Sleep Behavior Disorder Screening Questionnaire Research Articles

Clinical assessment and striatal dopaminergic activity in healthy controls and patients with Parkinson's disease: a Bayesian approach.

We aimed to evaluate correlations between striatal dopamine transporter (DAT) uptake and clinical assessments in both patients with Parkinson's disease (PD) and healthy controls. This study enrolled 193 healthy controls, and 581 patients with PD. They underwent various clinical assessments and 123I-FP-CIT SPECT scans. After reconstruction, attenuation correction, and normalization of SPECT images, counts were measured from the bilateral caudate and putamen, and the occipital cortex for reference. Count densities for each region were extracted and used to calculate striatal binding ratios (SBRs) for each striatal region. SBR is calculated as (target region/reference region)-1. After logarithmic transformation of striatal SBRs, we analyzed the effects of clinical assessments on striatal SBRs using Bayesian hierarchical modeling. MDS-UPDRS total score, part I, part II, part III, Epworth Sleepiness Scale, REM sleep behavior disorder screening questionnaire, SCOPA-AUT total score were negatively associated with striatal SBR in patients with PD. Also, HVLT recognition discrimination was positively associated with striatal SBR in both healthy controls and patients with PD. In healthy control, MDS-UPDRS part II, MOCA, SCOPA-AUT total score were positively associated with striatal SBR. We demonstrated that motor symptom, sleep disturbance, autonomic symptom, and cognition of patients with PD were associated with striatal dopaminergic activity. In healthy controls, motor symptoms, autonomic symptom, and cognition were associated with striatal dopaminergic activity, some of which showing the opposite direction with patients with PD. This result might provide new insight to underlying mechanism of dopamine system with motor and non-motor assessments.

Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire in Persian: A Report on the Translation Process

Background: Rapid eye movement sleep behavior disorder (RBD) is a condition where there are changes in muscle tone during REM sleep, leading to abnormal movements. This disorder is typically diagnosed using video polysomnography (VPSG), which is considered the gold standard test. However, a screening questionnaire for RBD (RBDSQ) has been developed, translated, and validated in various languages, and could be used as a low-cost alternative to VPSG. In this study, we followed a standard multi-step process to translate the RBDSQ into Persian. Methods: As per the guidelines suggested by Mapi Research Trust, we followed a four-step process for translation. The process included forward translation, backward translation, cognitive interviews with fifteen patients, and proofreading. We collaborated with Mapi Research Trust in each step of the process. Also, we conducted discussion and revision sessions for each step to ensure that the final translation was accurate. Results: After reviewing the forward and backward translations, some of the items were rephrased. Patients who participated in cognitive interviews found the translation to be generally clear, but some improvements were necessary to make it more expressive. The final proofreading process involved correcting some typing and spelling errors. Conclusions: The Persian translation of RBDSQ was approved by Mapi Research Trust through a standard translation process. This translation is now compatible with the original English version and is available for a future clinical validation study.

Prediction of Treatment Response and Effect on Clinical Manifestations for Normal Pressure Hydrocephalus of Sleep Related Breathing Disorders

Objectives: Sleep disorders and normal pressure hydrocephalus (NPH) are increasingly important issues observed in neurological disorders. However, the correlation between these diseases has not been sufficiently studied. Thus, we discuss the correlation between sleep disorders and the clinical features of NPH. Methods: Overall, 40 patients with idiopathic NPH were included in the study. To evaluate the sleep disorders and psychiatric problems, surveys were administered, including the 36-Item Short Form Survey, Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Berlin Questionnaire, STOP-Bang Questionnaire, Hospital Anxiety and Depression Scale (HADS), Morningness-Eveningness Questionnaire, and the REM Sleep Behavior Disorder Screening Questionnaire. To evaluate the severity of dementia and ataxia, all of the patients completed the Korean mini-mental state examination; Korea frontal assessment battery score, amd unified Parkinson’s disease rating scale-motor scores before and after cerebrospinal fluid (CSF) drainage. The Pearson’s chi-square test, independent Student’s t-test, Mann–Whitney U test, and linear regression analysis were used to analyze the relationship between sleep disorders and symptom improvement after CSF drainage. Results: Of the 40 patients, 21 patients had poor sleep quality (PSQI>5), 8 patients had insomnia (ISI≥8), 11 patients had daytime sleepiness (ESS≥11), 9 (STOP-Bang≥3) to 13 (Berlin≥2 categories) patients had sleep apnea, 13 patients were anxious (HAS≥8), and 27 patients were depressed (HDS≥8). A linear regression analysis showed that sleep apnea was significantly correlated with cognitive function, and insomnia was correlated with cognitive, motor, and frontal lobe functions. Additionally, patients with severe sleep apnea demonstrated a greater recovery of cognitive function after CSF drainage. Conclusions: Obstructive sleep apnea (OSA) is closely related to the clinical symptoms and treatment effectiveness of NPH. The diagnosis and proper treatment of OSA is expected to improve the prognosis of patients with NPH.

Predictive Modeling Using a Composite Index of Sleep and Cognition in the Alzheimer's Continuum: A Decade-Long Historical Cohort Study.

Sleep disturbances frequently affect Alzheimer's disease (AD), with up to 65% patients reporting sleep-related issues that may manifest up to a decade before AD symptoms. To construct a nomogram that synthesizes sleep quality and cognitive performance for predicting cognitive impairment (CI) conversion outcomes. Using scores from three well-established sleep assessment tools, Pittsburg Sleep Quality Index, REM Sleep Behavior Disorder Screening Questionnaire, and Epworth Sleepiness Scale, we created the Sleep Composite Index (SCI), providing a comprehensive snapshot of an individual's sleep status. Initially, a CI conversion prediction model was formed via COX regression, fine-tuned by bidirectional elimination. Subsequently, an optimized prediction model through COX regression, depicted as a nomogram, offering predictions for CI development in 5, 8, and 12 years among cognitively unimpaired (CU) individuals. After excluding CI patients at baseline, our study included 816 participants with complete baseline and follow-up data. The CU group had a mean age of 66.1±6.7 years, with 36.37% males, while the CI group had an average age of 70.3±9.0 years, with 39.20% males. The final model incorporated glial fibrillary acidic protein, Verbal Fluency Test and SCI, and an AUC of 0.8773 (0.792-0.963). In conclusion, the sleep-cognition nomogram we developed could successfully predict the risk of converting to CI in elderly participants and could potentially guide the design of interventions for rehabilitation and/or cognitive enhancement to improve the living quality for healthy older adults, detect at-risk individuals, and even slow down the progression of AD.

MRI brain structural and functional networks changes in Parkinson disease with REM sleep behavior disorders.

Rapid eye movement sleep behavior disorder (RBD) is common in individuals with Parkinson's disease (PD). In spite of that, the precise mechanism underlying the pathophysiology of RBD among PD remains unclear. The aim of the present study was to analyze gray matter volumes (GMVs) as well as the changes of functional connectivity (FC) among PD patients with RBD (PD-RBD) by employing a combination of voxel-based morphometry (VBM) and FC methods. A total of 65 PD patients and 21 healthy control (HC) subjects were included in this study. VBM analyses were performed on all subjects. Subsequently, regions with significant different GMVs between PD patients with and without RBD (PD-nRBD) were selected for further analysis of FC. Correlations between altered GMVs and FC values with RBD scores were also investigated. Additionally, receiver operating characteristic (ROC) curves were employed for the evaluation of the predictive value of GMVs and FC in identifying RBD in PD. PD-RBD patients exhibited lower GMVs in the left middle temporal gyrus (MTG) and bilateral cuneus. Furthermore, we observed higher FC between the left MTG and the right postcentral gyrus (PoCG), as well as lower FC between the bilateral cuneus (CUN) and the right middle frontal gyrus (MFG) among PD-RBD patients in contrast with PD-nRBD patients. Moreover, the GMVs of MTG (extending to the right PoCG) was positively correlated with RBD severity [as measured by REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) score]. Conversely, the FC value between the bilateral CUN and the right MTG in PD-RBD patients was negatively correlated with RBDSQ score. This study revealed the presence replace with GMV and FC changes among PD-RBD patients, which were closely linked to the severity of RBD symptoms. Furthermore, the combination of basic clinical characteristics, GMVs and FC values effectively predicted RBD for individuals with PD.

Validity and reliability of REM sleep behaviour disorder screening questionnaire (RBDSQ) Indonesian version among Indonesian Parkinson’s disease patients: a pilot study

Validity and reliability of REM sleep behaviour disorder screening questionnaire (RBDSQ) Indonesian version among Indonesian Parkinson’s disease patients: a pilot study

Clinical features and neurobiochemical mechanisms of olfactory dysfunction in patients with Parkinson disease.

This study aimed to investigate clinical features, influencing factors and neurobiochemical mechanisms of olfactory dysfunction (OD) in Parkinson disease (PD). Total 39 patients were divided into thePD with OD (PD-OD) and PD with no OD (PD-nOD) groups according to overall olfactory function, including threshold, discrimination and identification, assessed by Sniffin' Sticks test. Motor functionand non-motor symptoms were rated by multiple scales. Dopamine, acetylcholine, norepinephrine and 5-hydroxytryptamine levels in cerebrospinal fluid (CSF) were measured. We found that thePD-OD group showed significantly lower score of Montreal Cognitive Assessment Scale, higher scores of rapid eye movement sleep behavior disorder (RBD) Screening Questionnaire and Epworth Sleepiness Scale than thePD-nOD group (p < 0.05). RBD Screening Questionnaire score was independently associated with the scores of overall olfactory function and discrimination (p < 0.05). Dopamine and acetylcholine levels in CSF from thePD-OD group was significantly lower than that from thePD-nOD group (p < 0.05). Dopamine and acetylcholine levels in CSF were significantly and positively correlated with the scores of overall olfactory function, threshold, discrimination and identification in PD patients (p < 0.05). RBD Screening Questionnaire score was significantly and negatively correlated with acetylcholine level in CSF in PD patients with poor olfactory detection (p < 0.05). This investigation reveals that PD-OD is associated with cognitive impairment, probable RBD and excessive daytime sleepiness. PD-OD is correlated with the decreased levels of dopamine and acetylcholine in CSF. RBD is an independent influencing factor of overall olfactory function and discrimination, and thedecreased acetylcholine level in CSF may be the common neurobiochemical basis of RBD and OD in PD patients.

Isolated REM sleep behaviour disorder in the Tasmanian ISLAND Sleep Study: prevalence and profiles of prodromal dementia

AbstractBackgroundIdentifying people with isolated REM sleep behaviour disorder (iRBD) provides important opportunities for targeted dementia prevention as iRBD is a prodrome of Lewy Body dementia (LBD) and other neurodegenerative diseases (NDD). There have been no prevalence studies of iRBD in Australia and little is known about whether associated motor, cognitive, olfactory and circadian features influence the progression to different NDD. The Island Study Linking Ageing and Neurodegenerative Disease (ISLAND) Sleep Study aims to identify the iRBD prevalence in Tasmania and determine how different iRBD profiles predict progression to dementia and other NDD.MethodAdults aged 50+ years in Tasmania completed online questionnaires including the REM Sleep Behaviour Disorder Screening Questionnaire (RBDSQ), RBD single question screen (RBD1Q), Pittsburgh Sleep Quality Index (PSQI), and questions regarding dreaming, autonomic, motor s, and pain symptoms.Result2,905 participants have been recruited (mean (SD) age 64 (7.7) years; 26% male). 273 (9.4%) have ‘probable’ iRBD (pRBD) based on the RBDQ1. Compared to those without pRBD, the pRBD group have poorer sleep quality (66% vs 57%), greater autonomic dysfunction (median score 18 vs 13), more pain (particularly stabbing and itching pain), higher risk for sleep apnoea (30% vs 13%), more intense dreams (21% vs 8%), and more motor symptoms, including shaky limbs (16% vs 6%) and slurred speech (12% vs 6%).Conclusion2905 participants have been recruited (mean (SD) age 64 (7.7) years; 26% male). 273 (9.4%) have ‘probable’ iRBD (pRBD) based on the RBDQ1. Compared to those without pRBD, the pRBD group have poorer sleep quality (66% vs 57%), greater autonomic dysfunction (median score 18 vs 13), more pain (particularly stabbing and itching pain), higher risk for sleep apnoea (30% vs 13%), more intense dreams (21% vs 8%), and more motor symptoms, including shaky limbs (16% vs 6%) and slurred speech (12% vs 6%).

Parkinson’s Disease Non-Motor Subtypes Classification in a Group of Slovenian Patients: Actuarial vs. Data-Driven Approach

Background and purpose: The aim of this study was to examine the risk factors, prodromal symptoms, non-motor symptoms (NMS), and motor symptoms (MS) in different Parkinson’s disease (PD) non-motor subtypes, classified using newly established criteria and a data-driven approach. Methods: A total of 168 patients with idiopathic PD underwent comprehensive NMS and MS examinations. NMS were assessed by the Non-Motor Symptom Scale (NMSS), Montreal Cognitive Assessment (MoCA), Hamilton Depression Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), Epworth Sleepiness Scale (ESS), Starkstein Apathy Scale (SAS) and Fatigue Severity Scale (FSS). Motor subtypes were classified based on Stebbins’ method. Patients were classified into groups of three NMS subtypes (cortical, limbic, and brainstem) based on the newly designed inclusion criteria. Further, data-driven clustering was performed as an alternative, statistical learning-based classification approach. The two classification approaches were compared for consistency. Results: We identified 38 (22.6%) patients with the cortical subtype, 48 (28.6%) with the limbic, and 82 (48.8%) patients with the brainstem NMS PD subtype. Using a data-driven approach, we identified five different clusters. Three corresponded to the cortical, limbic, and brainstem subtypes, while the two additional clusters may have represented patients with early and advanced PD. Pearson chi-square test of independence revealed that a priori classification and cluster membership were significantly related to one another with a large effect size (χ2(8) = 175.001, p &lt; 0.001, Cramer’s V = 0.722). The demographic and clinical profiles differed between NMS subtypes and clusters. Conclusion: Using the actuarial and clustering approach, marked differences between individual NMS subtypes were found. The newly established criteria have potential as a simplified tool for future clinical research of NMS subtypes of Parkinson’s disease.

The Genetic Basis of Probable REM Sleep Behavior Disorder in Parkinson's Disease.

Patients with Parkinson's Disease (PD) experience REM sleep behavior disorder (RBD) more frequently than healthy controls. RBD is associated with torpid disease evolution. To test the hypothesis that differential genetic signatures might contribute to the torpid disease evolution in PD patients with RBD we compared the rate of genetic mutations in PD patients with or without probable RBD. Patients with a clinical diagnosis of PD in the Parkinson's Progression Markers Initiative (PPMI) database entered the study. We excluded those with missing data, dementia, psychiatric conditions, or a diagnosis change over the first five years from the initial PD diagnosis. Probable RBD (pRBD) was confirmed by a REM Sleep Behavior Disorder Screening Questionnaire score > 5 points. Logistic regression and Machine Learning (ML) algorithms were used to relate Single Nucleotide Polymorphism (SNPs) in PD-related genes with pRBD. We included 330 PD patients fulfilling all inclusion and exclusion criteria. The final logistic multivariate model revealed that the following SNPs increased the risk of pRBD: GBA_N370S_rs76763715 (OR, 95% CI: 3.38, 1.45-7.93), SNCA_A53T_rs104893877 (8.21, 2.26-36.34), ANK2. CAMK2D_rs78738012 (2.12, 1.08-4.10), and ZNF184_rs9468199 (1.89, 1.08-3.33). Conversely, SNP COQ7. SYT17_rs11343 reduced pRBD risk (0.36, 0.15-0.78). The ML algorithms led to similar results. The predictive models were highly specific (95-99%) but lacked sensitivity (9-39%). We found a distinctive genetic signature for pRBD in PD. The high specificity and low sensitivity of the predictive models suggest that genetic mutations are necessary but not sufficient to develop pRBD in PD. Additional investigations are needed.

Regional homogeneity and functional connectivity of freezing of gait conversion in Parkinson's disease.

Freezing of gait (FOG) is common in the late stage of Parkinson's disease (PD), which can lead to disability and impacts the quality of life. Therefore, early recognition is crucial for therapeutic intervention. We aimed to explore the abnormal regional homogeneity (ReHo) and functional connectivity (FC) in FOG converters and evaluate their diagnostic values. The data downloaded from the Parkinson's Disease Progression Markers Project (PPMI) cohort was subdivided into PD-FOG converters (n = 16) and non-converters (n = 17) based on whether FOG appeared during the 3-year follow-up; 16 healthy controls were well-matched. ReHo and FC analyses were used to explore the variations in spontaneous activity and interactions between significant regions among three groups of baseline data. Correlations between clinical variables and the altered ReHo values were assessed in FOG converter group. Last, logistic regression and receiver operating characteristic curve (ROC) were used to predict diagnostic value. Compared with the non-converters, FOG converters had reduced ReHo in the bilateral medial superior frontal gyrus (SFGmed), which was negatively correlated with the postural instability and gait difficulty (PIGD) score. ReHo within left amygdala/olfactory cortex/putamen (AMYG/OLF/PUT) was decreased, which was correlated with anxiety and autonomic dysfunction. Also, increased ReHo in the left supplementary motor area/paracentral lobule was positively correlated with the rapid eye movement sleep behavior disorder screening questionnaire. FOG converters exhibited diminished FC in the basal ganglia, limbic area, and cognitive control cortex, as compared with non-converters. The prediction model combined ReHo of basal ganglia and limbic area, with PIGD score was the best predictor of FOG conversion. The current results suggested that abnormal ReHo and FC in the basal ganglia, limbic area, and cognitive control cortex may occur in the early stage of FOG. Basal ganglia and limbic area dysfunction combined with higher PIGD score are useful for the early recognition of FOG conversion.

Decreased serum BDNF contributes to the onset of REM sleep behavior disorder in Parkinson’s disease patients

BackgroundBrain-derived neurotrophic factor (BDNF) promotes neuroprotection and neuroregeneration. BDNF enhances the survival of dopaminergic neurons and improves dopaminergic neurotransmission and motor performance in patients with Parkinson's disease (PD). However, the association between BDNF levels and rapid eye movement (REM) sleep behavior disorder (RBD) in PD patients has received limited attention. MethodsWe employed the Rapid Eye Movement Sleep Behavior Disorder Questionnaire-Hong Kong version (RBDQ-HK) and the Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire (RBDSQ) for RBD diagnosis. Patients were categorized into three groups: healthy controls (n = 53), PD patients without RBD (PD-nRBD; n = 56), and PD patients with RBD (PD-RBD; n = 45). Serum BDNF concentrations, demographic information, medical history, and motor/non-motor manifestations were compared between the three groups. Logistic regression analysis was performed to identify independent factors associated with PD and RBD. P-trend analysis was used to assess the relationship between BDNF levels and the risk of PD and RBD onset. Interaction effects were analyzed between BDNF, patients’ age, and gender on the risk of RBD onset in PD patients. ResultsOur findings indicate that serum BDNF levels were significantly lower in PD patients compared to healthy controls (p < 0.001). PD-RBD patients exhibited higher motor symptom scores (UPDRS III) than PD-nRBD patients (p = 0.021). Additionally, the PD-RBD group demonstrated lower cognitive function scores as measured by the Montreal Cognitive Assessment (MoCA) (p < 0.001) and Mini-Mental State Examination (MMSE) (p = 0.015). PD-RBD patients displayed significantly lower BDNF levels compared to both PD-nRBD and healthy control groups (p < 0.001). Univariate and multivariate logistic regression analyses showed that reduced BDNF levels were associated with an increased risk of RBD in PD patients (p = 0.005). P-trend analysis further confirmed the progressive relationship between decreased BDNF levels and the risk of PD and RBD onset. Furthermore, our interaction analysis highlighted the importance of monitoring younger PD patients with low serum BDNF levels for potential RBD onset. ConclusionsThis study illustrates that decreased serum BDNF levels may be linked to the development of RBD in PD patients, highlighting the potential utility of BDNF as a biomarker in clinical practice.

Olfactory Impairment Is the Main Predictor of Higher Scores at REM Sleep Behavior Disorder (RBD) Screening Questionnaire in Parkinson's Disease Patients.

Olfactory impairment and REM sleep behavior disorder (RBD) are common non-motor symptoms in Parkinson's disease (PD) patients, often preceding the onset of the specific motor symptoms and, thus, crucial for strategies directed to anticipate PD diagnosis. In this context, the specific interaction between olfactory impairment and RBD has not been clearly defined. The aim of this study was to determine the possible role of olfactory impairment and other clinical characteristics as possible predictors of higher scores at RBD screening questionnaire (RBDSQ) in a large population of PD patients. In this study, 590 PD patients were included from the Parkinson's Progression Markers Initiative. Demographic and clinical features were registered. All participants completed motor and non-motor evaluations at the baseline visit. For motor assessments, the disease severity was evaluated by the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) pars III. Regarding non-motor symptoms assessment, Montreal Cognitive Assessments (MoCA), University of Pennsylvania Smell Identification Test (UPSIT) and RBD screening questionnaire (RBDSQ) were registered. Among 590 PD patients included in this study, 111 patients with possible RBD were found (18.8%). RBD was less frequent in female PD patients (p ≤ 0.011). Among patients with or without possible RBD diagnosis, statistically significant differences in MDS-UPDRS III (23.3 ± 11.4 vs. 19.7 ± 9.1, respectively, p ≤ 0.002) and in UPSIT score (19.7 ± 8.3 vs. 22.6 ± 8.0, respectively, p ≤ 0.001) were found. Moreover, significant correlations between RBDSQ versus UPDRS III score and versus UPSIT score were observed. Multivariate linear regression analysis showed that UPSIT was the most significant predictor of higher scores at RBDSQ, while the other significant predictors were UPDRS III and age. The severity of olfactory impairment appears tightly correlated to RBD symptoms, highlighting the role of these biomarkers for PD patients. Additionally, according to this large study, our data confirmed that RBD in PD patients exhibits peculiar gender differences.

Motor and non-motor features in Parkinson's Disease patients carrying GBA gene mutations.

Mutations of the Glucocerebrosidase (GBA) gene are the most common genetic risk factor yet discovered for Parkinson's Disease (PD), being found in about 5-14% of Caucasian patients. We aimed to assess motor and non-motor symptoms (NMS) in patients with GBA-related PD (GBA-PD) in comparison with idiopathic PD (iPD) subjects using standardized and validated scales. Eleven (4M, 7 F) patients with GBA-PD and 22 iPD patients, selected from the same cohort and matched for gender, age, and disease duration, were enrolled. The disease severity was assessed by Unified Parkinson's Disease Rating Scale-section III, gait disorder and falls by Freezing of Gait Questionnaire, and motor fluctuations by Wearing off questionnaire. NMS were evaluated using the following scales: Mini-Mental State Examination and extended neuropsychological battery, if required, Non-Motor Symptoms Scale, SCOPA-AUT Questionnaire, Apathy Evaluation Scale, Beck Depression Inventory, Epworth Sleepiness Scale, Restless Legs Syndrome Rating Scale, REM Sleep Behavior Disorder Screening Questionnaire, and Questionnaire for Impulsive-Compulsive Disorders in Parkinson's disease. GBA-PD patients showed a more severe and rapidly progressive disease, and more frequent positive family history for PD, akinetic-rigid phenotype, postural instability, dementia, and psychosis in comparison to iPD. Two of three subjects carrying L444P mutation presented with early dementia. We also found a higher occurrence of fatigue, diurnal sleepiness, and intolerance to heat/cold in the carriers group. Our results confirm that NMS and a more severe and faster disease course more frequently occur among GBA-PD patients in comparison to iPD.

Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson's disease: Protocol of the mixed method, cyclic ActiveAgeing study.

BackgroundActive ageing is described as the process of optimizing health, empowerment, and security to enhance the quality of life in the rapidly growing population of older adults. Meanwhile, multimorbidity and neurological disorders, such as Parkinson’s disease (PD), lead to global public health and resource limitations. We introduce a novel user-centered paradigm of ageing based on wearable-driven artificial intelligence (AI) that may harness the autonomy and independence that accompany functional limitation or disability, and possibly elevate life expectancy in older adults and people with PD.MethodsActiveAgeing is a 4-year, multicentre, mixed method, cyclic study that combines digital phenotyping via commercial devices (Empatica E4, Fitbit Sense, and Oura Ring) with traditional evaluation (clinical assessment scales, in-depth interviews, and clinical consultations) and includes four types of participants: (1) people with PD and (2) their informal caregiver; (3) healthy older adults from the Helgetun living environment in Norway, and (4) people on the Helgetun waiting list. For the first study, each group will be represented by N = 15 participants to test the data acquisition and to determine the sample size for the second study. To suggest lifestyle changes, modules for human expert-based advice, machine-generated advice, and self-generated advice from accessible data visualization will be designed. Quantitative analysis of physiological data will rely on digital signal processing (DSP) and AI techniques. The clinical assessment scales are the Unified Parkinson’s Disease Rating Scale (UPDRS), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), Apathy Evaluation Scale (AES), and the REM Sleep Behaviour Disorder Screening Questionnaire (RBDSQ). A qualitative inquiry will be carried out with individual and focus group interviews and analysed using a hermeneutic approach including narrative and thematic analysis techniques.DiscussionWe hypothesise that digital phenotyping is feasible to explore the ageing process from clinical and lifestyle perspectives including older adults and people with PD. Data is used for clinical decision-making by symptom tracking, predicting symptom evolution, and discovering new outcome measures for clinical trials.

The efficacy and safety of transcutaneous auricular vagus nerve stimulation in patients with mild cognitive impairment: A double blinded randomized clinical trial

BackgroundThere are 9.9 million new cases of dementia in the world every year. Short-term conversion rate from mild cognitive impairment (MCI) to dementia is between 20% and 40%, but long-term in 5–10 years ranges from 60% to 100%. It is particularly important to prevent or prolong the development of MCI into dementia. Both auriculotherapy and vagus nerve stimulation are effective on improving cognitive functions. However, there is no double blinded randomized clinical trial to support the effectiveness of transcutaneous electrical stimulation of auricular acupoints in patients with MCI. MethodsThis randomized controlled trial involved patients with MCI, aged from 55 to 75 years old. Patients were randomly allocated to transcutaneous auricular vagus nerve stimulation (taVNS) group or sham taVNS group. In the taVNS group, two auricular acupoints were stimulated, including heart (concha, CO15) and kidney (CO10), which are in the distribution of vagus nerve. While in the sham taVNS group, two other auricular acupoints were stimulated, including elbow (scaphoid fossa, SF3) and shoulder (SF4,5), which are out of the distribution of vagus nerve. The primary outcome was the Montreal cognitive assessment-basic, MOCA-B. The secondary outcomes included auditory verbal learning test-HuaShan version (AVLT-H), shape trails test A&B (STT-A&B), animal fluence test (AFT), Boston naming test (BNT), Pittsburgh sleep quality index (PSQI), rapid eye movement sleep behavior disorder screening questionnaire (RBDSQ), Epworth sleepiness scale (ESS) and functional activities questionnaire (FAQ). These outcome measures were taken at baseline, 24 weeks later. ResultsAfter 24 weeks of intervention, the data of 52 patients were intended for analysis. After intervention, there was significant difference in the overall scores of MoCA-B between taVNS group and sham taVNS group (p = 0.033 < 0.05). In taVNS group, compared with before intervention, the overall scores of MOCA-B increased significantly after intervention (p < 0.001). As for N5 and N7, the two sub-indicators of AVLT-H, in taVNS group, compared with before intervention, both N5 and N7 increased significantly after intervention (both ps < 0.001). As for STTB, in taVNS group, compared with before intervention, STTB was significantly reduced after intervention (p = 0.016). For BNT, in taVNS group, compared with before intervention, BNT increased significantly after intervention (p < 0.001). In taVNS group, compared with before intervention, PSQI, RBDSQ, ESS and FAQ decreased significantly after intervention (p = 0.002, 0.025, <0.001, 0.006 respectively). 1 patient with a history of tympanic membrane perforation in taVNS group was reported with mild adverse reactions which disappeared a week after termination of taVNS. The intervention of taVNS is effective on increasing the overall scores of MoCA-B, N5 and N7. ConclusionThe clinical trial demonstrated that taVNS can improve cognitive performance in patients with MCI. This inexpensive, effective and innovative method can be recommended as a therapy for more patients with MCI in the prevention or prolonging of its development into dementia, but it is still required to be further investigated. Trial registrationhttp://www.chictr.org.cn. (ID: ChiCTR2000038868)

Association of Plasma and Electroencephalography Markers With Motor Subtypes of Parkinson's Disease.

ObjectiveThe aim of this study was to investigate the correlations of plasma neurodegenerative proteins and electroencephalography (EEG) dynamic functional network (DFN) parameters with disease progression in early Parkinson’s disease (PD) with different motor subtypes, including tremor-dominant (TD) and postural instability and gait disorder (PIGD).MethodsIn our study, 33 patients with PD (21 TD and 12 PIGD) and 33 healthy controls (HCs) were enrolled. Plasma neurofilament light chain (NfL), α-synuclein (α-syn), total-tau (t-tau), β-amyloid 42 (Aβ42), and β-amyloid 40 (Aβ40) levels were measured using an ultrasensitive single-molecule array (Simoa) immunoassay. All the patients with PD underwent EEG quantified by DFN analysis. The motor and non-motor performances were evaluated by a series of clinical assessments. Subsequently, a correlation analysis of plasma biomarkers and EEG measures with clinical scales was conducted.ResultsIn the TD group, plasma NfL exhibited a significant association with MDS-UPDRS III and Montreal Cognitive Assessment (MoCA). A higher Aβ42/40 level was significantly related to a decrease in Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA) in the PIGD group. In terms of the correlation between EEG characteristic parameters and clinical outcomes, trapping time (TT) delta was positively correlated with MDS-UPDRS III and MoCA scores in the TD group, especially in the prefrontal and frontal regions. For other non-motor symptoms, there were significant direct associations of kPLI theta with HAMD and HAMA, especially in the prefrontal region, and kPLI gamma was particularly correlated with Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire (RBDSQ) scores in the prefrontal, frontal, and parietal regions in the TD group. Furthermore, there was a significant positive correlation between plasma t-tau and kPLI, and pairwise correlations were found among plasma NfL, theta TT, and MoCA scores in the TD group.ConclusionThese results provide evidence that plasma neurodegenerative proteins and EEG measures have great potential in predicting the disease progression of PD subtypes, especially for the TD subtype. A combination of these two kinds of markers may have a superposition effect on monitoring and estimating the prognosis of PD subtypes and deserves further research in larger, follow-up PD cohorts.

Prevalence and features of non-motor symptoms in Wilson’s disease

IntroductionWilson's Disease (WD) is an autosomal recessive disorder caused by excessive copper deposition in liver, brain and other organs. The clinical picture is characterized by hepatic, psychiatric and neurological dysfunction. Movement disorders are the core neurological features, although non-motor symptoms (NMS), as cognitive/affective, autonomic and sleep disorders, may occur over time. We aimed to assess the frequency of NMS in WD patients compared with healthy subjects. MethodsTwenty-seven patients affected with genetically proven WD (12 F, 15 M) and 35 healthy controls (Ctrl; 17 F, 18 M), comparable for age and education, were enrolled. Eighteen patients presented with the neurological form of the disease (NV) and nine with the non-neurological variant (NNV). NMS were assessed in all subjects by the following clinical scales: Mini-Mental State Examination (MMSE), Non-Motor Symptoms Scale (NMSS), SCOPA-AUT Questionnaire, Apathy Evaluation Scale (AES), Beck Depression Inventory (BDI), Epworth Sleepiness Scale (ESS), Restless Legs Syndrome Rating Scale (RLSRS), REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), Questionnaire for Impulsive-Compulsive Disorders in Parkinson's disease (QUIP-RS). ResultsWe found that the patients showed more severe and frequent NMS and daytime sleepiness, and lower MMSE than Ctrl. In comparison to healthy subjects, NV subjects showed statistically significant higher ESS, NMSS, and RLSRS scores, and a lower MMSE score. Subtle and subclinical extrapyramidal/pyramidal signs and brain MRI signal abnormalities were detected in patients considered as asymptomatic for neurological disturbances. ConclusionsNMS are common among WD patient, in particular those with NV, likely due to the widespread pathological changes throughout the central nervous system.

Development and validation of a nomogram for freezing of gait in patients with Parkinson's Disease.

Freezing of gait (FOG) is a common and complex disabling episodic gait disturbance in patients with Parkinson's disease (PD). Currently, the treatment of FOG remains a challenge for clinicians. The aim of our study was to develop a nomogram for FOG risk based on data collected from Chinese patients with PD. A total of 379 PD patients (197 with FOG) from Kunming Medical University were recruited as a training cohort. Additionally, 339 PD patients (166 with FOG) were recruited from West China Hospital of Sichuan University, to serve as the validation cohort. The least absolute shrinkage and selection operator regression model was used to select clinical and demographic characteristics as well as blood markers, which were incorporated into a predictive model using multivariate logistic regression to predict the risk of developing FOG. The model was validated using the validation dataset, and model performance was evaluated using the C-index, calibration plot, and decision curve analyses. The final predictive model included the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) score, Parkinson's Disease Questionnaire (PDQ39), H-Y stage, and visuospatial function. The model showed good calibration and good discrimination, with a C-index value of 0.772 against the training cohort and 0.766 against the validation cohort. Decision curve analysis demonstrated the clinical utility of the nomogram. A nomogram incorporating RBDSQ, PDQ39, H-Y stage, and visuospatial function may reliably predict the risk of FOG in PD patients.

Reply to: Correlation of Antidepressant Use and Symptom Time Period in Dream Enactment Behaviors.

Firstly, I would like to thank Sumi et al.1 for showing interest in my recently published study2 and providing the opportunity to expand the discussion on this fascinating topic, that has both clinical and theoretical relevance. Sumi et al. had concerns about possible confounding due to medication use. Although all participants in the Parkinson's Progression Markers Initiative (PPMI) database were untreated for Parkinson's disease (PD) at baseline, which is important to highlight, since dopaminergic medications have previously been associated with dream alterations3; I do nevertheless agree that given the frequent comorbidity of depression and REM sleep behavior disorder in people with PD, that the effects of antidepressants and clonazepam used to treat these, ought to be considered. In fact, a previous study identified that 41.2% of PD participants in PPMI reported using antidepressants during the course of the study and 14.2% reported having used clonazepam.4 However, Sumi et al.'s statement that neither PPMI nor the study evaluated the presence of depression, is not entirely correct. In the study, total number of depressive symptoms, assessed using the extensively validated Geriatric Depression Scale,5 was included as a covariate in one of the sensitivity analyses.2 Crucially, the inclusion of depressive symptoms as a covariate did not alter the association between aggressive dream content and either motor or cognitive decline.2 Nonetheless, to ensure that the results were not confounded by antidepressant use specifically, I have now conducted two further analyses. First, I repeated the primary analyses after adjusting for antidepressant use at any time from baseline to the most recent study visit. Second, I repeated the analyses after including self-reported past or present depression (obtained from item 10 of the REM sleep behavior disorder screening questionnaire), as an additional covariate. Neither antidepressant use nor a history of depression attenuated the association between dream content and motor or cognitive decline (P's < 0.05). Similarly, after adjusting for clonazepam use, the associations between aggressive dream content and both outcomes remained significant (P's < 0.05). Finally, with respect to Sumi et al.'s third concern regarding fluctuation of aggressive dreams over time, it is pertinent to emphasize that these participants were all newly diagnosed at baseline, with a mean duration of 6.3 months since diagnosis. As such, it is unlikely that sufficient time had passed for there to be a significant group for whom “aggressive dreams [had] disappeared” during the course of PD. In any case, if such a group were to exist, it could actually have led to an underestimation of the association, since individuals who once had aggressive dreams would have been included in the non-aggressive dream group. Therefore, whilst the insightful concerns raised by Sumi et al are important to consider, I do not believe they challenge the core conclusions of this study, namely, that people with newly diagnosed, untreated PD who report having frequent aggressive dreams, may be at higher risk of early motor and cognitive decline than those who do not report having them. Data used in the preparation of this article were obtained from the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data). For up-to-date information on the study, visit www.ppmi-info.org. Data were downloaded from the PPMI database on December 22, 2020. 1. Research Project: Conception, Organization, Execution; 2. Statistical Analysis: Design, Execution; 3. Manuscript Preparation AIO: 1,2,3. Each Parkinson's Progression Markers Initiative site received approval from a local ethical committee on human experimentation before commencement of the study. Written informed consent was obtained from all individuals who participated in the study. I confirm that I have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines. No specific funding was received for this work. I declare that there are no conflicts of interest relevant to this work. The author is funded by a National Institute for Health Research academic clinical fellowship.