Cognitive Impairments and Self-Reported Sleep in Early-Stage Parkinson's Disease with Versus without Probable REM Sleep Behavior Disorder

A bibliometric and visual analysis of Parkinson's disease sleep disorders: articles from 2008 to 2023

Objective

Sleep disorder is a common non-motor symptom (NMS) of Parkinson's disease. However, the global research focus on Parkinson's sleep-related disorders (PDSDs) and future trends remains unclear. Currently, there is no bibliometric analysis of PDSDs. We aim to fill this gap, determine the status of current research, and predict future research hotspots.

Methods

We selected 1490 publications from the Web of Science Core Collection (WoSCC) database from 2008 to 2023. Based on CiteSpace and VOSviewer, the analysis was performed from the perspectives of the trend in the number of annual publications, countries, institutions, authors, journals, and co-citations.

Results

A total of 1490 publications from 590 authors from 409 institutions in 77 countries are included. The United States, China, and the United Kingdom are the leading countries. University College London (UCL) is the most prolific institution. Harvard University is the key for cooperation among institutions. Chaudhuri Kallol Ray is a leader in this field. "Movement Disorders" is the most influential journal. "A systematic review of the literature on disorders of sleep and wakefulness in Parkinson's disease from 2005 to 2015" is the publication with the highest co-citation intensity.

Conclusion

The total volume of publications on PDSDs is on the rise, entering a relatively high-yield stage in 2020. The COVID-19 pandemic and the emergence of new keywords may be the reasons behind this phenomenon. "quality of life" and "circadian rhythm" are the mainstream topics of PDSD research. Daytime sleepiness is the PDSD subtype that has received the most attention. Sleep quality, biomarkers, and neurodegeneration are likely to become future research hotspots.

Multiple sleep disturbances are associated with apathy in individuals with Parkinson's disease

Background

Parkinson's disease (PD) is associated with both sleep disturbances and apathy, and within PD, apathy has been associated with REM behavior disorder and excessive daytime sleepiness. Whether other forms of sleep disturbance are similarly associated with apathy in PD remains unclear. This study explored associations between a broad array of sleep disturbances and apathy in 50 individuals with idiopathic PD (PD) and 48 matched controls (MC).

Methods

Participants were adults aged 53-80 (Mdn = 67), 23 % female, and 96 % white. Sleep disturbances were measured with various questionnaires (ISI, PSQI, PROMIS-SD, ESS, PROMIS-SRI, RBDSQ). Mood was measured with the STAI and BDI-II. Apathy was evaluated using the Apathy Scale (AS). Spearman correlations and regression analyses were performed between measures of sleep disturbance and AS in the total sample and each group. Group correlations were compared using 2-sample Fisher's z test.

Results

The AS total score significantly correlated with PROMIS-SRI in the total sample and multiple measures of sleep disturbance in the PD group. The apathy subscales were each significantly correlated with sleep disturbance measures in the total sample, MC, and PD groups. The correlations between several sleep and apathy values were significantly stronger in the PD group than MC. When accounting for anxiety and depression most differences were no longer significant, only the PROMIS-SRI was significantly predictive of the behavioral apathy sub score.

Discussion

Evidence supports an association between sleep disturbances and apathy in individuals with PD. Specifically, insomnia severity, poor sleep quality, and daytime sleepiness were uniquely associated with apathy in this group. We did not find these associations in the matched control group. Anxiety and depression are likely involved in the association between sleep and apathy in PD. Experimental studies that manipulate or improve sleep may further elucidate the mechanisms underlying the association between sleep disturbance and apathy in PD.

The correlation between rapid eye movement sleep behavior disorder and the progress of Parkinson's disease: a systematic review and meta-analysis

Background

This meta-analysis was conducted to evaluate potential differences in symptoms between PD patients with or without RBD.

Methods

A systematic search was conducted in PubMed, Cochrane, Embase, and Web of Science databases (as of August 16, 2023), to identify relevant studies on PD and RBD. Statistical analysis was performed using Stata 15.0. Continuous variables were analyzed using the standardized mean difference (SMD) and 95% confidence interval (95% CI), while count data were assessed using the odds ratio (OR) and 95% CI as statistical effect sizes. Heterogeneity among all included studies was tested; for studies with low heterogeneity (I2 < 50%), a fixed-effects model was used to calculate statistical results. For studies with relatively high heterogeneity (I2 > 50%), a random-effects model was applied, followed by sensitivity and subgroup analyses to identify sources of heterogeneity.

Results

A total of 5,672 subjects were involved in this study. Compared to the NRBD group, the UPDRS-III score in the RBD group was significantly higher (SMD = 0.20, 95% CI: [0.11, 0.29], P < 0.001), and the Hoehn-Yahr score in the RBD group was also significantly higher (SMD = 0.29, 95% CI: [0.03, 0.55], P < 0.001). Patients with PD in the RBD group had more severe cognitive impairments than those in the NRBD group (SMD = -0.30, 95% CI: [-0.48, -0.11], P < 0.001). The incidence of hallucination in PD patients in the RBD group was 3.0 times that of the NRBD group (OR = 3.0, 95% CI: [2.15, 4.20], P = 0.110). PD patients in the RBD group also experienced more severe anxiety symptoms (SMD = 0.13, 95% CI: [-0.26, 0.51], P < 0.001), had higher scores in depression scales (SMD = 0.22, 95% CI: [0.02, 0.43], P < 0.001), and higher scores in sleep disorder scales than those in NRBD group (SMD = 0.10, 95% CI: [-0.11, 0.31], P < 0.001).

Conclusion

Results show PD patients with co-occurring RBD have more severe motor and non-motor symptoms likely due to overlapping affected regions in RBD and PD-related pathology, plus broader neurodegeneration seen in PD patients with RBD.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/#searchadvanced, identifier CRD42023476331.

Cortical Macro- and Microstructural Changes in Parkinson's Disease with Probable Rapid Eye Movement Sleep Behavior Disorder

BACKGROUND

Evidence regarding cortical atrophy patterns in Parkinson's disease (PD) with probable rapid eye movement sleep behavior disorder (RBD) (PD-pRBD) remains scarce. Cortical mean diffusivity (cMD), as a novel imaging biomarker highly sensitive to detecting cortical microstructural changes in different neurodegenerative diseases, has not been investigated in PD-pRBD yet.

OBJECTIVES

The aim was to investigate cMD as a sensitive measure to identify subtle cortical microstructural changes in PD-pRBD and its relationship with cortical thickness (CTh).

METHODS

Twenty-two PD-pRBD, 31 PD without probable RBD (PD-nonpRBD), and 28 healthy controls (HC) were assessed using 3D T1-weighted and diffusion-weighted magnetic resonance imaging on a 3-T scanner and neuropsychological testing. Measures of cortical brain changes were obtained through cMD and CTh. Two-class group comparisons of a general linear model were performed (P < 0.05). Cohen's d effect size for both approaches was computed.

RESULTS

PD-pRBD patients showed higher cMD than PD-nonpRBD patients in the left superior temporal, superior frontal, and precentral gyri, precuneus cortex, as well as in the right middle frontal and postcentral gyri and paracentral lobule (d > 0.8), whereas CTh did not detect significant differences. PD-pRBD patients also showed increased bilateral posterior cMD in comparison with HCs (d > 0.8). These results partially overlapped with CTh results (0.5 < d < 0.8). PD-nonpRBD patients showed no differences in cMD when compared with HCs but showed cortical thinning in the left fusiform gyrus and lateral occipital cortex bilaterally (d > 0.5).

CONCLUSIONS

cMD may be more sensitive than CTh displaying significant cortico-structural differences between PD subgroups, indicating this imaging biomarker's utility in studying early cortical changes in PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Reorganization of intrinsic functional connectivity in early-stage Parkinson's disease patients with probable REM sleep behavior disorder

REM sleep behavior disorder (RBD) symptoms in Parkinson's disease (PD) suggest both a clinically and pathologically malignant subtype. However, whether RBD symptoms are associated with alterations in the organization of whole-brain intrinsic functional networks in PD, especially at early disease stages, remains unclear. Here we use resting-state functional MRI, coupled with graph-theoretical approaches and network-based statistics analyses, and validated with large-scale network analyses, to characterize functional brain networks and their relationship with clinical measures in early PD patients with probable RBD (PD+pRBD), early PD patients without probable RBD (PD-pRBD) and healthy controls. Thirty-six PD+pRBD, 57 PD-pRBD and 71 healthy controls were included in the final analyses. The PD+pRBD group demonstrated decreased global efficiency (t = -2.036, P = 0.0432) compared to PD-pRBD, and decreased network efficiency, as well as comprehensively disrupted nodal efficiency and whole-brain networks (all eight networks, but especially in the sensorimotor, default mode and visual networks) compared to healthy controls. The PD-pRBD group showed decreased nodal degree in right ventral frontal cortex and more affected edges in the frontoparietal and ventral attention networks compared to healthy controls. Furthermore, the assortativity coefficient was negatively correlated with Montreal cognitive assessment scores in the PD+pRBD group (r = -0.365, P = 0.026, d = 0.154). The observation of altered whole-brain functional networks and its correlation with cognitive function in PD+pRBD suggest reorganization of the intrinsic functional connectivity to maintain the brain function in the early stage of the disease. Future longitudinal studies following these alterations along disease progression are warranted.

Alterations of Regional Homogeneity in Parkinson's Disease with Rapid Eye Movement Sleep Behavior Disorder

Objective

Patients with rapid eye movement (REM) sleep behavior disorder (RBD) in Parkinson's disease (PD-RBD) tend to have poor cognitive performance and faster cognitive deterioration, and the potential mechanism is still ambiguous. Therefore, this study aimed to detect the alterations in local brain function in PD-RBD.

Methods

Fifty patients, including 23 patients with PD-RBD and 27 patients with PD without RBD (PD-nRBD), and 26 healthy controls were enrolled. All subjects were subjected to one-night polysomnography and underwent resting-state functional magnetic resonance imaging (rs-fMRI). The fMRI images of the three groups were analyzed by regional homogeneity (ReHo) to observe the local neural activity. Correlations between altered ReHo values and chin electromyographic (EMG) density scores and cognitive scores in the PD subgroups were assessed.

Results

Compared with the patients with PD-nRBD, the patients with PD-RBD had higher ReHo values in the frontal cortex (the right superior frontal gyrus, the right middle frontal gyrus and the left medial superior frontal gyrus), the right caudate nucleus and the right anterior cingulate gyrus, and compared with the HCs, the patients with PD-RBD had lower ReHo values in the bilateral cuneus, the bilateral precuneus, the left inferior temporal gyrus and the left inferior occipital gyrus. For the patients with PD-RBD, the phasic chin EMG density scores were positively correlated with the ReHo values in the left medial superior frontal gyrus, and the tonic chin EMG density scores were positively correlated with the ReHo values in the right anterior cingulate gyrus.

Conclusion

This study indicates that increased ReHo in the frontal cortex, the caudate nucleus and the anterior cingulate gyrus may be linked with the abnormal motor behaviors during REM sleep and that decreased ReHo in the posterior regions may be related to the visuospatial-executive function in patients with PD-RBD.

Brain atrophy pattern in de novo Parkinson's disease with probable RBD associated with cognitive impairment

Rapid eye movement sleep behavior disorder (RBD) is associated with high likelihood of prodromal Parkinson’s disease (PD) and is common in de novo PD. It is associated with greater cognitive impairment and brain atrophy. However, the relation between structural brain characteristics and cognition remains poorly understood. We aimed to investigate subcortical and cortical atrophy in de novo PD with probable RBD (PD-pRBD) and to relate it with cognitive impairment. We analyzed volumetry, cortical thickness, and cognitive measures from 79 PD-pRBD patients, 126 PD without probable RBD patients (PD-non pRBD), and 69 controls from the Parkinson’s Progression Markers Initiative (PPMI). Regression models of cognition were tested using magnetic resonance imaging measures as predictors. We found lower left thalamus volume in PD-pRBD compared with PD-non pRBD. Compared with controls, PD-pRBD group showed atrophy in the bilateral putamen, left hippocampus, left amygdala, and thinning in the right superior temporal gyrus. Specific deep gray matter nuclei volumes were associated with impairment in global cognition, phonemic fluency, processing speed, and visuospatial function in PD-pRBD. In conclusion, cognitive impairment and gray matter atrophy are already present in de novo PD-pRBD. Thalamus, hippocampus, and putamen volumes were mainly associated with these cognitive deficits.

Disrupted functional connectivity in PD with probable RBD and its cognitive correlates

Recent studies associated rapid eye movement sleep behavior disorder (RBD) in Parkinson’s disease (PD) with severe cognitive impairment and brain atrophy. However, whole-brain functional connectivity has never been explored in this group of PD patients. In this study, whole-brain network-based statistics and graph-theoretical approaches were used to characterize resting-state interregional functional connectivity in PD with probable RBD (PD-pRBD) and its relationship with cognition. Our sample consisted of 30 healthy controls, 32 PD without probable RBD (PD-non pRBD), and 27 PD-pRBD. The PD-pRBD group showed reduced functional connectivity compared with controls mainly involving cingulate areas with temporal, frontal, insular, and thalamic regions (p < 0.001). Also, the PD-pRBD group showed reduced functional connectivity between right ventral posterior cingulate and left medial precuneus compared with PD-non pRBD (p < 0.05). We found increased normalized characteristic path length in PD-pRBD compared with PD-non pRBD. In the PD-pRBD group, mean connectivity strength from reduced connections correlated with visuoperceptual task and normalized characteristic path length correlated with processing speed and verbal memory tasks. This work demonstrates the existence of disrupted functional connectivity in PD-pRBD, together with abnormal network integrity, that supports its consideration as a severe PD subtype.

Sex differences in brain atrophy and cognitive impairment in Parkinson's disease patients with and without probable rapid eye movement sleep behavior disorder

Background

The presence of rapid eye movement sleep behavior disorder (RBD) contributes to increase cognitive impairment and brain atrophy in Parkinson’s disease (PD), but the impact of sex is unclear. We aimed to investigate sex differences in cognition and brain atrophy in PD patients with and without probable RBD (pRBD).

Methods

Magnetic resonance imaging and cognition data were obtained for 274 participants from the Parkinson's Progression Marker Initiative database: 79 PD with pRBD (PD-pRBD; male/female, 54/25), 126 PD without pRBD (PD-non pRBD; male/female, 73/53), and 69 healthy controls (male/female, 40/29). FreeSurfer was used to obtain volumetric and cortical thickness data.

Results

Males showed greater global cortical and subcortical gray matter atrophy than females in the PD-pRBD group. Significant group-by-sex interactions were found in the pallidum. Structures showing a within-group sex effect in the deep gray matter differed, with significant volume reductions for males in one structure in in PD-non pRBD (brainstem), and three in PD-pRBD (caudate, pallidum and brainstem). Significant group-by-sex interactions were found in Montreal Cognitive Assessment (MoCA) and Symbol Digits Modalities Test (SDMT). Males performed worse than females in MoCA, phonemic fluency and SDMT in the PD-pRBD group.

Conclusion

Male sex is related to increased cognitive impairment and subcortical atrophy in de novo PD-pRBD. Accordingly, we suggest that sex differences are relevant and should be considered in future clinical and translational research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10728-x.

Development and Validation of a Prognostic Model for Cognitive Impairment in Parkinson's Disease With REM Sleep Behavior Disorder

The presentation and progression of Parkinson’s disease (PD) are not uniform, but the presence of rapid eye movement sleep behavior disorder (RBD) in PD patients may indicate a worse prognosis than isolated PD. Increasing evidence suggests that patients with comorbid PD and RBD (PD-RBD) are more likely to develop cognitive impairment (CI) than those with isolated PD; however, the predictors of CI in PD-RBD patients are not well understood. This study aimed to develop a prognostic model for predicting mild cognitive impairment (MCI) in PD-RBD patients. The data of PD-RBD patients were extracted from the Parkinson’s Progression Markers Initiative study (PPMI), and the sample was randomly divided into a training set (n = 96) and a validation set (n = 24). PD-MCI as defined by the level II Movement Disorder Society (MDS) diagnostic criteria was the outcome of interest. The demographic features, clinical assessments, dopamine transporter (DAT) imaging data, cerebrospinal fluid (CSF) analyses and genetic data of PD patients were considered candidate predictors. We found that performance on the University of Pennsylvania Smell Identification Test (UPSIT), the mean signal and asymmetry index of the putamen on DAT imaging, p-tau/α-syn and p-tau in CSF, and rs55785911 genotype were predictors of PD-MCI in PD-RBD patients. A C-index of 0.81 was obtained with this model, and a C-index of 0.73 was obtained in the validation set. Favorable results of calibrations and decision curve analysis demonstrated the efficacy and feasibility of this model. In conclusion, we developed a prognostic model for predicting MCI in PD-RBD patients; the model displayed good discrimination and calibration and may be a convenient tool for clinical application. Larger samples and external validation sets are needed to validate this model.

REM Sleep Behavior Disorder in Parkinson's Disease: Change in Cognitive, Psychiatric, and Functional Outcomes from Baseline to 16-47-Month Follow-Up

OBJECTIVE

Rapid Eye Movement Sleep Behavior Disorder (RBD) is common in Parkinson's Disease (PD) and is associated with cognitive impairment; however, the majority of the evidence on the impact of RBD on multidomain cognitive batteries in PD is cross-sectional. This study evaluated the longitudinal impact of probable RBD (pRBD) on cognitive, psychiatric, and functional outcomes in people with PD.

METHOD

Case-control study. A total of 65 people with PD completed the study protocol at baseline and 16-to-47-month follow-up. Participants were classified as pRBD+ (n = 25) or pRBD- (n = 40) based on an established cutoff of 6 on the RBD Sleep Questionnaire (RBDSQ). Participants also completed a) comprehensive cognitive testing, b) self-report measures of depression, anxiety, and apathy, and c) performance-based and other-report forms of instrumental activities of daily living.

RESULTS

Baseline mean age was 67.8 (SD = 8.1; range = 45-86) and baseline mean years of education was 16.4 (SD = 2.1; range = 12-20). The two groups did not differ on measured demographic characteristics. Baseline mean T-scores for cognitive tests were in the average range (46-55). Hierarchical linear models tested group differences in cognitive and functional decline from baseline to follow-up, controlling for appropriate demographic and psychiatric variables. Compared to the pRBD- group, pRBD+ participants showed greater decline in attention/working memory (r = -0.31; p = 0.01) and UPSA financial skills (r = -0.31; p = 0.01). No other group differences approached significance.

CONCLUSIONS

RBD may differentially affect attention/working memory and financial abilities in PD. Results underscore the importance of regular RBD screening in older adults with PD in order to triage symptomatic patients to appropriate cognitive and medical interventions.

Sleep Disorders and Cognitive Dysfunctions in Parkinson's Disease: A Meta-Analytic Study

A relationship between sleep disorders and cognitive dysfunctions was reported in Parkinson's Disease (PD), however, some studies did not confirm the link. A meta-analytic study was performed to investigate the relationship between sleep disorders and cognitive dysfunctions, and to clarify the evolution of cognitive status in PD patients with sleep disorders.The systematic literature search was performed up to November 2020 using PubMed, Scopus, and PsycINFO databases. We included studies published in peer-reviewed journals in English providing results about neuropsychological comparison between patients with or without sleep disorders. Meta-analysis on cross-sectional data included 54 studies for REM Sleep Behavior Disorder (RBD), 22 for Excessive Daytime Sleepiness (EDS), 7 for Obstructive Sleep Apnea (OSA), 13 for Restless Legs Syndrome (RLS), and 5 for insomnia, the meta-analysis on longitudinal data included 7 studies.RBD was related to deficits of global cognitive functioning, memory, executive functions, attention/working memory, language, and visuospatial abilities. EDS was associated with deficits of global cognitive functioning and attention and working memory abilities, whereas RLS and OSA were related to global cognitive dysfunction. Moreover, we revealed that PD patients with RBD and those with EDS performed worse than PD patients without sleep disorders at follow-up rather than baseline evaluation. Our results suggest that sleep disorders are associated with cognitive deficits supporting indirectly that these, especially the REM Sleep Behavior Disorder, reflect abnormalities of frontal networks and posterior cortical areas. Sleep disorders in patients with PD seem to also increase the risk for long-term cognitive decline.

Exploring the Predictors of Rapid Eye Movement Sleep Behavior Disorder for Parkinson's Disease Patients Using Classifier Ensemble

The rapid eye movement sleep behavior disorder (RBD) of Parkinson's disease (PD) patients can be improved with medications such as donepezil as long as it is diagnosed with a thorough medical examination, since identifying a high-risk group of RBD is a critical issue to treat PD. This study develops a model for predicting the high-risk groups of RBD using random forest (RF) and provides baseline information for selecting subjects for polysomnography. Subjects consisted of 350 PD patients (Parkinson's disease with normal cognition (PD-NC) = 48; Parkinson's disease with mild cognitive impairment (PD-MCI) = 199; Parkinson's disease dementia (PDD) = 103) aged 60 years and older. This study compares the prediction performance of RF, discriminant analysis, classification and regression tree (CART), radial basis function (RBF) neural network, and logistic regression model to select a final model with the best model performance and presents the variable importance of the final model's variable. As a result of analysis, the sensitivity of RF (79%) was superior to other models (discriminant analysis = 14%, CART = 32%, RBF neural network = 25%, and logistic regression = 51%). It was confirmed that age, the motor score of Untitled Parkinson's Disease Rating (UPDRS), the total score of UPDRS, the age when a subject was diagnosed with PD first time, the Korean Mini Mental State Examination, and Korean Instrumental Activities of Daily Living, were major variables with high weight for predicting RBD. Among them, age was the most important factor. The model for predicting Parkinson's disease RBD developed in this study will contribute to the screening of patients who should receive a video-polysomnography.

Application of Machine Learning Technique to Distinguish Parkinson's Disease Dementia and Alzheimer's Dementia: Predictive Power of Parkinson's Disease-Related Non-Motor Symptoms and Neuropsychological Profile

In order to develop a predictive model that can distinguish Parkinson's disease dementia (PDD) from other dementia types, such as Alzheimer's dementia (AD), it is necessary to evaluate and identify the predictive accuracy of the cognitive profile while considering the non-motor symptoms, such as depression and rapid eye movement (REM) sleep behavior disorders. This study compared Parkinson's disease (PD)'s non-motor symptoms and the diagnostic predictive power of cognitive profiles that distinguish AD and PD using machine learning. This study analyzed 118 patients with AD and 110 patients with PDD, and all subjects were 60 years or older. In order to develop the PDD prediction model, the dataset was divided into training data (70%) and test data (30%). The prediction accuracy of the model was calculated by the recognition rate. The results of this study show that Parkinson-related non-motor symptoms, such as REM sleep behavior disorders, and cognitive screening tests, such as Korean version of Montreal Cognitive Assessment, were highly accurate factors for predicting PDD. It is required to develop customized screening tests that can detect PDD in the early stage based on these results. Furthermore, it is believed that including biomarkers such as brain images or cerebrospinal fluid as input variables will be more useful for developing PDD prediction models in the future.