A Polysomnographic Study of Parkinson's Disease Sleep Architecture

Exploring obstructive sleep apnea and sleep architecture in Parkinson's disease motor subtypes

INTRODUCTION

Parkinson's disease (PD) can be divided into motor subtypes: postural instability/gait difficulty (PIGD), tremor dominant, and indeterminate. This study aimed to assess differences in sleep structure and obstructive sleep apnea (OSA) between the PIGD and non-PIGD subtypes.

METHODS

PD participants with or without OSA (defined as apnea-hypopnea index (AHI) ≥ 15 events/hour on overnight polysomnography) were included. Patients were separated into two groups: PIGD and non-PIGD. Linear regression was used to explore differences in sleep, AHI, and other respiratory parameters between groups (adjusted for variables determined a priori). Logistic regression adjusted for the same variables was used to determine if the proportion of patients with OSA differed across groups. Subset analyses were performed: subset 1 excluding patients on psychoactive medication; subset 2 excluding patients taking levodopa or dopaminergic agonists (DAs) at nighttime and subset 3 excluding patients on either of the abovementioned drugs.

RESULTS

146 participants were studied. The non-PIGD group had less N3 sleep compared to the PIGD group (12.4% vs 16.9% p = 0.06), reaching significance in subsets 1 and 3. The AHI was significantly lower in the PIGD group (p = 0.047), including when medication effects were removed (p < 0.05). OSA was more frequent in the non-PIGD group, but only significantly in subset 3 (adjusted OR 0.3, p = 0.04).

CONCLUSION

OSA may be more severe in non-PIGD subtypes, and more frequent, in a subset free of psychoactive medication, and of levodopa and DAs, possibly owing to motor complications and dyskinesia. Future studies are required to confirm this.

Effect of exercise on sleep quality in Parkinson's disease: a mini review

The growing incidence of Parkinson's Disease (PD) is a major burden on the healthcare system. PD is caused by the degeneration of dopaminergic neurons and is known for its effects on motor function and sleep. Sleep is vital for maintaining proper homeostasis and clearing the brain of metabolic waste. Adequate time spent in each sleep stage can help maintain homeostatic function; however, patients with PD appear to exhibit sleep impairments. Although medications enhance the function of remaining dopaminergic neurons and reduce motor symptoms, their potential to improve sleep is still under question. Recently, research has shifted towards exercise protocols to help improve sleep in patients with PD. This review aims to provide an overview of how sleep is impaired in patients with PD, such as experiencing a reduction in time spent in slow-wave sleep, and how exercise can help restore normal sleep function. A PubMed search summarized the relevant research on the effects of aerobic and resistance exercise on sleep in patients with PD. Both high and low-intensity aerobic and resistance exercises, along with exercises related to balance and coordination, have been shown to improve some aspects of sleep. Neurochemically, sleeping leads to an increase in toxin clearance, including α-synuclein. Furthermore, exercise appears to enhance the concentration of brain-derived neurotrophic factors, which has preliminary evidence to suggest correlations to time spent in slow-wave sleep. More research is needed to further elucidate the physiological mechanism pertaining to sleep and exercise in patients with PD.

Sleep structure and related clinical characteristics in drug-naïve Parkinson's disease with subjectively different sleep quality

Background

Sleep disturbance is a common non-motor symptom of Parkinson's disease (PD). Most polysomnography (PSG) studies are conducted when patients are in their "on medication" state. Our study aimed to investigate changes in the sleep structure in drug-naive PD patients with poor subjective sleep quality based on polysomnography (PSG) and to explore potential correlations between sleep structure and clinical features of the disease.

Methods

A total of 44 drug-naive PD patients were included. All patients completed a standardized questionnaire to obtain demographic and clinical characteristics and underwent whole-night PSG recording. Patients with PSQI scores >5.5 were considered poor sleepers, and patients with PSQI scores <5.5 were considered to be good sleepers.

Results

There were 24 (54.5%) PD patients in the good sleeper group and 20 (24.5%) PD patients in the poor sleeper group. We observed that poor sleepers had severe non-motor symptoms (NMS) and worse life quality. The PSG displayed that they had a longer wake-up time after sleep onset (WASO) and lower sleep efficiency (SE). Correlation analysis revealed that the micro-arousal index was positively associated with UPDRS-III, and the N1 sleep percentage was negatively associated with the NMS score in good sleepers. For poor sleepers, rapid eye movement (REM) sleep percentage was negatively related to the Hoehn-Yahr (H-Y) stage, WASO increased with UPDRS-III, periodic limb movement index (PLMI) increased with the NMS score, and N2 sleep percentage was negatively related to the score of life quality.

Conclusion

Night awakening is the main manifestation of decreased sleep quality in drug-naive PD patients. Poor sleepers have severe non-motor symptoms and poor life quality. Additionally, the increase in nocturnal arousal events may predict the progression of motor dysfunction.

Chaudhuri's Dashboard of Vitals in Parkinson's syndrome: an unmet need underpinned by real life clinical tests

We have recently published the notion of the "vitals" of Parkinson's, a conglomeration of signs and symptoms, largely nonmotor, that must not be missed and yet often not considered in neurological consultations, with considerable societal and personal detrimental consequences. This "dashboard," termed the Chaudhuri's vitals of Parkinson's, are summarized as 5 key vital symptoms or signs and comprise of (a) motor, (b) nonmotor, (c) visual, gut, and oral health, (d) bone health and falls, and finally (e) comorbidities, comedication, and dopamine agonist side effects, such as impulse control disorders. Additionally, not addressing the vitals also may reflect inadequate management strategies, leading to worsening quality of life and diminished wellness, a new concept for people with Parkinson's. In this paper, we discuss possible, simple to use, and clinically relevant tests that can be used to monitor the status of these vitals, so that these can be incorporated into clinical practice. We also use the term Parkinson's syndrome to describe Parkinson's disease, as the term "disease" is now abandoned in many countries, such as the U.K., reflecting the heterogeneity of Parkinson's, which is now considered by many as a syndrome.

The Home-Based Sleep Laboratory

Sleep disturbances are prevalent in neurodegenerative diseases in general, and in Parkinson's disease (PD) in particular. Recent evidence points to the clinical value of sleep in disease progression and improving quality of life. Therefore, monitoring sleep quality in an ongoing manner at the convenience of one's home has the potential to improve clinical research and to contribute to significantly better personalized treatment. Further, precise mapping of sleep patterns of each patient can contribute to a better understanding of the disease, its progression and the appropriate medical treatment. Here we review selective, state-of-the-art, home-based devices for assessing sleep and sleep related disorders. We highlight the large potential as well as the main challenges. In particular, we discuss medical validity, standardization and regulatory concerns that currently impede widespread clinical adoption of existing devices. Finally, we propose a roadmap with the technological and scientific steps that are required to impact PD research and treatment.

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.

Electrocardiogram-based sleep analysis for sleep apnea screening and diagnosis

PURPOSE

Despite the increasing number of research studies of cardiopulmonary coupling (CPC) analysis, an electrocardiogram-based technique, the use of CPC in underserved population remains underexplored. This study aimed to first evaluate the reliability of CPC analysis for the detection of obstructive sleep apnea (OSA) by comparing with polysomnography (PSG)-derived sleep outcomes.

METHODS

Two hundred five PSG data (149 males, age 46.8 ± 12.8 years) were used for the evaluation of CPC regarding the detection of OSA. Automated CPC analyses were based on ECG signals only. Respiratory event index (REI) derived from CPC and apnea-hypopnea index (AHI) derived from PSG were compared for agreement tests.

RESULTS

CPC-REI positively correlated with PSG-AHI (r = 0.851, p < 0.001). After adjusting for age and gender, CPC-REI and PSG-AHI were still significantly correlated (r = 0.840, p < 0.001). The overall results of sensitivity and specificity of CPC-REI were good.

CONCLUSION

Compared with the gold standard PSG, CPC approach yielded acceptable results among OSA patients. ECG recording can be used for the screening or diagnosis of OSA in the general population.

Deep Phenotyping of Parkinson's Disease

Phenotype is the set of observable traits of an organism or condition. While advances in genetics, imaging, and molecular biology have improved our understanding of the underlying biology of Parkinson's disease (PD), clinical phenotyping of PD still relies primarily on history and physical examination. These subjective, episodic, categorical assessments are valuable for diagnosis and care but have left gaps in our understanding of the PD phenotype. Sensors can provide objective, continuous, real-world data about the PD clinical phenotype, increase our knowledge of its pathology, enhance evaluation of therapies, and ultimately, improve patient care. In this paper, we explore the concept of deep phenotyping-the comprehensive assessment of a condition using multiple clinical, biological, genetic, imaging, and sensor-based tools-for PD. We discuss the rationale for, outline current approaches to, identify benefits and limitations of, and consider future directions for deep clinical phenotyping.

The use of accelerometry as a tool to measure disturbed nocturnal sleep in Parkinson's disease

Sleep disturbances are common in Parkinson’s disease (PD). We used the Parkinson’s KinetiGraph (PKG), an objective movement recording system for PD to assess night time sleep in 155 people aged over 60 and without PD (controls), 72 people with PD (PwP) and 46 subjects undergoing a Polysomnogram (PSG: 36 with sleep disorder and 10 with normal sleep). The PKG system uses a wrist worn logger to capture acceleration and derive a bradykinesia score (BKS) every 2 min over 6 days. The BKS ranges from 0–160 with higher scores associated with lesser mobility. Previously we showed that BKS > 80 were associated with day time sleep and used this to produce scores for night time sleep: Efficiency (Percent time with BKS > 80), Fragmentation (Average duration of runs of BKS > 80) and Sleep Quality (BKS > 111 as a representation of atonia). There was a fair association with BKS score and sleep level as judged by PSG. Using these PKG scores, it was possible to distinguish between normal and abnormal PSG studies with good Selectivity (86%) and Sensitivity (80%). The PKG’s sleep scores were significantly different in PD and Controls and correlated with a subject’s self-assessment (PDSS 2) of the quality, wakefulness and restlessness. Using both the PDSS 2 and the PKG, it was apparent that sleep disturbances were apparent early in disease in many PD subjects and that subjects with poor night time sleep were more likely to have day time sleepiness. This system shows promise as a quantitative score for assessing sleep in Parkinson’s disease.

A movement recording system reveals the occurrence of sleep disturbances in the early stages of Parkinson’s disease (PD). Malcolm Horne, a movement disorders expert at the University in Melbourne, and colleagues assessed night time sleep in 72 patients with PD using a wrist-worn device that captures movement patterns. The Parkinson’s KinetiGraph (PKG) system derives scores that are associated with sleep stages and correlate with patients’ self-assessment of sleep quality, wakefulness and restlessness. Significant differences between the PKG sleep scores of PD patients and age-matched healthy controls confirmed that night time sleep disturbances and day time sleepiness worsen as the disease progresses. Abnormal PKG scores were found in patients affected by the disease for only 3 years highlighting the extent to which sleep is disrupted in early-stage PD.

Quality of Sleep and Sleep Disorders in Patients with Parkinsonism: A Polysomnography Based Study from Rural South India

OBJECTIVE

The objective of this study is to study the quality of sleep, sleep disorders, and polysomnographic profile in Parkinsonism patients from rural areas and to correlate polysomnographic profile with the staging of disease and with sleep questionnaire.

MATERIALS AND METHODS

Between May 2014 and December 2015, 168 Parkinsonism patients were prospectively screened using sleep questionnaire; Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Parkinson Disease Sleep Score-2 (PDSS-2). Sixty patients underwent overnight polysomnography subsequently.

RESULTS

The mean age of 168 patients in the study was 65.3 ± 12.8 years. The mean duration of Parkinsonism was 4.6 ± 3.1 years. The mean ESS, PSQI and PDSS-2 were 12.4 ± 3.2, 7.9 ± 2.1 and 44.7 ± 5.8, respectively. A total of 148 patients (88.1%) had poor quality sleep, which was reported only in 37 patients (22%). Excessive daytime sleepiness (80%) and insomnia (76.7%) were most common symptoms. Polysomnographic profile showed poor sleep efficiency (median interquartile range [IQR] 74.8% [17.8%-99.5%]), reduced slow wave sleep (median [IQR] 0% [0%-9.5%]), and reduced rapid eye movement [REM] sleep (median (IQR) 4.9% [0.1%-24.2%]). Sleep disorders in the study were sleep fragmentation (n = 60, 100%), obstructive sleep apnea syndrome (n = 40, 66.7%), central sleep apnea syndrome (n = 6, 10%), and periodic limb movement disorder (n = 52, 86.7%). Two patients had REM sleep behavioral disorder clinically. There was statistically significant positive correlation between staging of disease, sleep latencies, and sleep questionnaire.

CONCLUSION

Sleep is impaired in majority of Parkinsonism patients which needs to be diagnosed early and managed effectively. Patient education and awareness programs in rural areas regarding sleep disorders in Parkinsonism are required for early diagnosis.

Clinical characteristics of sleep disorders in patients with Parkinson's disease

In order to investigate the sleep quality and influencing factors in patients with Parkinson's disease (PD), 201 PD patients were enrolled and underwent extensive clinical evaluations. Subjective sleep evaluation was assessed using the Pittsburgh Sleep Quality Index (PSQI), and the Epworth Sleepiness Scale (ESS). It was found that poor sleep quality (77.11%) and excessive daytime sleepiness (32.34%) were commonly seen in PD patients and positively correlated with disease severity. Then 70 out of the 201 PD patients and 70 age- and sex-matched controls underwent a polysomnographic recording. The parameters were compared between PD group and control group and the influencing factors of sleep in PD patients were analyzed. The results showed that sleep efficiency (SE) was significantly decreased (P<0.01), and sleep latency (SL) and the arousal index (AI) were increased (P<0.05) in the PD group as compared with those in the control group. SE and total sleep time (TST) were positively correlated with the Hoehn and Yahr (H&Y) stage. There was significant difference in the extent of hypopnea and hypoxemia between the PD group and the control group (P<0.05). Our results indicate that PD patients have an overall poor sleep quality and a high prevalence of sleep disorder, which may be correlated with the disease severity. Respiratory function and oxygen supply are also affected to a certain degree in PD patients.

Sleep Dysfunction in Parkinson's Disease

INTRODUCTION

Sleep disorders are common in Parkinson's Disease (PD). It can antedate the motor manifestations of PD. It is related primarily to the involvement of sleep regulating structures, secondary involvement through motor, depressive and dysautonomic symptoms and the tertiary involvement through anti-parkinsonian medications.

AIM

The aim of our study is to evaluate the frequency and nature of the sleep abnormalities in Idiopathic Parkinson's Disease, analysing the sleep architecture using polysomnography and to correlate the results with the disease parameters.

MATERIALS AND METHODS

A cross-sectional study was done in 50 patients who fulfill the "UK Parkinson's Disease Society Brain Bank Clinical Diagnostic Criteria". They were assessed using detailed history and clinical neurological examination. The severity of the disease was assessed based on Unified Parkinson's Disease Rating Scale (UPDRS part III) and the sleep is assessed using Parkinson's Disease Sleepiness Scale (PDSS) and Epworth Sleepiness Scale (ESS). Objective sleep study was done using polysomnography.

RESULTS

Disturbed sleep was reported by 70% of patients. Sixty percent of them had difficulty in falling asleep and 48% had difficulty in maintaining the sleep due to frequent awakenings. Day time somnolence was reported by 30% of patients. Polysomnographic analysis showed reduced total sleep time in 40 patients (80%). Correlation analysis of the total sleep time, sleep efficiency, deep sleep time, REM sleep time with the disease duration, staging, severity, PDSS Score, showed significant positive correlation (p<0.05). Sleep related movement disorders like Periodic Limb Movements (PLMS), Restless Leg Syndrome (RLS) also showed inverse correlation with disease duration and severity (p<0.05).

CONCLUSION

Sleep architecture is markedly disturbed in patients with Idiopathic Parkinson's disease. There is a reduction in the total sleep time, deep sleep time and REM Sleep duration. Periodic limb movements in sleep, restless leg syndrome, and obstructive sleep apnea contributes to the sleep fragmentation resulting in defective day time functioning.