Chronic lymphocytic leukaemia Australasian consensus practice statement.

Chronic lymphocytic leukaemia (CLL) is the most common haematological malignancy in Australia and New Zealand (ANZ). Considerable changes to diagnostic and management algorithms have occurred within the last decade. The availability of next-generation sequencing and measurable residual disease assessment by flow cytometry allow for advanced prognostication and response assessments. Novel therapies, including inhibitors of Bruton's tyrosine kinase (BTKi) and B-cell lymphoma 2 (BCL2) inhibitors, have transformed the treatment landscape for both treatment-naïve and relapsed/refractory disease, particularly for patients with high-risk genetic aberrations. Recommendations regarding appropriate supportive management continue to evolve, and special considerations are required for patients with CLL with respect to the global SARS-CoV-2 pandemic. The unique funding and treatment environments in Australasia highlight the need for specific local guidance with respect to the investigation and management of CLL. This consensus practice statement was developed by a broadly representative group of ANZ experts in CLL with endorsement by peak haematology bodies, with a view to providing this standardised guidance.

Identifying clinical features and blood biomarkers associated with mild cognitive impairment in Parkinson disease using machine learning.

BACKGROUND AND PURPOSE: A broad list of variables associated with mild cognitive impairment (MCI) in Parkinson disease (PD) have been investigated separately. However, there is as yet no study including all of them to assess variable importance. Shapley variable importance cloud (ShapleyVIC) can robustly assess variable importance while accounting for correlation between variables. Objectives of this study were (i) to prioritize the important variables associated with PD-MCI and (ii) to explore new blood biomarkers related to PD-MCI. METHODS: ShapleyVIC-assisted variable selection was used to identify a subset of variables from 41 variables potentially associated with PD-MCI in a cross-sectional study. Backward selection was used to further identify the variables associated with PD-MCI. Relative risk was used to quantify the association of final associated variables and PD-MCI in the final multivariable log-binomial regression model. RESULTS: Among 41 variables analysed, 22 variables were identified as significantly important variables associated with PD-MCI and eight variables were subsequently selected in the final model, indicating fewer years of education, shorter history of hypertension, higher Movement Disorder Society-Unified Parkinson's Disease Rating Scale motor score, higher levels of triglyceride (TG) and apolipoprotein A1 (ApoA1), and SNCA rs6826785 noncarrier status were associated with increased risk of PD-MCI (p < 0.05). CONCLUSIONS: Our study highlighted the strong association between TG, ApoA1, SNCA rs6826785, and PD-MCI by machine learning approach. Screening and management of high TG and ApoA1 levels might help prevent cognitive impairment in early PD patients. SNCA rs6826785 could be a novel therapeutic target for PD-MCI. ShapleyVIC-assisted variable selection is a novel and robust alternative to traditional approaches for future clinical study to prioritize the variables of interest.

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.

Plasma Neurofilament Light Concentration Is Associated with Diffusion-Tensor MRI-Based Measures of Neurodegeneration in Early Parkinson's Disease.

BACKGROUND: Neurofilament light is a marker of axonal degeneration, whose measurement from peripheral blood was recently made possible by new assays. OBJECTIVE: We aimed to determine whether plasma neurofilament light chain (NfL) concentration reflects brain white matter integrity in patients with early Parkinson's disease (PD). METHODS: 137 early PD patients and 51 healthy controls were included. Plasma NfL levels were measured using ultrasensitive single molecule array. 3T MRI including diffusion tensor imaging was acquired for voxelwise analysis of association between NfL and both fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts and subcortical nuclei. RESULTS: A pattern of brain microstructural changes consistent with neurodegeneration was associated with increased plasma NfL in most of the frontal lobe and right internal capsule, with decreased FA and increased MD. The same clusters were also associated with poorer global cognition. A significant cluster in the left putamen was associated with increased NfL, with a significantly greater effect in PD than controls. CONCLUSION: Plasma NfL may be associated with brain microstructure, as measured using diffusion tensor imaging, in patients with early PD. Higher plasma NfL was associated with a frontal pattern of neurodegeneration that also correlates with cognitive performance in our cohort. This may support a future role for plasma NfL as an accessible biomarker for neurodegeneration and cognitive dysfunction in PD.

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.

Biomarker characterization of clinical subtypes of Parkinson Disease.

The biological underpinnings of the PD clusters remain unknown as the existing PD clusters lacks biomarker characterization. We try to identify clinical subtypes of Parkinson Disease (PD) in an Asian cohort and characterize them by comparing clinical assessments, genetic status and blood biochemical markers. A total of 206 PD patients were included from a multi-centre Asian cohort. Hierarchical clustering was performed to generate PD subtypes. Clinical and biological characterization of the subtypes were performed by comparing clinical assessments, allelic distributions of Asian related PD gene (SNCA, LRRK2, Park16, ITPKB, SV2C) and blood biochemical markers. Hierarchical clustering method identified three clusters: cluster A (severe subtype in motor, non-motor and cognitive domains), cluster B (intermediate subtype with cognitive impairment and mild non-motor symptoms) and cluster C (mild subtype and young age of onset). The three clusters had significantly different allele frequencies in two SNPs (Park16 rs6679073 A allele carriers in cluster A B C: 67%, 74%, 89%, p = 0.015; SV2C rs246814 T allele distribution: 7%, 12%, 25%, p = 0.026). Serum homocysteine (Hcy) and C-reactive protein (CRP) levels were also significantly different among three clusters (Mean levels of Hcy and CRP among cluster A B C were: 19.4 ± 4.2, 18.4 ± 5.7, 15.6 ± 5.6, adjusted p = 0.005; 2.5 ± 5.0, 1.5 ± 2.4, 0.9 ± 2.1, adjusted p < 0.0001, respectively). Of the 3 subtypes identified amongst early PD patients, the severe subtype was associated with significantly lower frequency of Park16 and SV2C alleles and higher levels of Hcy and CRP. These biomarkers may be useful to stratify PD subtypes and identify more severe subtypes.

Blood Lipid Biomarkers in Early Parkinson's Disease and Parkinson's Disease with Mild Cognitive Impairment.

BACKGROUND: Lipid biomarkers have potential neuroprotective effects in Parkinson's disease (PD) and there is limited evidence in the field. OBJECTIVE: This study aims to investigate the association between comprehensive blood lipid biomarkers and PD. METHODS: A total of 205 PD patients and 102 non-PD subjects were included from Early Parkinson's disease Longitudinal Singapore (PALS) cohort. We investigated 6 serum lipid biomarkers including total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (Apo A1), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (Apo B). PD patients were further classified into mild cognitive impairment (MCI) and normal cognition (NC) subgroups. We conducted a cross-sectionals study to examine the association between lipids and PD and further explored the relationship between lipids and PD-MCI. RESULTS: PD patients had significantly lower level of lipid panel including TC, TG, HDL-C, Apo A1, LDL-C, and Apo B (all p < 0.05). TC, TG, Apo A1, and Apo B levels were independent protective factors (p < 0.05) for PD in the logistic regression model. PD-MCI group had significantly higher mean TC, TG, and Apo A1 levels compared to PD-NC group. Higher TC, TG, and Apo A1 levels were independent risk factors (p < 0.05) for PD-MCI. CONCLUSION: We demonstrated that PD patients had significantly lower levels of lipid biomarkers while PD-MCI patients had higher levels of TC, TG, and Apo A1. TC, TG, and Apo A1 may be useful biomarkers for PD-MCI.

Longitudinal Study of SNCA Rep1 Polymorphism on Executive Function in Early Parkinson's Disease.

The alpha-synuclein gene promoter (SNCA-Rep1) is associated with Parkinson's disease (PD), but its relationship with performance across individual cognitive domains in early PD is unknown. This study aims to investigate Rep1 polymorphism and longitudinal change in cognition in early PD. In this longitudinal study, Rep1 allele lengths ("long" and "short") were determined in 204 early PD patients. All participants underwent annual neuropsychological assessments and followed up for 3 years. Linear-mixed model was performed to investigate the association of Rep1 status and longitudinal change in individual cognitive domains. At 3 years, significant decline in executive function was observed in long Rep1 allele carriers vs short allele carriers, controlling for potential confounders. This is the first longitudinal study demonstrating that long Rep1 allele carriers are at higher risk for executive dysfunction in early PD.

Detection of Freezing of Gait Using Convolutional Neural Networks and Data From Lower Limb Motion Sensors.

Parkinson's disease (PD) is a chronic, non-reversible neurodegenerative disorder, and freezing of gait (FOG) is one of the most disabling symptoms in PD as it is often the leading cause of falls and injuries that drastically reduces patients' quality of life. In order to monitor continuously and objectively PD patients who suffer from FOG and enable the possibility of on-demand cueing assistance, a sensor-based FOG detection solution can help clinicians manage the disease and help patients overcome freezing episodes. Many recent studies have leveraged deep learning models to detect FOG using signals extracted from inertial measurement unit (IMU) devices. Usually, the latent features and patterns of FOG are discovered from either the time or frequency domain. In this study, we investigated the use of the time-frequency domain by applying the Continuous Wavelet Transform to signals from IMUs placed on the lower limbs of 63 PD patients who suffered from FOG. We built convolutional neural networks to detect the FOG occurrences, and employed the Bayesian Optimisation approach to obtain the hyper-parameters. The results showed that the proposed subject-independent model was able to achieve a geometric mean of 90.7% and a F1 score of 91.5%.

Utility of quantitative susceptibility mapping and diffusion kurtosis imaging in the diagnosis of early Parkinson's disease.

OBJECTIVE: To investigate the utility of quantitative susceptibility mapping (QSM) and diffusion kurtosis imaging (DKI) as complementary tools in characterizing pathological changes in the deep grey nuclei in early Parkinson's disease (PD) and their clinical correlates to aid in diagnosis of PD. METHOD: Patients with a diagnosis of PD made within a year and age-matched healthy controls were recruited. All participants underwent clinical evaluation using the Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) and Hoehn & Yahr stage (H&Y), and brain 3 T MRI including QSM and DKI. Regions-of-interest (ROIs) in the caudate nucleus, putamen, globus pallidus, and medial and lateral substantia nigra (SN) were manually drawn to compare the mean susceptibility (representing iron deposition) and DKI indices (representing restricted water diffusion) between PD patients and healthy controls and in correlation with MDS-UPDRS III and H&Y, focusing on susceptibility value, mean diffusivity (MD) and mean kurtosis (MK). RESULTS: There were forty-seven PD patients (aged 68.7 years, 51% male, disease duration 0.78 years) and 16 healthy controls (aged 67.4 years, 63% male). Susceptibility value was increased in PD in all ROIs except the caudate, and was significantly different after multiple comparison correction in the putamen (PD: 64.75 ppb, HC: 44.61 ppb, p = 0.004). MD was significantly higher in PD in the lateral SN, putamen and caudate, the regions with the lowest susceptibility value. In PD patients, we found significant association between the MDS-UPDRS III score and susceptibility value in the putamen after correcting for age and sex (ß = 0.21, p = 0.003). A composite DKI-QSM diagnostic marker based on these findings successfully differentiated the groups (p < 0.0001) and had "good" classification performance (AUC = 0.88). CONCLUSIONS: QSM and DKI are complementary tools allowing a better understanding of the complex contribution of iron deposition and microstructural changes in the pathophysiology of PD.

Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease.

Background: Various classifications have been proposed to subtype Parkinson's disease (PD) based on their motor phenotypes. However, the stability of these subtypes has not been properly evaluated. Objective: The goal of this study was to understand the distribution of PD motor subtypes, their stability over time, and baseline factors that predicted subtype stability. Methods: Participants (n = 170) from two prospective cohorts were included: the Early PD Longitudinal Singapore (PALS) study and the National Neuroscience Institute Movement Disorders Database. Early PD patients were classified into tremor-dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate subtypes according to the Movement Disorder Society's Unified PD Rating Scale (MDS-UPDRS) criteria and clinically evaluated for three consecutive years. Results: At baseline, 60.6% patients were TD, 12.4% patients were indeterminate, and 27.1% patients were PIGD subtypes (p < 0.05). After 3 years, only 62% of patients in TD and 50% of patients in PIGD subtypes remained stable. The mean levodopa equivalent daily dose (LEDD) was higher in the PIGD subtype (276.92 ± 232.91 mg; p = 0.01). Lower LEDD [p < 0.05, odds ratio (OR) 0.99, 95% confidence interval (CI): 0.98-0.99] and higher TD/PIGD ratios (p < 0.05, OR 1.77, 95% CI: 1.29-2.43) were independent predictors of stability of TD subtype with an area under the curve (AUC) of 0.787 (95%CI: 0.669-0.876), sensitivity = 57.8%, and specificity = 89.7%. Conclusion: Only 50-62% of PD motor subtypes as defined by MDS-UPDRS remained stable over 3 years. TD/PIGD ratio and baseline LEDD were independent predictors for TD subtype stability over 3 years.

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.

SNCA Rep1 microsatellite length influences non-motor symptoms in early Parkinson's disease.

Long alpha-synuclein gene (SNCA) promoter (Rep1) allele-carriers are linked to higher risk for Parkinson's disease (PD) and faster motor progression. Non-motor symptoms including autonomic, neuropsychiatric, and sleep disorders are common in PD. However, the relationship between SNCA Rep1 microsatellite lengths and non-motor symptoms in early PD remains to be elucidated. 171 consecutive early PD patients were recruited from tertiary clinics and genotyped for Rep1. Multivariable regression analyses were performed to examine associations between Rep1 alleles and non-motor outcome scores. Longer Rep1 alleles significantly associated with higher total Non-Motor Symptom Scale (NMSS) scores (p=.006) and Hospital Anxiety and Depression Scale (HADS) depression subscale scores (p=.002), after adjusting for covariates and Bonferroni correction. We demonstrated that SNCA Rep1 allele length influences overall non-motor symptom burden and depression in early PD patients. Further functional studies to evaluate the role of Rep1 in non-dopaminergic systems may unravel new therapeutic targets for non-motor symptoms in PD.

Convolutional Neural Network for Freezing of Gait Detection Leveraging the Continuous Wavelet Transform on Lower Extremities Wearable Sensors Data.

Freezing of Gait is the most disabling gait disturbance in Parkinson's disease. For the past decade, there has been a growing interest in applying machine learning and deep learning models to wearable sensor data to detect Freezing of Gait episodes. In our study, we recruited sixty-seven Parkinson's disease patients who have been suffering from Freezing of Gait, and conducted two clinical assessments while the patients wore two wireless Inertial Measurement Units on their ankles. We converted the recorded time-series sensor data into continuous wavelet transform scalograms and trained a Convolutional Neural Network to detect the freezing episodes. The proposed model achieved a generalisation accuracy of 89.2% and a geometric mean of 88.8%.

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.

Attitude of Asian Parkinson Patients towards Clinical Research and Tissue Donation.

OBJECTIVE: The success of clinical research and tissue donation programs are highly dependent on recruitment of willing volunteers. A comprehensive survey of patient preferences and attitudes can help identify and address barriers hindering the recruitment for research. METHOD: This is a cross-sectional study on 105 Parkinson's disease patients who completed an interviewer-administered questionnaire. RESULTS: Out of 105 respondents, 48% of patients had either already participated in clinical research or were keen to participate. About 80% believed clinical research to be safe for their health and privacy. More than 70% of participants were willing to donate blood, urine, or stool, while 16% were agreeable for cerebrospinal fluid sample donation. Motivating factors for clinical research included altruism (64%) and contribution to advance medical knowledge (64%). Common reasons for unwillingness towards clinical research included the risks involved (43%), time constraints (33%), and mobility challenges (24%). CONCLUSION: The attitude of Singaporean Parkinson patients toward clinical research and tissue donation is encouraging with about half of the participants willing to support clinical research. Three-quarters of patients would support tissue donations. Participation in research may be further increased with greater patient and public education to overcome misconceptions and also by limiting the demands of studies.

Patient attitudes towards brain donation across both neurodegenerative and non-neurodegenerative neurological disorders.

Brain donations are imperative for research; understanding possible barriers to entry is required to improve brain donation rates. While a few surveys have studied attitudes towards brain banking in patients with neurodegenerative disorders, none have surveyed patients with chronic neurological disorders but without neurodegeneration. This cross-sectional study was conducted on 187 participants, with both neurodegenerative (n = 122) and non-neurodegenerative disorders (n = 65), to compare their attitudes and preferences towards brain donation. Encouragingly, patients with non-neurodegenerative disorders were just as likely to consider brain donation as those with neurodegenerative diseases. Approximately half of each group were willing to consider brain donation, and majority of participants across both groups would not be offended if asked to participate in brain donation (71%). Across both groups, altruistic reasons such as desire to advance medical knowledge and benefit to other patients were the main motivating factors for brain donation, while perceived stress for family members, fears of body disfigurement and religious reasons were the main reasons against brain donation. Of note, nearly two-thirds of all participants were agreeable to allow their family to decide on their behalf. Overall, participants with non-neurodegenerative disorders appeared equally likely to consider brain donation as participants with neurodegenerative disorders. This is an important finding as they represent a significant population seen in specialist neurology clinics who may be overlooked in brain donor recruitment and awareness efforts. Healthcare professionals involved in brain banking should consider actively approaching these potential donors and involving their family members in these discussions.

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.