wrist actigraphy, followed by two in-laboratory evaluations. Patients were classified as RBD versus non-RBD based on dream enactment history and video-polysomnography. We comprehensively characterized patients' movement patterns during sleep using actigraphic signals. We then trained machine learning classification algorithms to discriminate patients with or without RBD using the most relevant features. Classification performance was quantified with respect to clinical diagnosis, separately for in-laboratory and at-home recordings. Performance was further validated in a control group of non-Parkinson's disease patients with other sleep conditions.

RESULTS

To characterize RBD, actigraphic features extracted from both (1) individual movement episodes and (2) global nocturnal activity were critical. RBD patients were more active overall, and showed movements that were shorter, of higher magnitude, and more scattered in time. Using these features, our classification algorithms reached an accuracy of 92.9 ± 8.16% during in-clinic tests. When validated on home recordings in Parkinson's disease patients, accuracy reached 100% over a 2-week window, and was 94.4% in non-Parkinson's disease control patients. Features showed robustness across tests and conditions.

INTERPRETATION

These results open new perspectives for faster, cheaper, and more regular screening of sleep disorders, both for routine clinical practice and clinical trials. ANN NEUROL 2023;93:317-329.

Quantification of REM sleep without atonia: A review of study methods and meta-analysis of their performance for the diagnosis of RBD

The present review focuses on REM sleep without atonia (RSWA) scoring methods. In consideration of the numerous papers published in the last decade, that used different methods for the quantification of RSWA, their systematic revision is an emerging need. We made a search using the PubMed, Embase, Scopus and Web of Science Databases, from 2010 until December 2021, combining the search term "RSWA" with "scoring methods", "IRBD", "alfasyn disease", and "neurodegenerative disease", and with each of the specific sleep disorders, diagnosed according to current criteria, with the identification of the references of interest for the topic. Furthermore, a Meta-analysis of the diagnostic performance of RSWA scoring methods, in terms of sensitivity and specificity, was carried out. The comparison of the hierarchical summary receiver-operating characteristic curves obtained for visual methods and that obtained for the automated REM sleep atonia index (RAI), shows substantially similar prediction areas indicating a comparable performance. This systematic review and meta-analysis support the validity of a series of visual methods and of the automated RAI in the quantification of RSWA with the purpose to guide clinicians in the interpretation of their results and their correct and efficient use within the diagnostic work-up for REM sleep behavior disorder.

Sleep matters: Neurodegeneration spectrum heterogeneity, combustion and friction ultrafine particles, industrial nanoparticle pollution, and sleep disorders-Denial is not an option

Sustained exposures to ubiquitous outdoor/indoor fine particulate matter (PM_2.5), including combustion and friction ultrafine PM (UFPM) and industrial nanoparticles (NPs) starting in utero, are linked to early pediatric and young adulthood aberrant neural protein accumulation, including hyperphosphorylated tau (p-tau), beta-amyloid (Aβ_{1 - 42}), α-synuclein (α syn) and TAR DNA-binding protein 43 (TDP-43), hallmarks of Alzheimer's (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS). UFPM from anthropogenic and natural sources and NPs enter the brain through the nasal/olfactory pathway, lung, gastrointestinal (GI) tract, skin, and placental barriers. On a global scale, the most important sources of outdoor UFPM are motor traffic emissions. This study focuses on the neuropathology heterogeneity and overlap of AD, PD, FTLD, and ALS in older adults, their similarities with the neuropathology of young, highly exposed urbanites, and their strong link with sleep disorders. Critical information includes how this UFPM and NPs cross all biological barriers, interact with brain soluble proteins and key organelles, and result in the oxidative, endoplasmic reticulum, and mitochondrial stress, neuroinflammation, DNA damage, protein aggregation and misfolding, and faulty complex protein quality control. The brain toxicity of UFPM and NPs makes them powerful candidates for early development and progression of fatal common neurodegenerative diseases, all having sleep disturbances. A detailed residential history, proximity to high-traffic roads, occupational histories, exposures to high-emission sources (i.e., factories, burning pits, forest fires, and airports), indoor PM sources (tobacco, wood burning in winter, cooking fumes, and microplastics in house dust), and consumption of industrial NPs, along with neurocognitive and neuropsychiatric histories, are critical. Environmental pollution is a ubiquitous, early, and cumulative risk factor for neurodegeneration and sleep disorders. Prevention of deadly neurological diseases associated with air pollution should be a public health priority.

Non-REM sleep with hypertonia in Parkinsonian Spectrum Disorders: A pilot investigation

INTRODUCTION

From an ongoing multicenter effort toward differentiation of Parkinsonian spectrum disorders (PSD) from other types of neurodegenerative disorders, the sleep biomarker non-rapid-eye-movement sleep with hypertonia (NRH) emerged.

METHODS

This study included in the PSD group patients with dementia with Lewy bodies/Parkinson disease dementia (DLB/PDD = 16), Parkinson disease (PD = 16), and progressive supranuclear palsy (PSP = 13). The non-PSD group included patients with Alzheimer disease dementia (AD = 24), mild cognitive impairment (MCI = 35), and a control group with normal cognition (CG = 61). In-home, multi-night Sleep Profiler studies were conducted in all participants. Automated algorithms detected NRH, characterized by elevated frontopolar electromyographic power. Between-group differences in NRH were evaluated using Logistic regression, Mann-Whitney U and Chi-squared tests.

RESULTS

NRH was greater in the PSD group compared to non-PSD (13.9 ± 11.0% vs. 3.1 ± 4.7%, P < 0.0001). The threshold NRH≥5% provided the optimal between-group differentiation (AUC = 0.78, P < 0.001). NRH was independently associated with the PSD group after controlling for age, sex, and SSRI/SNRI use (P < 0.0001). The frequencies of abnormal NRH by subgroup were PSP = 92%, DLB/PDD = 81%, PD = 56%, MCI = 26%, AD = 17%, and CG = 16%. The odds of abnormal NRH in each PSD subgroup ranged from 3.7 to 61.2 compared to each non-PSD subgroup. The night-to-night and test-retest intraclass correlations were excellent (0.78 and 0.84, both P < 0.0001).

CONCLUSIONS

In this pilot study, NRH appeared to be a novel candidate sleep biomarker for PSD-related neurodegeneration. Future studies in larger cohorts are needed to confirm these findings, understand the etiology of NRH magnitude/duration, and determine whether it is an independent prodromal marker for specific neurodegenerative pathologies.