Polysomnographic Predictors of Sleep, Motor, and Cognitive Dysfunction Progression in Parkinson's Disease

Epg5 links proteotoxic stress due to defective autophagic clearance and epileptogenesis in Drosophila and Vici syndrome patients

Epilepsy is a common neurological condition that arises from dysfunctional neuronal circuit control due to either acquired or innate disorders. Autophagy is an essential neuronal housekeeping mechanism, which causes severe proteotoxic stress when impaired. Autophagy impairment has been associated to epileptogenesis through a variety of molecular mechanisms. Vici Syndrome (VS) is the paradigmatic congenital autophagy disorder in humans due to recessive variants in the ectopic P-granules autophagy tethering factor 5 (EPG5) gene that is crucial for autophagosome-lysosome fusion and autophagic clearance. Here, we used Drosophila melanogaster to study the importance of Epg5 in development, aging, and seizures. Our data indicate that proteotoxic stress due to impaired autophagic clearance and seizure-like behaviors correlate and are commonly regulated, suggesting that seizures occur as a direct consequence of proteotoxic stress and age-dependent neurodegenerative progression. We provide complementary evidence from EPG5-mutated patients demonstrating an epilepsy phenotype consistent with Drosophila predictions.Abbreviations: AD: Alzheimer's disease; ALS-FTD: Amyotrophic Lateral Sclerosis-FrontoTemoporal Dementia; DART: Drosophila Arousal Tracking; ECoG: electrocorticogram; EEG: electroencephalogram; EPG5: ectopic P-granules 5 autophagy tethering factor; KA: kainic acid; MBs: mushroom bodies; MRI magnetic resonance imaging; MTOR: mechanistic target of rapamycin kinase; PD: Parkinson's disease; TSC: TSC complex; VS: Vici syndrome.

Diagnosis and treatment of autonomic failure, pain and sleep disturbances in Parkinson's disease: guideline "Parkinson's disease" of the German Society of Neurology

BACKGROUND AND OBJECTIVE

Non-motor symptoms frequently develop throughout the disease course of Parkinson's disease (PD), and pose affected individuals at risk of complications, more rapid disease progression and poorer quality of life. Addressing such symptom burden, the 2023 revised "Parkinson's disease" guideline of the German Society of Neurology aimed at providing evidence-based recommendations for managing PD non-motor symptoms, including autonomic failure, pain and sleep disturbances.

METHODS

Key PICO (Patient, Intervention, Comparison, Outcome) questions were formulated by the steering committee and refined by the assigned authors. Recommendations were drafted based on relevant studies, systematic reviews, meta-analyses and high-quality guidelines identified by the literature search. They were subsequently reviewed, revised, and voted by the Guideline Group in online consensus conferences. Consensus was achieved in case of > 75% agreement among the group members. The consensus was considered strong, if agreement was > 95%.

RESULTS

The guideline entails: (i) 10 PICOs and 23 recommendations on the diagnosis and treatment of urogenital, cardiovascular and gastrointestinal autonomic failure; (ii) four PICOs and four recommendations on the possible types of pain in PD individuals, their diagnosis and treatment; (iii) 11 PICOs and 11 recommendations on the screening, diagnosis and treatment of sleep disturbances and excessive daytime sleepiness in PD individuals, as well as on their prognostic implications. Thirty-one out of 38 recommendations achieved a strong consensus.

CONCLUSION

The current German PD guideline provides a practice-oriented and etiology-driven stepwise approach to the diagnosis and treatment of autonomic failure, pain and sleep disturbances in PD individuals.

Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson's disease

BACKGROUND

Sleep fragmentation is a persistent problem throughout the course of Parkinson's disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear.

METHOD

We recorded subthalamic nucleus (STN) local field potentials (LFPs) using deep brain stimulation (DBS) with real-time wireless recording capacity from 13 patients with PD undergoing a one-night polysomnography recording, 1 month after DBS surgery before initial programming and when the patients were off-medication. The STN LFP features that characterised different sleep stages, correlated with arousal and sleep fragmentation index, and preceded stage transitions during N2 and REM sleep were analysed.

RESULTS

Both beta and low gamma oscillations in non-rapid eye movement (NREM) sleep increased with the severity of sleep disturbance (arousal index (ArI)-betaNREM: r=0.9, p=0.0001, sleep fragmentation index (SFI)-betaNREM: r=0.6, p=0.0301; SFI-gammaNREM: r=0.6, p=0.0324). We next examined the low-to-high power ratio (LHPR), which was the power ratio of theta oscillations to beta and low gamma oscillations, and found it to be an indicator of sleep fragmentation (ArI-LHPRNREM: r=-0.8, p=0.0053; ArI-LHPRREM: r=-0.6, p=0.0373; SFI-LHPRNREM: r=-0.7, p=0.0204; SFI-LHPRREM: r=-0.6, p=0.0428). In addition, long beta bursts (>0.25 s) during NREM stage 2 were found preceding the completion of transition to stages with more cortical activities (towards Wake/N1/REM compared with towards N3 (p<0.01)) and negatively correlated with STN spindles, which were detected in STN LFPs with peak frequency distinguishable from long beta bursts (STN spindle: 11.5 Hz, STN long beta bursts: 23.8 Hz), in occupation during NREM sleep (β=-0.24, p<0.001).

CONCLUSION

Features of STN LFPs help explain neurophysiological mechanisms underlying sleep fragmentations in PD, which can inform new intervention for sleep dysfunction.

TRIAL REGISTRATION NUMBER

NCT02937727.

Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

Elucidating sleep disorders: a comprehensive bioinformatics analysis of functional gene sets and hub genes

Background

Sleep disorders (SD) are known to have a profound impact on human health and quality of life although their exact pathogenic mechanisms remain poorly understood.

Methods

The study first accessed SD datasets from the GEO and identified DEGs. These DEGs were then subjected to gene set enrichment analysis. Several advanced techniques, including the RF, SVM-RFE, PPI networks, and LASSO methodologies, were utilized to identify hub genes closely associated with SD. Additionally, the ssGSEA approach was employed to analyze immune cell infiltration and functional gene set scores in SD. DEGs were also scrutinized in relation to miRNA, and the DGIdb database was used to explore potential pharmacological treatments for SD. Furthermore, in an SD murine model, the expression levels of these hub genes were confirmed through RT-qPCR and Western Blot analyses.

Results

The findings of the study indicate that DEGs are significantly enriched in functions and pathways related to immune cell activity, stress response, and neural system regulation. The analysis of immunoinfiltration demonstrated a marked elevation in the levels of Activated CD4+ T cells and CD8+ T cells in the SD cohort, accompanied by a notable rise in Central memory CD4 T cells, Central memory CD8 T cells, and Natural killer T cells. Using machine learning algorithms, the study also identified hub genes closely associated with SD, including IPO9, RAP2A, DDX17, MBNL2, PIK3AP1, and ZNF385A. Based on these genes, an SD diagnostic model was constructed and its efficacy validated across multiple datasets. In the SD murine model, the mRNA and protein expressions of these 6 hub genes were found to be consistent with the results of the bioinformatics analysis.

Conclusion

In conclusion, this study identified 6 genes closely linked to SD, which may play pivotal roles in neural system development, the immune microenvironment, and inflammatory responses. Additionally, the key gene-based SD diagnostic model constructed in this study, validated on multiple datasets showed a high degree of reliability and accuracy, predicting its wide potential for clinical applications. However, limited by the range of data sources and sample size, this may affect the generalizability of the results.

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.

The Park Sleep subtype in Parkinson's disease: from concept to clinic

INTRODUCTION

The heterogeneity of Parkinson's disease (PD) is evident from descriptions of non-motor (NMS) subtypes and Park Sleep, originally identified by Sauerbier et al. 2016, is one such clinical subtype associated with the predominant clinical presentation of sleep dysfunctions including excessive daytime sleepiness (EDS), along with insomnia.

AREAS COVERED

A literature search was conducted using the PubMed, Medline, Embase, and Web of Science databases, accessed between 1 February 2023 and 28 March 2023. In this review, we describe the clinical subtype of Park Sleep and related 'tests' ranging from polysomnography to investigational neuromelanin MRI brain scans and some tissue-based biological markers.

EXPERT OPINION

Cholinergic, noradrenergic, and serotonergic systems are dominantly affected in PD. Park Sleep subtype is hypothesized to be associated primarily with serotonergic deficit, clinically manifesting as somnolence and narcoleptic events (sleep attacks), with or without rapid eye movement behavior disorder (RBD). In clinic, Park Sleep recognition may drive lifestyle changes (e.g. driving) along with therapy adjustments as Park Sleep patients may be sensitive to dopamine D3 active agonists, such as ropinirole and pramipexole. Specific dashboard scores based personalized management options need to be implemented and include pharmacological, non-pharmacological, and lifestyle linked advice.

[Application of Polysomnography in Common Neurodegenerative Diseases]

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

Respiratory therapies for Amyotrophic Lateral Sclerosis: A state of the art review

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative condition noteworthy for upper and lower motor neuron death. Involvement of respiratory motor neuron pools leads to progressive pathology. These impairments include decreases in neural activation and muscle coordination, progressive airway obstruction, weakened airway defenses, restrictive lung disease, increased risk of pulmonary infections, and weakness and atrophy of respiratory muscles. These neural, airway, pulmonary, and neuromuscular changes deteriorate integrated respiratory-related functions including sleep, cough, swallowing, and breathing. Ultimately, respiratory complications account for a large portion of morbidity and mortality in ALS. This state-of-the-art review highlights applications of respiratory therapies for ALS, including lung volume recruitment, mechanical insufflation-exsufflation, non-invasive ventilation, and respiratory strength training. Therapeutic acute intermittent hypoxia, an emerging therapeutic tool for inducing respiratory plasticity will also be introduced. A focus on emerging evidence and future work underscores the common goal to continue to improve survival for patients living with ALS.

Predictors of cognitive impairment in newly diagnosed Parkinson's disease with normal cognition at baseline: A 5-year cohort study

Background and objective

Cognitive impairment (CI) is a substantial contributor to the disability associated with Parkinson's disease (PD). We aimed to assess the clinical features and explore the underlying biomarkers as predictors of CI in patients with newly diagnosed PD (NDPD; less than 2 years).

Methods

We evaluated the cognitive function status using the Montreal Cognitive Assessment (MoCA) and a battery of neuropsychological tests at baseline and subsequent annual follow-up for 5 years from the Parkinson's Progression Markers Initiative (PPMI) database. We assessed the baseline clinical features, apolipoprotein (APO) E status, β-glucocerebrosidase (GBA) mutation status, cerebrospinal fluid findings, and dopamine transporter imaging results. Using a diagnosis of CI (combined mild cognitive impairment and dementia) developed during the 5-year follow-up as outcome measures, we assessed the predictive values of baseline clinical variables and biomarkers. We also constructed a predictive model for the diagnosis of CI using logistic regression analysis.

Results

A total of 409 patients with NDPD with 5-year follow-up were enrolled, 232 with normal cognitive function at baseline, and 94 patients developed CI during the 5-year follow-up. In multivariate analyses, age, current diagnosis of hypertension, baseline MoCA scores, Movement disorder society Unified PD Rating Scale part III (MDS-UPDRS III) scores, and APOE status were associated with the development of CI. Predictive accuracy of CI using age alone improved by the addition of clinical variables and biomarkers (current diagnosis of hypertension, baseline MoCA scores, and MDS-UPDRS III scores, APOE status; AUC 0.80 [95% CI 0.74-0.86] vs. 0.71 [0.64-0.77], p = 0.008). Cognitive domains that had higher frequencies of impairment were found in verbal memory (12.6 vs. 16.8%) and attention/processing speed (12.7 vs. 16.9%), however, no significant difference in the prevalence of CI at annual follow-up was found during the 5-year follow-up in NDPD patients.

Conclusion

In NDPD, the development of CI during the 5-year follow-up can be predicted with good accuracy using a model combining age, current diagnosis of hypertension, baseline MoCA scores, MDS-UPDRS III scores, and APOE status. Our study underscores the need for the earlier identification of CI in NDPD patients in our clinical practice.