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

Anticipating Tomorrow: Tailoring Parkinson's Symptomatic Therapy Using Predictors of Outcome

BACKGROUND

Although research into Parkinson's disease (PD) subtypes and outcome predictions has continued to advance, recommendations for using outcome prediction to guide current treatment decisions remain sparse.

OBJECTIVES

To provide expert opinion-based recommendations for individually tailored PD symptomatic treatment based on knowledge of risk prediction and subtypes.

METHODS

Using a modified Delphi approach, members of the Movement Disorders Society (MDS) Task Force on PD subtypes generated a series of general recommendations around the question: "Using what you know about genetic/biological/clinical subtypes (or any individual-level predictors of outcome), what advice would you give for selecting symptomatic treatments for an individual patient now, based on what their subtype or individual characteristics predict about their future disease course?" After four iterations and revisions, those recommendations with over 75% endorsement were adopted.

RESULTS

A total of 19 recommendations were endorsed by a group of 13 panelists. The recommendations primarily centered around two themes: (1) incorporating future risk of cognitive impairment into current treatment plans; and (2) identifying future symptom clusters that might be forestalled with a single medication.

CONCLUSIONS

These recommendations provide clinicians with a framework for integrating future outcomes into patient-specific treatment choices. They are not prescriptive guidelines, but adaptable suggestions, which should be tailored to each individual. They are to be considered as a first step of a process that will continue to evolve as additional stakeholders provide new insights and as new information becomes available. As individualized risk prediction advances, the path to better tailored treatment regimens will become clearer.

Too little or too much nocturnal movements in Parkinson's disease: A practical guide to managing the unseen

Nocturnal and sleep-related motor disorders in people with Parkinson's disease (PD) have a wide spectrum of manifestations and present a complex clinical picture. Problems can arise due to impaired movement ability (hypokinesias), e.g. nocturnal hypokinesia or early-morning akinesia, or to excessive movement (hyperkinesias), e.g. end-of-the-day dyskinesia, parasomnias, periodic limb movement during sleep and restless legs syndrome. These disorders can have a significant negative impact on the sleep, daytime functional ability, and overall quality of life of individuals with PD and their carers. The debilitating motor issues are often accompanied by a combination of non-motor symptoms, including pain and cramping, which add to the overall burden. Importantly, nocturnal motor disorders encompass a broader timeline than just the period of sleep, often starting in the evening, as well as occurring throughout the night and on awakening, and are not just limited to problems of insomnia or sleep fragmentation. Diagnosis can be challenging as, in many cases, the 'gold standard' assessment method is video polysomnography, which may not be available in all settings. Various validated questionnaires are available to support evaluation, and alternative approaches, using wearable sensors and digital technology, are now being developed to facilitate early diagnosis and monitoring. This review sets out the parameters of what can be considered normal nocturnal movement and describes the clinical manifestations, usual clinical or objective assessment methods, and evidence for optimal management strategies for the common nocturnal motor disorders that neurologists will encounter in people with PD in their clinical practice.

Online cognitive monitoring technology for people with Parkinson's disease and REM sleep behavioural disorder

Automated online cognitive assessments are set to revolutionise clinical research and healthcare. However, their applicability for Parkinson's Disease (PD) and REM Sleep Behavioural Disorder (RBD), a strong PD precursor, is underexplored. Here, we developed an online battery to measure early cognitive changes in PD and RBD. Evaluating 19 candidate tasks showed significant global accuracy deficits in PD (0.65 SD, p = 0.003) and RBD (0.45 SD, p = 0.027), driven by memory, language, attention and executive underperformance, and global reaction time deficits in PD (0.61 SD, p = 0.001). We identified a brief 20-min battery that had sensitivity to deficits across these cognitive domains while being robust to the device used. This battery was more sensitive to early-stage and prodromal deficits than the supervised neuropsychological scales. It also diverged from those scales, capturing additional cognitive factors sensitive to PD and RBD. This technology offers an economical and scalable method for assessing these populations that can complement standard supervised practices.

Neurocognitive Impairment and Social Cognition in Parkinson's Disease Patients

In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.

Lactiplantibacillus (Lactobacillus) plantarum as a Complementary Treatment to Improve Symptomatology in Neurodegenerative Disease: A Systematic Review of Open Access Literature

This systematic review addresses the use of Lactiplantibacillus (Lactobacillus) plantarum in the symptomatological intervention of neurodegenerative disease. The existence of gut microbiota dysbiosis has been associated with systemic inflammatory processes present in neurodegenerative disease, creating the opportunity for new treatment strategies. This involves modifying the strains that constitute the gut microbiota to enhance synaptic function through the gut-brain axis. Recent studies have evaluated the beneficial effects of the use of Lactiplantibacillus plantarum on motor and cognitive symptomatology, alone or in combination. This systematic review includes 20 research articles (n = 3 in human and n = 17 in animal models). The main result of this research was that the use of Lactiplantibacillus plantarum alone or in combination produced improvements in symptomatology related to neurodegenerative disease. However, one of the studies included reported negative effects after the administration of Lactiplantibacillus plantarum. This systematic review provides current and relevant information about the use of this probiotic in pathologies that present neurodegenerative processes such as Alzheimer's disease, Parkinson's disease and Multiple Sclerosis.

Relationship of Sleep Disorder with Neurodegenerative and Psychiatric Diseases: An Updated Review

Sleep disorders affect many people worldwide and can accompany neurodegenerative and psychiatric diseases. Sleep may be altered before the clinical manifestations of some of these diseases appear. Moreover, some sleep disorders affect the physiological organization and function of the brain by influencing gene expression, accelerating the accumulation of abnormal proteins, interfering with the clearance of abnormal proteins, or altering the levels of related hormones and neurotransmitters, which can cause or may be associated with the development of neurodegenerative and psychiatric diseases. However, the detailed mechanisms of these effects are unclear. This review mainly focuses on the relationship between and mechanisms of action of sleep in Alzheimer's disease, depression, and anxiety, as well as the relationships between sleep and Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. This summary of current research hotspots may provide researchers with better clues and ideas to develop treatment solutions for neurodegenerative and psychiatric diseases associated with sleep disorders.

Sleep disorders cause Parkinson's disease or the reverse is true: Good GABA good night

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative brain disease due to degeneration of dopaminergic neurons (DNs) presented with motor and non-motor symptoms. PD symptoms are developed in response to the disturbance of diverse neurotransmitters including γ-aminobutyric acid (GABA). GABA has a neuroprotective effect against PD neuropathology by protecting DNs in the substantia nigra pars compacta (SNpc). It has been shown that the degeneration of GABAergic neurons is linked with the degeneration of DNs and the progression of motor and non-motor PD symptoms. GABA neurotransmission is a necessary pathway for normal sleep patterns, thus deregulation of GABAergic neurotransmission in PD could be the potential cause of sleep disorders in PD.

AIM

Sleep disorders affect GABA neurotransmission leading to memory and cognitive dysfunction in PD. For example, insomnia and short sleep duration are associated with a reduction of brain GABA levels. Moreover, PD-related disorders including rigidity and nocturia influence sleep patterns leading to fragmented sleep which may also affect PD neuropathology. However, the mechanistic role of GABA in PD neuropathology regarding motor and non-motor symptoms is not fully elucidated. Therefore, this narrative review aims to clarify the mechanistic role of GABA in PD neuropathology mainly in sleep disorders, and how good GABA improves PD. In addition, this review of published articles tries to elucidate how sleep disorders such as insomnia and REM sleep behavior disorder (RBD) affect PD neuropathology and severity. The present review has many limitations including the paucity of prospective studies and most findings are taken from observational and preclinical studies. GABA involvement in the pathogenesis of PD has been recently discussed by recent studies. Therefore, future prospective studies regarding the use of GABA agonists in the management of PD are suggested to observe their distinct effects on motor and non-motor symptoms.

CONCLUSION

There is a bidirectional relationship between the pathogenesis of PD and sleep disorders which might be due to GABA deregulation.

Prevalence and clinical aspects of obstructive sleep apnea in Parkinson disease: A meta-analysis

BACKGROUND AND PURPOSE

Obstructive sleep apnea (OSA) frequently occurs in Parkinson Disease (PD), probably caused by upper airway dysfunctions or shared pathogenetic mechanisms. OSA may precede PD diagnosis or worsen throughout its course, but its relationship with clinical features and dopaminergic medication remains unclear. This meta-analysis aimed to provide a reliable estimate of OSA prevalence in the PD population (PD-OSA) and to clarify its clinical associated factors to help clinicians in understanding the underlying pathophysiological mechanisms.

METHODS

A systematic literature search was performed up to April 2023 using the PubMed, Scopus, and PsycINFO databases. Articles were included if they provided data on PD patients with and without OSA. Pooled prevalence for PD-OSA was calculated using the proportions of PD participants diagnosed with OSA. Demographic and clinical features associated with PD-OSA were explored by comparing PD patients with and without OSA.

RESULTS

Seventeen studies were included in the meta-analysis. Pooled OSA prevalence was 45% of a total sample of 1448 PD patients and was associated with older age, male sex, higher body mass index (BMI), more severe motor disturbances and periodic limb movements, reduced risk of rapid eye movement sleep behavior disorder, intake of dopamine agonists, and worse excessive daytime sleepiness. No relationship emerged with cognitive functioning and neuropsychiatric manifestations.

CONCLUSIONS

OSA affects nearly half of PD patients as a secondary outcome of predisposing factors such as older age and higher BMI in addition to PD-related motor impairment. Future studies should focus on determining the impact of both clinical features and dopaminergic medication on the development of PD-OSA.

Sleep Deficits Inter-Link Lower Basal Forebrain-Posterior Cingulate Connectivity and Perceived Stress and Anxiety Bidirectionally in Young Men

BACKGROUND

The basal nucleus of Meynert (BNM), a primary source of cholinergic projections to the cortex, plays key roles in regulating the sleep-wake cycle and attention. Sleep deficit is associated with impairment in cognitive and emotional functions. However, whether or how cholinergic circuit, sleep, and cognitive/emotional dysfunction are inter-related remains unclear.

METHODS

We curated the Human Connectome Project data and explored BNM resting state functional connectivities (rsFC) in relation to sleep deficit, based on the Pittsburgh Sleep Quality Index (PSQI), cognitive performance, and subjective reports of emotional states in 687 young adults (342 women). Imaging data were processed with published routines and evaluated at a corrected threshold. We assessed the correlation between BNM rsFC, PSQI, and clinical measurements with Pearson regressions and their inter-relationships with mediation analyses.

RESULTS

In whole-brain regressions with age and alcohol use severity as covariates, men showed lower BNM rsFC with the posterior cingulate cortex (PCC) in correlation with PSQI score. No clusters were identified in women at the same threshold. Both BNM-PCC rsFC and PSQI score were significantly correlated with anxiety, perceived stress, and neuroticism scores in men. Moreover, mediation analyses showed that PSQI score mediated the relationship between BNM-PCC rsFC and these measures of negative emotions bidirectionally in men.

CONCLUSIONS

Sleep deficit is associated with negative emotions and lower BNM rsFC with the PCC. Negative emotional states and BNM-PCC rsFC are bidirectionally related through poor sleep quality. These findings are specific to men, suggesting potential sex differences in the neural circuits regulating sleep and emotional states.

Association between multiple metals exposure and sleep disorders in a Chinese population: A mixture-based approach

OBJECTIVE

Previous studies have suggested a possible association between metals and sleep disorders. This study aimed to explore the association between Zn, Cu, Se, Mg and Ca and sleep disorders in single and multi-metal co-exposure models.

METHODS

Logistic regression models, restricted cubic spline model (RCS), Quantile g computation (Q-gcomp), Weighted Quantile Sum (WQS), and Bayesian kernel machine regression (BKMR) models were used to investigate the association between metal levels and sleep disorders.

RESULTS

Logistic regression showed that in the total population, the second, third, and fourth quartile Zn concentration exhibited a lower risk of sleep disorders compared with the first quartile, with odds ratios (ORs) of 0.783, 0.711, and 0.704, respectively. Compared with Zn/Cu and Zn/Se in the first quartile, the third and fourth quartiles showed a lower risk of sleep disorders. In the 30-59 years group, the risk of sleep disorders was 0.699 times greater for the fourth quartile Mg concentration than that for the first quartile. The risk of sleep disorders in Mg/Ca concentration in the third quartile was 0.737 times higher than in the first quartile. Q-gcomp, WQS, and BKMR model analysis showed the negative overall effect of mixtures of the five metals on sleep disorders, with Zn being the largest contributor.

CONCLUSION

Our study showed that plasma Zn, Mg, Zn/Cu, Zn/Se, and Mg/Ca reduced the risk of sleep disorders, and the combined effect of multiple metals was negatively associated with the risk of sleep disorders, with Zn being the largest contributor to this relationship.

Cognitive reserve moderates the relationship between sleep difficulties and executive functions in patients with Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor disturbances as well as non-motor symptoms, such as sleep and cognitive difficulties. Recent evidence has shown that, in patients with PD, sleep disturbances selectively correlate with specific cognitive functions, such as non-verbal reasoning, attention and executive functions, and language abilities. The present study aimed to test the hypothesis of Cognitive Reserve (CR) as a potential moderator in the relationship between sleep difficulties and cognitive performance in PD patients. Participants were asked to attend two sessions in which they were assessed for cognitive functions and reserve, as well as subjective sleep quality, excessive sleepiness, and symptoms of REM sleep behavior disorder (RBD) and insomnia. The results of preliminary correlations confirmed the presence of a significant negative correlation between sleep quality and cognitive performance. The results of the moderation analysis revealed a significant role for CR as a moderator of the negative association between RBD and executive functions. Specifically, a significant negative correlation was observed between sleep difficulties and executive performance only in patients with low CR. Overall, our results suggest that patients with PD with low to average CR levels could be considered to be more at risk of developing cognitive deficits in the presence of sleep difficulties.

Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson's disease

Introduction

Cognitive decline is common in Parkinson's disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials.

Methods

Data were from the Parkinson's Progression Markers Initiative de novo cohort. Baseline scores were calculated for Lifestyle for Brain Health (LIBRA) and the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) per prior literature and preliminary Parkinson's disease Risk Estimator for Decline In Cognition Tool (pPREDICT) by attributing a point for fourteen posited risk factors. Baseline and 5-year follow-up composite cognitive scores (CCSs) were calculated from a neuropsychological battery and used to define cognitive decliners (PD-decline) versus maintainers (PD-maintain).

Results

The PD-decline group (n = 44) had higher LIBRA (6.76 ± 0.57, p < 0.05), MoPaRDS (2.45 ± 1.41, p < 0.05) and pPREDICT (4.52 ± 1.66, p < 0.05) scores compared to the PD-maintain group (n = 263; LIBRA 4.98 ± 0.20, MoPaRDS 1.68 ± 1.16, pPREDICT 3.38 ± 1.69). Area-under-the-curve (AUC) for LIBRA was 0.64 (95% confidence interval [CI], 0.55-0.73), MoPaRDS was 0.66 (95% CI, 0.58-0.75) and for pPREDICT was 0.68 (95% CI, 0.61-0.76). In linear regression analyses, LIBRA (p < 0.05), MoPaRDS (p < 0.05) and pPREDICT (p < 0.05) predicted change in CCS. Only age stratified by sex (p < 0.05) contributed significantly to the model for LIBRA. Age and presence of hallucinations (p < 0.05) contributed significantly to the model for MoPaRDS. Male sex, older age, excessive daytime sleepiness, and moderate-severe motor symptoms (all p < 0.05) contributed significantly to the model for pPREDICT.

Conclusion

Although MoPaRDS is a PD-specific tool for predicting cognitive decline relying on only clinical features, it does not focus on potentially modifiable risk factors. LIBRA does focus on potentially modifiable risk factors and is associated with prediction of all-cause dementia in some populations, but pPREDICT potentially demonstrates improved performance in cognitive decline risk calculation in individuals with PD and may identify actionable risk factors. As pPREDICT incorporates multiple potentially modifiable risk factors that can be obtained easily in the clinical setting, it is a first step in developing an easily assessable tool for a personalized approach to reduce dementia risk in people with PD.

Machine learning-based prediction of longitudinal cognitive decline in early Parkinson's disease using multimodal features

Patients with Parkinson's Disease (PD) often suffer from cognitive decline. Accurate prediction of cognitive decline is essential for early treatment of at-risk patients. The aim of this study was to develop and evaluate a multimodal machine learning model for the prediction of continuous cognitive decline in patients with early PD. We included 213 PD patients from the Parkinson's Progression Markers Initiative (PPMI) database. Machine learning was used to predict change in Montreal Cognitive Assessment (MoCA) score using the difference between baseline and 4-years follow-up data as outcome. Input features were categorized into four sets: clinical test scores, cerebrospinal fluid (CSF) biomarkers, brain volumes, and genetic variants. All combinations of input feature sets were added to a basic model, which consisted of demographics and baseline cognition. An iterative scheme using RReliefF-based feature ranking and support vector regression in combination with tenfold cross validation was used to determine the optimal number of predictive features and to evaluate model performance for each combination of input feature sets. Our best performing model consisted of a combination of the basic model, clinical test scores and CSF-based biomarkers. This model had 12 features, which included baseline cognition, CSF phosphorylated tau, CSF total tau, CSF amyloid-beta1-42, geriatric depression scale (GDS) scores, and anxiety scores. Interestingly, many of the predictive features in our model have previously been associated with Alzheimer's disease, showing the importance of assessing Alzheimer's disease pathology in patients with Parkinson's disease.

A high propensity for excessive daytime sleepiness independent of lifestyle is associated with cognitive performance in community-dwelling older adults

Objective

The relationship between excessive daytime sleepiness (EDS) and cognitive performance of older adults remains unclear, especially when a healthy lifestyle is considered. The study aimed to explore the association between EDS in passive and active situations and general cognitive function among community-dwelling older adults.

Methods

Two hundred and seventy-one older adults aged 60 and above were recruited from the community cohort in Shangrao. All study participants were free of depression and dementia. The Chinese version of the Epworth Sleepiness Scale (CESS) was used to evaluate EDS. Using the item scores of CESS, the presence of EDS among all study participants were grouped as non-EDS, passive situation-related EDS (PSR-EDS), active situation-related EDS (ASR-EDS), and high sleep propensity (HSP). The Hong Kong Brief Cognitive Test (HKBC) was used to assess cognitive function. Chinese healthy lifestyle metrics were scored based on AHA Life Simple-7. The multivariate logistic regression model was used to estimate the association between the presence of EDS and cognitive function.

Results

The PSR-EDS (n = 29, 20.8 ± 5.3) and the HSP groups (n = 21, 19.8 ± 4.8) scored lower with HKBC than in the non-EDS group (n = 213, 23.2 ± 4.9). The subdomain performance of language in the HSP group was poorer than in the non-EDS group (ps < 0.05). Relative to non-EDS, HSP (OR = 3.848, 95% CI = 1.398-10.591) was associated with an increased risk of poor cognitive performance after adjusting age, sex, education, and healthy lifestyle metrics.

Conclusion

High propensity for excessive daytime sleepiness, irrespective of lifestyle, is associated with poorer cognitive performance among community-dwelling older adults. The findings may provide empirical evidence to support sleepiness intervention for reducing the risk of cognitive decline.

Role of astrocytes in sleep deprivation: accomplices, resisters, or bystanders?

Sleep plays an essential role in all studied animals with a nervous system. However, sleep deprivation leads to various pathological changes and neurobehavioral problems. Astrocytes are the most abundant cells in the brain and are involved in various important functions, including neurotransmitter and ion homeostasis, synaptic and neuronal modulation, and blood-brain barrier maintenance; furthermore, they are associated with numerous neurodegenerative diseases, pain, and mood disorders. Moreover, astrocytes are increasingly being recognized as vital contributors to the regulation of sleep-wake cycles, both locally and in specific neural circuits. In this review, we begin by describing the role of astrocytes in regulating sleep and circadian rhythms, focusing on: (i) neuronal activity; (ii) metabolism; (iii) the glymphatic system; (iv) neuroinflammation; and (v) astrocyte-microglia cross-talk. Moreover, we review the role of astrocytes in sleep deprivation comorbidities and sleep deprivation-related brain disorders. Finally, we discuss potential interventions targeting astrocytes to prevent or treat sleep deprivation-related brain disorders. Pursuing these questions would pave the way for a deeper understanding of the cellular and neural mechanisms underlying sleep deprivation-comorbid brain disorders.

Cognitive heterogeneity in Parkinson's disease: A mechanistic view

Cognitive impairment occurs in most individuals with Parkinson's disease (PD), exacting a high toll on patients, their caregivers, and the healthcare system. In this review, we begin by summarizing the current clinical landscape surrounding cognition in PD. We then discuss how cognitive impairment and dementia may develop in PD based on the spread of the pathological protein alpha-synuclein (aSyn) from neurons in brainstem regions to those in the cortical regions of the brain responsible for higher cognitive functions, as first proposed in the Braak hypothesis. We appraise the Braak hypothesis from molecular (conformations of aSyn), cell biological (cell-to-cell spread of pathological aSyn), and organ-level (region-to-region spread of aSyn pathology at the whole brain level) viewpoints. Finally, we argue that individual host factors may be the most poorly understood aspect of this pathological process, accounting for substantial heterogeneity in the pattern and pace of cognitive decline in PD.

Sleep disorders affect cognitive function in adults: an overview of systematic reviews and meta-analyses

Sleep disorders frequently result in poor memory, attention deficits, as well as a worse prognosis for neurodegenerative changes, such as Alzheimer's disease. The purpose of this study is to investigate the impact of sleep disorders on cognition. We screened four databases for all meta-analyses and systematic reviews from the establishment through March 2022. We have carried out quality evaluation and review the eligible systematic reviews. Evidence grading and quality assessment were performed on 22 eligible articles. Sleep deprivation primarily affects simple attention, complex attention, and working memory in cognition and alertness. The moderate-to-high-quality evidence proves optimal sleep time as 7-8 h. Sleep time outside this range increases the risk of impaired executive function, non-verbal memory, and working memory. Sleep-related breathing disorders is more likely to cause mild cognitive impairment and affects several cognitive domains. In older adults, insomnia primarily affects working memory, episodic memory, inhibitory control, cognitive flexibility, problem-solving, operational ability, perceptual function, alertness, and complex attention, and maintaining sensitivity. Sleep disturbances significantly impair cognitive function, and early detection and intervention may be critical steps in reducing poor prognosis. A simple neuropsychological memory test could be used to screen people with sleep disorders for cognitive impairment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00439-9.

The assessment of executive functions to test the integrity of the nigrostriatal network: A pilot study

Background

Parkinson’s disease (PD) is a chronic neurodegenerative disorder characterized by motor and non-motor symptoms. The latter mainly include affective, sleep, and cognitive deficits. Non-demented PD patients often demonstrate impairments in several executive domains following neuropsychological evaluation. The current pilot study aims at assessing the discriminatory power of the Frontal Assessment Battery-15 (FAB15) in differentiating (i) non-demented PD patients and healthy controls and (ii) PD patients with more and less pronounced motor symptoms.

Methods

Thirty-nine non-demented early-stage PD patients in the “on” dopamine state (26 females, mean age = 64.51 years, SD = 6.47, mean disease duration = 5.49 years, SD = 2.28) and 39 healthy participants (24 females, mean age = 62.60 years, SD = 5.51) were included in the study. All participants completed the FAB15. Motor symptoms of PD patients were quantified via the Unified Parkinson’s Disease Rating Scale-Part III (UPDRS-Part III) and Hoehn and Yahr staging scale (H&amp;Y).

Results

The FAB15 score, adjusted according to normative data for sex, age, and education, proved to be sufficiently able to discriminate PD patients from healthy controls (AUC = 0.69 [95% CI 0.60–0.75], SE = 0.06, p = 0.04, optimal cutoff = 11.29). Conversely, the battery lacked sufficient discriminative capability to differentiate PD patients based on the severity of motor symptoms.

Conclusion

The FAB15 may be a valid tool for distinguishing PD patients from healthy controls. However, it might be less sensitive in identifying clinical phenotypes characterized by visuospatial impairments resulting from posteroparietal and/or temporal dysfunctions. In line with previous evidence, the battery demonstrated to be not expendable in the clinical practice for monitoring the severity of PD-related motor symptoms.

Sleep and wakefulness disturbances in Parkinson's disease: A meta-analysis on prevalence and clinical aspects of REM sleep behavior disorder, excessive daytime sleepiness and insomnia

Sleep disorders (SDs) are common non-motor symptoms of Parkinson's disease (PD) with wide variability in their prevalence rates. The etiology of SDs in PD is multifactorial because the degenerative processes underlying the disease and their interaction with drugs and clinical features may promote REM sleep behavior disorder (RBD), excessive daytime sleepiness (EDS) and insomnia. Therefore, we designed a meta-analytic study to provide a reliable estimate of the prevalence and associated clinical and neuropsychiatric aspects of SDs in PD. A systematic literature search was performed up to February 2022. Pooled RBD prevalence was 46%, and its occurrence was associated with older age, lower education, longer disease duration, higher levodopa equivalent daily dose (LEDD), worse motor and autonomic manifestations, poorer quality of life and autonomy, and more severe neuropsychiatric symptoms. The pooled prevalence of EDS was 35% and was associated with older age, longer disease duration, worse motor and autonomic symptoms, higher LEDD, reduced autonomy, and more severe neuropsychiatric symptoms. Insomnia was reported in 44% of PD patients and was related to longer disease duration, higher LEDD, and more severe depression. SDs are associated with a more severe PD clinical phenotype; further studies should explore the pathophysiological mechanisms underlying SDs and develop targeted therapeutic strategies.

Effects of repetitive transcranial magnetic stimulation over right dorsolateral prefrontal cortex on excessive daytime sleepiness in patients with Parkinson's disease

BACKGROUND

Excessive daytime sleepiness (EDS) is a common sleep disorder in Parkinson's disease (PD), which seriously affects patients' quality of life. Repetitive transcranial magnetic stimulation (rTMS) can be used as an add-on therapy to a variety of non-motor symptoms of PD. However, little is known on the treatment of EDS in PD patients.

OBJECTIVE

To explore the effects of low frequency rTMS over right dorsolateral prefrontal cortex (DLPFC) in the treatment of EDS in PD.

METHODS

We conducted a sham-controlled, parallel study including 25 individuals of PD with possible EDS based on Epworth Sleepiness Scale (ESS ≥8 points) and randomly divided them into active group (n = 15) and sham group (n = 10). 1 Hz rTMS was administrated over right DLPFC for 10 consecutive days. In the active group, we further classified them into responsive group and non-responsive group according to change of ESS score in comparison with baseline. Clinical assessments on motor and non-motor symptoms were completed at baseline, at the end of treatment and 1 month after treatment.

RESULTS

Compared to baseline, active group showed significant improvement on ESS score 10 days and 1 month after treatment (P < 0.05 for both). The percentage change of ESS score was positively related to disease duration during follow-up. No significant changes were observed on ESS score change in the sham group. Further analysis of individuals in the active group showed that, relative to those with non-response to rTMS, individuals with therapeutic response exhibited longer disease duration and lower baseline levodopa equivalent dose.

CONCLUSION

Low frequency rTMS over right DLPFC may improve symptoms of EDS in PD.

Mucosal Immunity and the Gut-Microbiota-Brain-Axis in Neuroimmune Disease

Recent advances in next-generation sequencing (NGS) technologies have opened the door to a wellspring of information regarding the composition of the gut microbiota. Leveraging NGS technology, early metagenomic studies revealed that several diseases, such as Alzheimer's disease, Parkinson's disease, autism, and myalgic encephalomyelitis, are characterized by alterations in the diversity of gut-associated microbes. More recently, interest has shifted toward understanding how these microbes impact their host, with a special emphasis on their interactions with the brain. Such interactions typically occur either systemically, through the production of small molecules in the gut that are released into circulation, or through signaling via the vagus nerves which directly connect the enteric nervous system to the central nervous system. Collectively, this system of communication is now commonly referred to as the gut-microbiota-brain axis. While equally important, little attention has focused on the causes of the alterations in the composition of gut microbiota. Although several factors can contribute, mucosal immunity plays a significant role in shaping the microbiota in both healthy individuals and in association with several diseases. The purpose of this review is to provide a brief overview of the components of mucosal immunity that impact the gut microbiota and then discuss how altered immunological conditions may shape the gut microbiota and consequently affect neuroimmune diseases, using a select group of common neuroimmune diseases as examples.

Management of psychiatric and cognitive complications in Parkinson's disease

Neuropsychiatric symptoms (NPSs) such as affective disorders, psychosis, behavioral changes, and cognitive impairment are common in Parkinson's disease (PD). However, NPSs remain under-recognized and under-treated, often leading to adverse outcomes. Their epidemiology, presentation, risk factors, neural substrate, and management strategies are incompletely understood. While psychological and psychosocial factors may contribute, hallmark PD neuropathophysiological changes, plus the associations between exposure to dopaminergic medications and occurrence of some symptoms, suggest a neurobiological basis for many NPSs. A range of psychotropic medications, psychotherapeutic techniques, stimulation therapies, and other non-pharmacological treatments have been studied, are used clinically, and are beneficial for managing NPSs in PD. Appropriate management of NPSs is critical for comprehensive PD care, from recognizing their presentations and timing throughout the disease course, to the incorporation of different therapeutic strategies (ie, pharmacological and non-pharmacological) that utilize a multidisciplinary approach.

Survey of Patients Employing Cannabigerol-Predominant Cannabis Preparations: Perceived Medical Effects, Adverse Events, and Withdrawal Symptoms

Introduction: Cannabigerol (CBG), and its precursor before decarboxylation, cannabigerolic acid is sometimes labeled the "mother of all cannabinoids." The purpose of the present study was to investigate reasons for use and self-reported therapeutic effects in CBG-predominant cannabis users. Usage patterns and adverse effects, including withdrawal symptoms were also explored. Methods: Cannabidiol-predominant cannabis users were recruited online to complete an online survey assessing CBG use patterns, conditions treated with CBG-predominant cannabis (containing >50% CBG), perceived efficacy, associated adverse events, and withdrawal symptoms. One hundred twenty-seven eligible participants (U.S. residents ages 21+ who reported using CBG-predominant cannabis in the past 6 months) completed the survey. Results: Most of the samples (n=65; 51.2%) reported use of CBG-predominant products solely for medical purposes (n=46; 36.2% reported use for medical and recreational purposes; n=8; 6.3% reported recreational use only, and n=8 were missing). The most common conditions the complete sample reported using CBG to treat were anxiety (51.2%), chronic pain (40.9%), depression (33.1%), and insomnia/disturbed sleep (30.7%). Efficacy was highly rated, with the majority reporting their conditions were "very much improved" or "much improved" by CBG. Furthermore, 73.9% claimed superiority of CBG-predominant cannabis over conventional medicines for chronic pain, 80% for depression, 73% for insomnia, and 78.3% for anxiety. Forty-four percent of CBG-predominant cannabis users reported no adverse events, with 16.5% noting dry mouth, 15% sleepiness, 11.8% increased appetite, and 8.7% dry eyes. Around 84.3% reported no withdrawal symptoms, with sleep difficulties representing the most frequently endorsed withdrawal symptom (endorsed by two respondents). Conclusions: This is the first patient survey of CBG-predominant cannabis use to date, and the first to document self-reported efficacy of CBG-predominant products, particularly for anxiety, chronic pain, depression, and insomnia. Most respondents reported greater efficacy of CBG-predominant cannabis over conventional pharmacotherapy, with a benign adverse event profile and negligible withdrawal symptoms. This study establishes that humans are employing CBG and suggests that CBG-predominant cannabis-based medicines should be studied in randomized controlled trials.

Constructing prediction models for excessive daytime sleepiness by nomogram and machine learning: A large Chinese multicenter cohort study

Objective

Although risk factors for excessive daytime sleepiness (EDS) have been reported, there are still few cohort-based predictive models for EDS in Parkinson’s disease (PD). This 1-year longitudinal study aimed to develop a predictive model of EDS in patients with PD using a nomogram and machine learning (ML).

Materials and methods

A total of 995 patients with PD without EDS were included, and clinical data during the baseline period were recorded, which included basic information as well as motor and non-motor symptoms. One year later, the presence of EDS in this population was re-evaluated. First, the baseline characteristics of patients with PD with or without EDS were analyzed. Furthermore, a Cox proportional risk regression model and XGBoost ML were used to construct a prediction model of EDS in PD.

Results

At the 1-year follow-up, EDS occurred in 260 of 995 patients with PD (26.13%). Baseline features analysis showed that EDS correlated significantly with age, age of onset (AOO), hypertension, freezing of gait (FOG). In the Cox proportional risk regression model, we included high body mass index (BMI), late AOO, low motor score on the 39-item Parkinson’s Disease Questionnaire (PDQ-39), low orientation score on the Mini-Mental State Examination (MMSE), and absence of FOG. Kaplan–Meier survival curves showed that the survival prognosis of patients with PD in the high-risk group was significantly worse than that in the low-risk group. XGBoost demonstrated that BMI, AOO, PDQ-39 motor score, MMSE orientation score, and FOG contributed to the model to different degrees, in decreasing order of importance, and the overall accuracy of the model was 71.86% after testing.

Conclusion

In this study, we showed that risk factors for EDS in patients with PD include high BMI, late AOO, a low motor score of PDQ-39, low orientation score of MMSE, and lack of FOG, and their importance decreased in turn. Our model can predict EDS in PD with relative effectivity and accuracy.

Sleep Quality and Related Clinical Manifestations in Huntington Disease

(1) Background: Sleep patterns are frequently disrupted in neurodegenerative disorders such as Huntington disease (HD); however, they are still poorly understood, especially their association with clinic features. Our study aimed to explore potential correlations between sleep features and motor, cognitive, behavioural and functional changes in manifest HD subjects. (2) Methods: We enrolled 42 patients who were assessed by the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) questionnaires; clinical features were evaluated by the validated ENROLL-HD platform assay, including the Unified Huntington’s Disease Rating Scale (UHDRS) and the Problem Behaviours Assessment Short Form (PBA-s). (3) Results: We found a significant association between the patients’ perception of sleep abnormalities and scores of impaired independence, cognitive and motor performances. Specifically, sleep efficiency (PSQI—C4 subscores) and the use of sleep medications (PSQI—C6 subscores) seem to be more frequently associated with the severity of the disease progression. (4) Conclusion: sleep abnormalities represent an important part of the HD clinical profile and can impair patients’ quality of life by affecting their level of independence, cognition performance and mental well-being.

Neuropsychology of posteromedial parietal cortex and conversion factors from Mild Cognitive Impairment to Alzheimer's disease: systematic search and state-of-the-art review

In the present review, we discuss the rationale and the clinical implications of assessing visuospatial working memory (VSWM), awareness of memory deficits, and visuomotor control in patients with mild cognitive impairment (MCI). These three domains are related to neural activity in the posteromedial parietal cortex (PMC) whose hypoactivation seems to be a significant predictor of conversion from MCI to Alzheimer’s disease (AD) as indicated by recent neuroimaging evidence. A systematic literature search was performed up to May 2021. Forty-eight studies were included: 42 studies provided analytical cross-sectional data and 6 studies longitudinal data on conversion rates. Overall, these studies showed that patients with MCI performed worse than healthy controls in tasks assessing VSWM, awareness of memory deficits, and visuomotor control; in some cases, MCI patients’ performance was comparable to that of patients with overt dementia. Deficits in VSWM and metamemory appear to be significant predictors of conversion. No study explored the relationship between visuomotor control and conversion. Nevertheless, it has been speculated that the assessment of visuomotor abilities in subjects at high AD risk might be useful to discriminate patients who are likely to convert from those who are not. Being able to indirectly estimate PMC functioning through quick and easy neuropsychological tasks in outpatient settings may improve diagnostic and prognostic accuracy, and therefore, the quality of the MCI patient’s management.

Parkinsonism and dementia

The aim of the present review is to summarize literature data on dementia in parkinsonian disorders. Cognitive decline and the gradual development of dementia are considered to be key features in the majority of parkinsonian conditions. The burden of dementia in everyday life of parkinsonian patients and their caregivers is vast and can be even more challenging to handle than the motor component of the disease. Common pathogenetic mechanisms involve the aggregation and spreading of abnormal proteins like alpha-synuclein, tau or amyloid in cortical and subcortical regions with subsequent dysregulation of multiple neurotransmitter systems. The degree of cognitive deterioration in these disorders is variable and ranges from mild cognitive impairment to severe cognitive dysfunction. There is also variation in the number and type of affected cognitive domains which can involve either a single domain like executive or visuospatial function or multiple ones. Novel genetic, biological fluid or imaging biomarkers appear promising in facilitating the diagnosis and staging of dementia in parkinsonian conditions. A significant part of current research in Parkinson's disease and other parkinsonian syndromes is targeted towards the cognitive aspects of these disorders. Stabilization or amelioration of cognitive outcomes represents a primary endpoint in many ongoing clinical trials for novel disease modifying treatments in this field. This article is part of the Special Issue "Parkinsonism across the spectrum of movement disorders and beyond" edited by Joseph Jankovic, Daniel D. Truong and Matteo Bologna.

Association between sleep disorders and cognitive dysfunctions in non-demented patients with advanced Parkinson's disease

Background

Parkinson’s disease (PD) is increasingly recognized as a multidimensional disorder, characterized by several non-motor symptoms, including disturbances of sleep and cognition. Current studies on the relationship between sleep problems and neuropsychological functions, mainly conducted in early to moderate PD patients, outline mixed results. In this study, we analysed the relationship between subjectively reported sleep alterations and cognitive functions in a large cohort of 181 advanced PD patients.

Methods

All consecutive, non-demented, advanced PD patients candidates for device-aided therapy completed two self-administered sleep questionnaires—the Parkinson’s Disease Sleep Scale (PDSS-2) and the Epworth Sleepiness Scale (ESS)—and underwent a comprehensive battery of neuropsychological tests encompassing five cognitive domains (reasoning, memory, attention, frontal executive functions, and language).

Results

Patients showed mild to moderate sleep problems (PDSS-2 score: 23.4 ± 1.2) and mild daytime sleepiness (ESS 8.6 ± 5.1). A significant correlation was found between PDSS-2 total score and non-verbal reasoning, as well as attentive skills, executive functions, and language abilities. No correlations were found between sleep measures and memory tests scores. Patients with clinically relevant sleep disturbances performed worse on attention, executive functions, and language. No significant correlations were found between daytime sleepiness and any neuropsychological test.

Conclusions

In advanced PD patients, sleep disturbances selectively correlate with specific neuropsychological functions and not with short-term memory and consolidation. Even if confirmations by means of longitudinal studies are needed, our observations suggest the importance of considering treatment of sleep disturbances to minimize their potential impact on cognition.