Objective Measurement and Characterization of Sleep Benefit in Parkinson's Disease

Slow-wave sleep and REM sleep without atonia predict motor progression in Parkinson's disease

BACKGROUND

Growing evidence supports the potential role of sleep in the motor progression of Parkinson's disease (PD). Slow-wave sleep (SWS) and rapid eye movement (REM) sleep without atonia (RWA) are important sleep parameters. The association between SWS and RWA with PD motor progression and their predictive value have not yet been elucidated.

METHODS

We retro-prospectively analyzed clinical and polysomnographic data of 136 patients with PD. The motor symptoms were assessed using Unified Parkinson's Disease Rating Scale Part III (UPDRS III) at baseline and follow-up to determine its progression. Partial correlation analysis was used to explore the cross-sectional associations between slow-wave energy (SWE), RWA and clinical symptoms. Longitudinal analyses were performed using Cox regression and linear mixed-effects models.

RESULTS

Among 136 PD participants, cross-sectional partial correlation analysis showed SWE decreased with the prolongation of the disease course (P = 0.046), RWA density was positively correlated with Hoehn & Yahr (H-Y) stage (tonic RWA, P < 0.001; phasic RWA, P = 0.002). Cox regression analysis confirmed that low SWE (HR = 1.739, 95% CI = 1.038-2.914; P = 0.036; FDR-P = 0.036) and high tonic RWA (HR = 0.575, 95% CI = 0.343-0.963; P = 0.032; FDR-P = 0.036) were predictors of motor symptom progression. Furthermore, we found that lower SWE predicted faster rate of axial motor progression (P < 0.001; FDR-P < 0.001) while higher tonic RWA density was associated with faster rate of rigidity progression (P = 0.006; FDR-P = 0.024) using linear mixed-effects models.

CONCLUSIONS

These findings suggest that SWS and RWA might represent markers of different motor subtypes progression in PD.

Sleep benefit in patients with Parkinson's disease is associated with the dopamine transporter expression in putamen

PURPOSE

Sleep benefit (SB) is a well-known phenomenon in patients with Parkinson's disease (PD); however, the mechanisms underlying this phenomenon remain unclear. This study aimed to evaluate whether the SB phenomenon in PD patients is associated with dopamine transporter (DAT) expression levels in the striatum.

METHODS

The data of 125 PD patients were collected and divided into SB (n = 61) and non-SB (nSB) groups (n = 54) depending on whether they had SB or not. DAT expression on both sides of the striatum in PD patients was measured using 2b-carbomethoxy-3b-(4-trimethylstannylphenyl) tropane (11C-CFT) positron emission tomography imaging. The clinical variables, sleep scores, and striatum 11C-CFT uptake index of PD patients between the SB and nSB groups were compared. The associations of clinical variables, sleep scores, and striatum 11C-CFT uptake index with the SB variable were analyzed using logistic regression analysis. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of the striatum 11C-CFT uptake index in distinguishing SB patients from nSB patients.

RESULTS

The tremor subtype ratio (P = 0.011), levodopa equivalent daily dose (LEDD) (P < 0.001), sleep efficiency score (P = 0.025), habitual sleep efficiency (P = 0.012), and night sleep duration (P = 0.005) in the SB group were significantly different from those in the nSB group. The 11C-CFT uptake index in both the contralateral and ipsilateral striata in the SB group was significantly higher than that in the nSB group (P < 0.05). The binary logistic regression showed that SB variables were significantly and independently associated with tremor subtype (P = 0.048), LEDD (P = 0.021), sleep duration at night (P = 0.035), 11C-CFT uptake index in the contralateral (P = 0.013) and ipsilateral (P = 0.019) putamen in PD patients after correction for important clinical confounders. ROC analysis showed that the 11C-CFT uptake index on the onset side of the putamen had a high capacity (AUC: 0.916) to distinguish SB patients from nSB patients with high sensitivity (83.33 %) and specificity (88.89 %).

CONCLUSION

DAT expression in the putamen was associated with the SB phenomenon in PD patients, and the putamen DAT expression level could predict the SB phenomenon in PD patients.

Clinical Review of Smartphone Applications in Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is the second leading neurodegenerative disease worldwide. Important advances in monitoring and treatment have been made in recent years. This article reviews literature on utility of smartphone applications in monitoring PD symptoms that may ultimately facilitate improved patient care, and on movement modulation as a potential therapeutic.

REVIEW SUMMARY

Novel mobile phone applications can provide one-time and/or continuous data to monitor PD motor symptoms in person or remotely, that may support precise therapeutic adjustments and management decisions. Apps have also been developed for medication management and treatment.

CONCLUSIONS

Smartphone applications provide a wide array of platforms allowing for meaningful short-term and long-term data collection and are also being tested for intervention. However, the variability of the applications and the need to translate complicated sensor data may hinder immediate clinical applicability. Future studies should involve stake-holders early in the design process to promote usability and streamline the interface between patients, clinicians, and PD apps.

Digital Technology in Movement Disorders: Updates, Applications, and Challenges

Purpose of Review

Digital technology affords the opportunity to provide objective, frequent, and sensitive assessment of disease outside of the clinic environment. This article reviews recent literature on the application of digital technology in movement disorders, with a focus on Parkinson’s disease (PD) and Huntington’s disease.

Recent Findings

Recent research has demonstrated the ability for digital technology to discriminate between individuals with and without PD, identify those at high risk for PD, quantify specific motor features, predict clinical events in PD, inform clinical management, and generate novel insights.

Summary

Digital technology has enormous potential to transform clinical research and care in movement disorders. However, more work is needed to better validate existing digital measures, including in new populations, and to develop new more holistic digital measures that move beyond motor features.

Sleep in Parkinson's disease

Sleep disturbances are common in Parkinson's disease and comprise the entire spectrum of sleep disorders. On the one hand regulation of sleep and wakefulness is affected in Parkinson's disease, leading to the development of disorders, such as insomnia and daytime sleepiness. While on the other hand control of motor activity during sleep is impaired, with subsequent manifestation of parasomnias (mainly REM sleep behavior disorders, but also, albeit more rarely, sleepwalking, and overlap parasomnia). Restless legs syndrome has been reported to be frequent in patients with Parkinson's disease, although there is no consensus on whether it is more frequent in Parkinson's disease than in the general population. The same is true for sleep-related breathing disorders. Regarding the diagnosis of sleep disorders in patients with Parkinson's disease, one of the main challenges is correctly identifying excessive daytime sleepiness as there are many potential confounding factors, for example it is necessary to distinguish sleep-related breathing disorders from medication effects, and to distinguish restless legs syndrome from the concomitant presence of potential mimics specific to Parkinson's disease, such as akathisia, nocturnal leg cramps, nocturnal hypokinesia, early morning dystonia, etc. The correct diagnosis of REM sleep behavior disorder is also not always easy, and video-polysomnography should be performed in order to exclude mimic-like movements at the end of sleep apneas or violent periodic leg movements of sleep. These aspects and specific considerations about diagnosis and treatment of sleep disorders in patients with Parkinson's disease will be reviewed.

Quantitative associations between objective sleep measures and early-morning mobility in Parkinson’s disease: cross-sectional analysis of the PHASE study

Study Objectives

Previous studies have suggested associations between sleep measures and early-morning akinesia; however, objective evidence is limited. The purpose of this study was to evaluate the associations between objective sleep measures and morning mobility among patients with Parkinson’s disease (PD).

Methods

In this cross-sectional study, we measured objective sleep parameters and morning mobility in 157 patients with PD (mean age, 71.4 years) for six consecutive days using an actigraph placed on the nondominant wrist. Low morning mobility was defined as less than 100 counts/min within the first 2 hours after rising.

Results

The mean duration of low morning mobility was 55.7 minutes (SD, 23.8), and the mean sleep parameters were as follows: sleep efficiency (SE), 72.1% (13.6); wake after sleep onset (WASO), 104.7 minutes (57.9); total sleep time (TST), 343.6 minutes (104.0); and fragmentation index (FI), 3.5 (3.4). Multivariable linear regression analysis adjusted for potential confounders demonstrated significant associations between better objective sleep measures and shorter low morning mobility (SE per %: β, −0.419; 95% CI = −0.635 to −0.204; p &lt; 0.001; WASO per min: β, 0.056; 95% CI = 0.003 to 0.109; p = 0.039; and FI per unit; β, 1.161; 95% CI = 0.300 to 2.023; p = 0.009) but not TST (p = 0.78). These findings were not altered by different cutoff values of mobility (50 counts/min) or duration (1 h after rising).

Conclusions

In patients with PD, better objective sleep measures are significantly associated with shorter low morning mobility. Future studies investigating whether improved sleep reduces symptoms of low morning mobility are required.

The related factors of sleep benefit in Parkinson's disease: A systematic review and meta-analysis

Background

Sleep benefit (SB) refers to the poorly understood phenomenon in Parkinson’s disease (PD) in which patients wake up in the morning with improved motor function. Although previous studies have suggested that several related factors are associated with SB, this relationship remains controversial.

Objective

This systematic review and meta-analysis aimed to identify the possible related factors of SB in PD.

Methods

We searched PubMed, EMBASE and WanFang databases to collect eligible articles. We calculated pooled estimates of odds ratios (ORs) or the mean deviation (MD) with 95% confidence intervals.

Results

We found 3 related factors associated with SB: the duration of PD (MD 1.22, 95% CI: 0.21–2.23), sleep efficiency (MD -4.48,95% CI: -7.24- -2.44), and on-state MDS-UPDRS-Ⅲ total score (MD 3.05, 95% CI: 0.53–5.57).

Conclusion

PD patients with SB are more likely to have a long duration of PD, a low sleep efficiency and a high MDS-UPDRS-Ⅲ total score. Our work helps obtain a better understanding of sleep SB in PD and its underlying mechanisms. More studies need to be conducted to evaluate the associations between clinical factors in PD and the SB phenomenon.