Microstructure of Brain Nuclei in Early Parkinson's Disease: Longitudinal Diffusion Kurtosis Imaging.

BACKGROUND: Diffusion kurtosis imaging provides in vivo measurement of microstructural tissue characteristics and could help guide management of Parkinson's disease. OBJECTIVE: To investigate longitudinal diffusion kurtosis imaging changes on magnetic resonance imaging in the deep grey nuclei in people with early Parkinson's disease over two years, and whether they correlate with disease progression. METHODS: We conducted a longitudinal case-control study of early Parkinson's disease. 262 people (Parkinson's disease: n = 185, aged 67.5±9.1 years; 43% female; healthy controls: n = 77, aged 66.6±8.1 years; 53% female) underwent diffusion kurtosis imaging and clinical assessment at baseline and two-year timepoints. We automatically segmented five nuclei, comparing the mean kurtosis and other diffusion kurtosis imaging indices between groups and over time using repeated-measures analysis of variance, and Pearson correlation with the two-year change in Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III. RESULTS: At baseline, mean kurtosis was higher in Parkinson's disease than controls in the substantia nigra, putamen, thalamus and globus pallidus when adjusting for age, sex, and levodopa equivalent daily dose (p < 0.027). These differences grew over two years, with mean kurtosis increasing for the Parkinson's disease group while remaining stable for the control group; evident in significant "group ×time" interaction effects for the putamen, thalamus and globus pallidus (ηp2= 0.08-0.11, p < 0.015). However, we did not detect significant correlations between increasing mean kurtosis and declining motor function in the Parkinson's disease group. CONCLUSION: Diffusion kurtosis imaging of specific grey matter structures shows abnormal microstructure in PD at baseline and abnormal progression in PD over two years.

Poor sleep quality is associated with fatigue and depression in early Parkinson's disease: A longitudinal study in the PALS cohort.

Background: Sleep disorders are common in Parkinson's disease (PD). However, the longitudinal relationship between sleep quality and the other non-motor symptoms of PD has not been well characterized, especially in early PD. Objective: To explore the value of baseline sleep quality in predicting the progression of other non-motor symptoms in early PD. Methods: 109 early PD patients were recruited to the study. Patients were stratified into good and poor sleepers using the Pittsburgh Sleep Quality Index (PSQI). Assessments performed at baseline and 1 year follow-up included the Epworth Sleepiness Scale, Fatigue Severity Scale, Non-Motor Symptom Scale, Geriatric Depression Scale, Hospital Anxiety and Depression Scale, Apathy Scale, Montreal Cognitive Assessment and detailed neuropsychological assessments. Multivariable linear regression was performed at baseline to investigate differences in clinical scores between poor and good sleepers, while multivariable regression models were used to investigate associations between sleep quality and progression of test scores at 1 year follow-up. Results: 59 poor sleepers and 50 good sleepers were identified. At baseline, poor sleepers had greater HADS anxiety scores (p = 0.013) [2.99 (95% CI 2.26, 3.73)] than good sleepers [1.59 (95% CI 0.75, 2.42)]. After 1 year, poor sleepers had greater fatigue (FSS scores +3.60 as compared to -2.93 in good sleepers, p = 0.007) and depression (GDS scores +0.42 as compared to -0.70, p = 0.006). Conclusion: This study shows a longitudinal association between sleep quality, fatigue, and depression in early PD patients, independent of medication effect and disease severity, this may support the hypothesis that a common serotonergic pathway is implicated in these non-motor symptoms.

Subjective cognitive Complaints in early Parkinson's disease patients with normal cognition are associated with affective symptoms.

INTRODUCTION: Subjective cognitive complaints (SCC) and affective symptoms are highly prevalent in Parkinson's Disease (PD). In early PD, SCC prevalence and its affective correlates, using recommended Movement Disorders Society (MDS) Level II Criteria to define the underlying cognitive impairment, has not been previously explored. METHODS: We recruited 121 participants with early PD from two tertiary hospitals in Singapore. The presence of SCC was defined using a Non-Motor Symptoms Scale Domain-5 Score ≥1. Comprehensive neuropsychological testing was conducted with Mild Cognitive Impairment (PD-MCI) defined using recommended MDS Level II Criteria. Affective symptoms were assessed using the Hospital Anxiety Depression Scale (HADS), Geriatric Depression Scale (GDS) and Apathy Scale (AS). Analysis using multivariable linear regression model was performed. RESULTS: In our early PD cohort, SCC prevalence independent of underlying cognitive status was 38.8%. Prevalence of SCC in cognitively impaired and cognitively normal participants was 10.7% and 28.1% respectively (р = 0.241). In cognitively normal PD participants, multivariable linear regression analysis revealed that SCC was significantly associated with anxiety (ß = 0.28, 95% CI = 0.09-0.79, p = 0.014), depression (ß = 0.31, 95% CI = 0.10-0.59, p = 0.006) and apathy (ß = 0.32, 95% CI = 1.15-5.98, p = 0.004). Such an association was not found in cognitively impaired PD participants. CONCLUSION: SCC is highly prevalent even in early PD. Its implications in early PD differ depending on underlying cognitive status. SCC in cognitively impaired participants underestimates the true prevalence of PD-MCI. In contrast, SCC in cognitively normal participants is suggestive of an underlying affective disorder.

Corrigendum: Increased Activation of Default Mode Network in Early Parkinson's With Excessive Daytime Sleepiness.

[This corrects the article DOI: 10.3389/fnins.2019.01334.].

Utility of plasma Neurofilament light as a diagnostic and prognostic biomarker of the postural instability gait disorder motor subtype in early Parkinson's disease.

BACKGROUND: The main motor subtypes of Parkinson's disease (PD) include tremor-dominant (TD) and postural instability gait disorder (PIGD), with varying disease course that warrant the development of biomarkers capable of predicting progression according to motor subtype. The PIGD subtype is associated with a poorer prognosis, hence identification of a biomarker associated with PIGD is clinically relevant. Neurofilament light (NfL) chain is a potential biomarker of disease severity in neurological disorders including PD. However, no study has investigated NfL and PD motor subtypes. Here, we aimed to investigate the diagnostic and prognostic utility of plasma NfL for PD motor subtypes in early Parkinson's disease. Given the higher risk for cognitive and motor decline in PIGD, we hypothesized that plasma NfL is a potential biomarker for PIGD. METHODS: Plasma NfL was measured in 199 participants (149 PD and 50 healthy controls, HC) using an ultrasensitive single molecule array. Patients were classified into TD or PIGD based on MDS-UPDRS components. After 2 years, 115 patients were reassessed. Association between NfL and clinical measures in PIGD and TD at baseline and at 2-year follow-up were analysed. RESULTS: At baseline, plasma NfL levels were higher in PD than HC (8.8 ± 3.4 vs 16.2 ± 7.6 pg/ml, p < 0.0001), and differentiated PD from HC with a good diagnostic accuracy (AUC = 0.833, p < 0.001). At 2 years, NfL was higher in PIGD than TD (18.4 ± 14.5 vs 12.6 ± 4.4 pg/ml, p = 0.039). Within the PIGD group, higher NfL associated significantly with worse global cognition and UPDRS motor scores at baseline, and was able to predict motor and cognitive decline at a mean follow-up duration of 1.9 years, controlled for age, sex and disease duration. CONCLUSIONS: In this longitudinal study, we demonstrated for the first time the potential utility of plasma NfL as a diagnostic and prognostic biomarker in PIGD even at early stages of PD. These important novel findings will require further confirmation in larger, longitudinal PD cohorts.

Plasma ubiquitin C-terminal hydrolase L1 levels reflect disease stage and motor severity in Parkinson's disease.

Parkinson's disease (PD) is characterized by Lewy bodies containing α-synuclein and ubiquitin aggregates, their co-occurrence possibly linked to a failure of the ubiquitin proteasome system. Ubiquitin C-terminal hydrolase L1 (UCHL1) plays an important role in maintenance of nervous system integrity, and overexpression of UCHL1 has been shown to increase ubiquitin levels within neurons. While cerebrospinal fluid ubiquitin levels were reported to be lower in PD vs controls, plasma UCHL1 levels and their relationship with clinical measures in PD has not been reported. We measured plasma UCHL1 levels using single molecule array (Simoa) in 291 subjects (242 PD and 49 healthy controls, HC). We found that UCHL1 levels were significantly higher in PD patients at moderate stages (Hoehn and Yahr, H&Y stage >2) vs milder PD (H&Y ≤2, p<0.001) and HC (p=0.001). There was no significant difference in UCHL1 levels between PD patients at H&Y stages ≤2 vs HC. Across all PD patients, UCHL1 correlated significantly with UPDRS Part III motor scores (ß=3.87, 95% CI=0.43-7.31, p=0.028), but not with global cognition. Overall, we found that UCHL1 correlates with motor function in PD, with higher levels seen in later disease stages. These findings will be validated in longitudinal studies.

Physical Activity Improves Anxiety and Apathy in Early Parkinson's Disease: A Longitudinal Follow-Up Study.

Objective: In a prospective study, we investigated the association between physical activity and various motor, non-motor outcomes, and quality of life in early Parkinson's disease (PD) participants in the PD Longitudinal Singapore Study. Background: Prospective studies that examined the association between physical activity and motor and non-motor domains in early PD are lacking. Methods: 121 PD participants were followed-up prospectively to evaluate the association of physical activity with various symptom domains. The Physical Activity Scale for the Elderly (PASE) was used to measure physical activity annually. PD-related symptoms were categorized by motor, non-motor, and quality of life measures. Multivariate regression with gain score analysis was performed to understand the association of baseline PASE scores with the change of each variable at 1-year follow-up. Results: Higher baseline PASE scores (greater activity) were associated with a younger age, lower MDS-UPDRS motor scores, a smaller levodopa equivalent daily dose, better attention and memory scores, and better QoL. Activity scores in early PD declined on follow-up. Multivariate analysis revealed higher baseline physical activity to be associated with decreased anxiety and apathy scores at 1-year follow-up, after adjusting for demographic variables and medications. Conclusion: We demonstrated that higher baseline physical activity was associated with improved anxiety and apathy symptoms in early PD over a 1-year period.

A Wearable, Patient-Adaptive Freezing of Gait Detection System for Biofeedback Cueing in Parkinson's Disease.

Freezing of Gait (FoG) is a common motor-related impairment among Parkinson's disease patients, which substantially reduces their quality of life and puts them at risk of falls. These patients benefit from wearable FoG detection systems that provide timely biofeedback cues and hence help them regain control over their gait. Unfortunately, the systems proposed thus far are bulky and obtrusive when worn. The objective of this paper is to demonstrate the first integration of an FoG detection system into a single sensor node. To achieve such an integration, features with low computational load are selected and dedicated hardware is designed that limits area and memory utilization. Classification is achieved with a neural network that is capable of learning in real time and thus allows the system to adapt to a patient during run-time. A small form factor FPGA implements the feature extraction and classification, whereas a custom PCB integrates the system into a single node. The system fits into a 4.5 × 3.5 × 1.5 cm 3 housing case, weighs 32 g, and achieves 95.6% sensitivity and 90.2% specificity when adapted to a patient. Biofeedback cues are provided either through auditory or somatosensory means and the system can remain operational for longer than 9 h while providing cues. The proposed system is highly competitive in terms of classification performance and excels with respect to wearability and real-time patient adaptivity.

Increased Activation of Default Mode Network in Early Parkinson's With Excessive Daytime Sleepiness.

BACKGROUND AND OBJECTIVES: The underlying neuropathology of excessive daytime sleepiness (EDS) remains elusive in Parkinson's disease (PD). We aim to investigate neural network changes that underlie EDS in PD. METHODS: Early PD patients comprising eighty-one patients without EDS (EDS-) and seventeen patients with EDS (EDS+) received a resting state functional MRI scan and the Epworth Sleepiness Scale (ESS). Connectivities within the default mode network (DMN), motor and basal ganglia networks were compared between the EDS+ and EDS- groups. Correlations between network connectivity and the severity of EDS were investigated through linear regression. RESULTS: EDS+ patients displayed a trend of increased network connectivity of the posterior DMN (pDMN). A significant positive correlation was found between connectivity of the ventromedial prefrontal cortex in the pDMN and ESS. CONCLUSION: EDS+ patients are likely to display increased activation in the DMN, suggesting neural compensation in early PD or impaired attentiveness due to mechanisms such as mind-wandering.

Serum uric acid level and its association with motor subtypes and non-motor symptoms in early Parkinson's disease: PALS study.

OBJECTIVE: Uric acid has been found to be potentially neuroprotective in Parkinson's disease (PD). We investigated the relationship between serum uric acid levels and both motor and non-motor features in a prospective early PD cohort study. METHODS: Fasting serum uric acid levels were measured from 125 early PD patients. Demographic, clinical characteristics, motor and non-motor assessments were performed. Patients were categorized into three motor subtypes: tremor-dominant (TD), postural instability/gait difficulty (PIGD), and mixed. Non-motor symptoms were classified as present or absent based on the appropriate cut-offs for each non-motor instrument. RESULTS: Most patients had TD (n = 51, 40.8%) and mixed (n = 63, 50.4%) motor subtypes, while a minority had PIGD (n = 11, 8.8%) motor subtype. The mean serum uric acid levels were significantly different between the three motor subtypes (p = 0.0106), with the mixed subtype having the lowest serum uric acid levels. Using the TD subtype as reference, patients with higher serum uric acid levels were less likely to have the mixed (OR = 0.684; p = 0.0312) subtype as opposed to the TD subtype. Uric acid levels were not significantly different between the TD and PIGD subtypes. For non-motor symptoms, higher serum uric acid levels were significantly associated with less fatigue (OR = 0.693; p = 0.0408). CONCLUSION: Higher serum uric acid levels were associated with TD motor subtype and less fatigue in early PD, which could be related to its anti-oxidative properties. Uric acid could be an important biomarker for specific motor features and symptoms of fatigue in PD.