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

Utility of the REM sleep behavior disorder screening questionnaire (RBDSQ) in Parkinson’s disease patients

This study evaluated the effects of ropinirole prolonged-release (RPR) in comparison with ropinirole immediate-release (RIR) on sleep-related disorders in Parkinson disease (PD).Thirty-three PD patients (aged 62.5 [SD, 8] years; PD duration, 9 [SD, 4] years) were evaluated on a stable dose of RIR and 5 to 13 weeks after switch to the closest possible dose of RPR. The following questionnaires were administered: Epworth Sleepiness Scale, PD Sleep Scale, Pittsburgh Sleep Quality Index, REM Sleep Behavior Disorder Screening Questionnaire, and PD Questionnaire 39. We further monitored the occurrence of restless legs syndrome and sleep attacks (SAs). Motor disability was evaluated by PD diary and by Unified Parkinson Disease Rating Scale part 3 on medication (ON) and after medication withdrawal (OFF). In 8 patients with marked subjective sleep disturbance, polysomnography, and multiple sleep latency test were performed.After switching to RPR, there was an improvement in PD Sleep Scale (94.9 [SD, 23] vs 102.2 [SD, 27]; P < 0.05 corrected), Pittsburgh Sleep Quality Index (7.2 [SD, 3] vs 5.8 [SD, 3]; P < 0.05 corrected), Epworth Sleepiness Scale (14.1 [SD, 5] vs 12.0 [SD, 6]; P < 0.05 corrected) and Unified Parkinson Disease Rating Scale part 3 in the ON state (20.9 [SD, 10] 10 vs 17.6 [SD, 10]; P < 0.05 corrected). Thirteen patients reported disappearance of SAs on RPR. Polysomnography and multiple sleep latency test showed no changes in a subgroup of 8 patients after the switch to RPR.Ropinirole prolonged-release compared with RIR improved subjective quality of sleep, reduced daytime sleepiness, and led to disappearance of SAs in some patients possibly due to a more stable plasma level of ropinirole.

Stable two-year longitudinal clinical outcomes in LRRK2 G2019S non-manifest carriers in a remote nationwide study.

Cognitive impairment (CI) is one of the most feared and debilitating complications of PD. No therapy has been shown to slow or prevent CI in PD. To determine associations between modifiable comorbidities, including cardiovascular disease risk factors, mood disorders, and sleep characteristics, and rate of cognitive decline in Parkinson's disease (PD). Data from the Parkinson's Progression Markers Initiative (PPMI) cohort was queried for baseline cardiovascular disease risk factors, mood disorders, and sleep characteristics. Linear mixed- effects models (LME) were used to examine the association between baseline factors and change in cognition, evaluated by the Montreal Cognitive Assessment (MoCA) over time. Baseline comorbidities found to affect MoCA decline were assessed for an association with focal cognitive domains using LME. Higher Body Mass Index (BMI) (β = -0.009, P = 0.039), State Trait Anxiety Inventory (STAI) (β = -0.005, P < 0.001), Geriatric Depression Scale (GDS) (β = -0.034, P < 0.001), Epworth Sleepiness Scale (ESS) (β = -0.017, P = 0.003), and REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) (β = -0.037, P < 0.001) were associated with faster rates of MoCA decline. Using established cut-offs for clinically significant symptoms, being overweight, or the presence of depression, excessive day time sleepiness (EDS), and possible REM sleep behavior disorder (pRBD), were all associated with faster rate of cognitive decline. Several modifiable baseline comorbidities are associated with faster rate of CI over time in patients with PD. These associations identify potential opportunities for early intervention that could influence CI in PD.

BackgroundEstablished assessment scales used for Parkinson’s disease (PD) have several limitations in tracking symptom progression and fluctuation. Both research and commercial-grade wearables show potential in improving these assessments. However, it is not known whether pervasive and affordable devices can deliver reliable data, suitable for designing open-source unobtrusive around-the-clock assessments. Our aim is to investigate the usefulness of the research-grade wristband Empatica E4, commercial-grade smartwatch Fitbit Sense, and the Oura ring, for PD research.MethodThe study included participants with PD (N = 15) and neurologically healthy controls (N = 16). Data were collected using established assessment scales (Movement Disorders Society Unified Parkinson’s Disease Rating Scale, Montreal Cognitive Assessment, REM Sleep Behavior Disorder Screening Questionnaire, Hoehn and Yahr Stage), self-reported diary (activities, symptoms, sleep, medication times), and 2-week digital data from the three devices collected simultaneously. The analyses comprised three steps: preparation (device characteristics assessment, data extraction and preprocessing), processing (data structuring and visualization, cross-correlation analysis, diary comparison, uptime calculation), and evaluation (usability, availability, statistical analyses).ResultsWe found large variation in data characteristics and unsatisfactory cross-correlation. Due to output incongruences, only heart rate and movement could be assessed across devices. Empatica E4 and Fitbit Sense outperformed Oura in reflecting self-reported activities. Results show a weak output correlation and significant differences. The uptime was good, but Oura did not record heart rate and movement concomitantly. We also found variation in terms of access to raw data, sampling rate and level of device-native processing, ease of use, retrieval of data, and design. We graded the system usability of Fitbit Sense as good, Empatica E4 as poor, with Oura in the middle.ConclusionsIn this study we identified a set of characteristics necessary for PD research: ease of handling, cleaning, data retrieval, access to raw data, score calculation transparency, long battery life, sufficient storage, higher sampling frequencies, software and hardware reliability, transparency. The three analyzed devices are not interchangeable and, based on data features, none were deemed optimal for PD research, but they all have the potential to provide suitable specifications in future iterations.

To examine potential sex differences in nonmotor symptoms (NMS) among drug-naive patients with Parkinson disease (PD), and to identify NMS that can best differentiate patients with early PD from controls. Our cross-sectional analysis included 414 newly diagnosed, untreated patients with PD (269 men and 145 women) and 188 healthy controls (121 men and 67 women) in the Parkinson's Progression Markers Initiative Study. NMS were measured using well-validated instruments covering sleep, olfactory, neurobehavioral, autonomic, and neuropsychological domains. Male and female patients with PD were fairly comparable on motor presentations but differed on several nonmotor features. Male patients with PD had significantly more pronounced deficits in olfaction (p = 0.02) and in certain cognitive measurements (all p < 0.01) than female patients, whereas female cases experienced higher trait anxiety (p = 0.02). Multiple stepwise logistic regression analysis showed that the combination of NMS measures-University of Pennsylvania Smell Identification Test (UPSIT), Montreal Cognitive Assessment (MoCA), Scales for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), and state anxiety from the State-Trait Anxiety Inventory-effectively differentiated patients with PD from controls with an area under the receiver operating characteristic curve (AUC) of 0.913 (95% confidence interval [CI]: 0.89-0.94). UPSIT, MoCA, and SCOPA-AUT were the most predictive NMS measurements in men (AUC = 0.919; 95% CI: 0.89-0.95) as compared to UPSIT, MoCA, and REM Sleep Behavior Disorder Screening Questionnaire in women (AUC = 0.903; 95% CI: 0.86-0.95). Our analysis revealed notable sex differences in several nonmotor features of patients with de novo PD. Furthermore, we found a parsimonious NMS combination that could effectively differentiate de novo cases from healthy controls.

The phenotype of Parkinson's disease (PD) in patients with and without leucine-rich repeat kinase 2 (LRRK2) G2019S mutations reportedly is similar; however, large, uniformly evaluated series are lacking. The objective of this study was to characterize the clinical phenotype of Ashkenazi Jewish (AJ) PD carriers of the LRRK2 G2019S mutation. We studied 553 AJ PD patients, including 65 patients who were previously reported, from three sites (two in New York and one in Tel-Aviv). Glucocerebrosidase (GBA) mutation carriers were excluded. Evaluations included the Montreal Cognitive Assessment (MoCA), the Unified Parkinson's Disease Rating Scale (UPDRS), the Geriatric Depression Scale (GDS) and the Non-Motor Symptoms (NMS) questionnaire. Regression models were constructed to test the association between clinical and demographic features and LRRK2 status (outcome) in 488 newly recruited participants. LRRK2 G2019S carriers (n = 97) and non-carriers (n = 391) were similar in age and age at onset of PD. Carriers had longer disease duration (8.6 years vs. 6.1 years; P < 0.001), were more likely to be women (51.5% vs. 37.9%; P = 0.015), and more often reported first symptoms in the lower extremities (40.0% vs. 19.2%; P < 0.001). In logistic models that were adjusted for age, disease duration, sex, education, and site, carriers were more likely to have lower extremity onset (P < 0.001), postural instability and gait difficulty (PIGD) (P = 0.043), and a persistent levodopa response for >5 years (P = 0.042). Performance on the UPDRS, MoCA, GDS, and NMS did not differ by mutation status. PD in AJ LRRK2 G2019S mutation carriers is similar to idiopathic PD but is characterized by more frequent lower extremity involvement at onset and PIGD without the associated cognitive impairment.

ObjectivesGBA1 mutations are a frequent risk factor for Parkinson disease (PD). The aim of this study is to evaluate clinical features in a group of GBA1 mutation–positive individuals over a...

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.

Paired neurophysiological and clinical study of the brainstem at different stages of Parkinson’s Disease

Dream content alterations in Parkinson's disease (PD) are associated with motor and cognitive dysfunction cross-sectionally. Although recent studies suggest abnormal dream content in PD might also predict cognitive decline, the relationship between dream content and motor decline in PD remains unknown. To investigate whether abnormal dream content in PD predicts both motor and cognitive decline. Data were obtained from the Parkinson's Progression Markers Initiative cohort study. Patients were evaluated at baseline and at the 60-month follow-up, with validated clinical scales, including the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), Montreal Cognitive Assessment (MoCA), and the Movement Disorder Society-Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III). Patients were dichotomized using RBDSQ item 2, which inquires whether they frequently experience aggression in their dreams. Regression analyses were used to assess whether frequent aggressive dreams at baseline predicted longitudinal changes in MDS-UPDRS III and MoCA scores as well as progression to Hoehn and Yahr stage 3 (H&Y ≥ 3) and cognitive impairment. Of the patients, 58/224 (25.9%) reported frequent aggressive dreams at baseline. Aggressive dreams predicted a faster increase in MDS-UPDRS III scores (β=4.64; P= 0.007) and a faster decrease in MoCA scores (β=-1.49; P= 0.001). Furthermore, they conferred a 6-fold and 2-fold risk for progressing to H&Y ≥ 3 (odds ratio [OR]=5.82; P= 0.005) and cognitive impairment (OR,2.35; P= 0.023) within 60 months. These associations remained robust when adjusting for potential confounders. This study demonstrates for the first time that frequent aggressive dreams in newly diagnosed PD may independently predict early motor and cognitive decline.

Diagnostic value of the REM sleep behavior disorder screening questionnaire in Parkinson's disease

Objective To investigate the apathy and neuropsychological characteristics of newly diagnosed Parkinson's disease (PD) patients. Methods Eighty-two newly diagnosed PD patients and 30 matched healthy controls by age, sex and education level were recruited in the present study.Apathy was assessed using Apathy Evaluation Scale (AES) and related factors, including age, sex, education level and disease duration were simultaneously evaluated.Unified Parkinson's Disease Rating Scale (UPDRS), Hamilton Depression Rating Scale (HAMD), as well as Montreal Cognitive Assessment (MoCA) were employed in order to respectively evaluate the motor function, depression and cognition. Results The AES scores in the PD patients were significantly higher when compared to the healthy controls. The prevalence of apathy and depression in the PD patients was 51.2%(42/82) and 19.5%(16/82), respectively. There were no statistically significant differences in age, sex, education level, UPDRS-Ⅱ/Ⅲ scores and MoCA scores between apathy (n=42) and no-apathy (n=40) PD patients (P>0.05), while the statistically significant difference in HAMD scores between apathy (n=42) and no-apathy (n=40)PD patients was shown (the HAMD scores of apathy PD patients were 10.61±3.30, the HAMD scores of no-apathy PD patients were 5.96±1.90, t=7.87, P<0.05). The correlation analysis indicated that there were no correlations between AES scores and the related factors, including age, education level, disease duration and UPDRS-Ⅱ/Ⅲ scores, but AES scores were positively correlated with HAMD scores. Conclusion In newly diagnosed PD patients, the apathy is independent of depression, motor dysfunction, as well as cognitive impairment, which may be an early signal for PD. Key words: Parkinson disease; Apathy; Neuropsychological test; Newly diagnosed

BackgroundSex-related differences in non-motor Parkinson’s disease (PD) symptoms have been reported. However, many previous studies lack diversity and their results may not be generalisable.AimTo investigate sex-related non-motor symptom differences in...

Background: Different factors influence severity, progression, and outcomes in Parkinson's disease (PD). Lack of standardized clinical assessment limits comparison of outcomes and availability of well-characterized cohorts for collaborative studies.Methods: Structured clinical documentation support (SCDS) was developed within the DNA Predictions to Improve Neurological Health (DodoNA) project to standardize clinical assessment and identify molecular predictors of disease progression. The Longitudinal Clinical and Genetic Study of Parkinson's Disease (LONG-PD) was launched within the Genetic Epidemiology of Parkinson's disease (GEoPD) consortium using a Research Electronic Data Capture (REDCap) format mirroring the DodoNA SCDS. Demographics, education, exposures, age at onset (AAO), Unified Parkinson's Disease Rating Scale (UPDRS) parts I-VI or Movement Disorders Society (MDS)–UPDRS, Montreal Cognitive Assessment (MoCA)/Short Test of Mental Status (STMS)/Mini Mental State Examination (MMSE), Geriatric Depression Scale (GDS), Epworth Sleepiness Scale (ESS), dopaminergic therapy, family history, nursing home placement, death and blood samples were collected. DodoNA participants (396) with 6 years of follow-up and 346 LONG-PD participants with up to 3 years of follow-up were analyzed using group-based trajectory modeling (GBTM) focused on: AAO, education, family history, MMSE/MoCA/STMS, UPDRS II-II, UPDRS-III tremor and bradykinesia sub-scores, Hoehn and Yahr staging (H&Y) stage, disease subtype, dopaminergic therapy, and presence of autonomic symptoms. The analysis was performed with either cohort as the training/test set.Results: Patients are classified into slowly and rapidly progressing courses by AAO, MMSE score, H &Y stage, UPDRS-III tremor and bradykinesia sub-scores relatively early in the disease course. Late AAO and male sex assigned patients to the rapidly progressing group, whereas tremor to the slower progressing group. Classification is independent of which cohort serves as the training set. Frequencies of disease-causing variants in LRRK2 and GBA were 1.89 and 2.96%, respectively.Conclusions: Standardized clinical assessment provides accurate phenotypic characterization in pragmatic clinical settings. Trajectory analysis identified two different trajectories of disease progression and determinants of classification. Accurate phenotypic characterization is essential in interpreting genomic information that is generated within consortia, such as the GEoPD, formed to understand the genetic epidemiology of PD. Furthermore, the LONGPD study protocol has served as the prototype for collecting standardized phenotypic information at GEoPD sites. With genomic analysis, this will elucidate disease etiology and lead to targeted therapies that can improve disease outcomes.