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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.

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%.

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.

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

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

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 (β = 0.28, 95% CI = 0.09–0.79, p = 0.014), depression (β = 0.31, 95% CI = 0.10–0.59, p = 0.006) and apathy (β = 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.

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.

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.

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

Background: There is currently insufficient long-term data on costs of treatment in patients with Parkinson’s disease (PD), which is chronic and progressive, and associated with substantial healthcare costs. Identifying patterns in healthcare utilization and cost may illuminate further discussion on early intervention. Objective: To characterize long-term healthcare utilization and costs of PD in newly diagnosed patients managed by movement disorder specialists. Methods: Using a longitudinal matched-cohort study of linked data from the National Neuroscience Institute Parkinson’s disease and Movement Disorder and healthcare administrative databases in Singapore from 2008–2017, we compared healthcare utilization and costs between patients and controls matched on age, sex, race, and Charlson Comorbidity Index score. Results: 1,162 patients met study inclusion criteria and 1,157 matched controls were identified. The total mean annual healthcare cost (at 2017 costs) was significantly increased in patients compared to controls from years 1–9 post-diagnosis. The increased cost was observed 2 years before diagnosis (USD2322 vs. 2052; p

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.

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.

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%.

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 p 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.

Objective. The aim of this study is to compare Parkinson’s disease (PD) treatment practices by movement disorder (MD) specialists across a decade, and to determine the factors that influence drug choice for the motor symptoms of PD in newly diagnosed drug-naïve patients. Methods. This prospective temporal analysis included patients seen at the National Neuroscience Institute in Singapore and diagnosed with PD by MD specialists in the years 2007 and 2017. Primary outcomes were use of specific PD drugs and changes in drug-prescribing patterns. Descriptive analyses and multivariable logistic regression models determined the extent to which patient characteristics were associated with type of PD treatment. Results. Of 230 patients with PD (mean (SD) age, 66.7 (10.3) years), 131 (57.0%) were male. From 2007 to 2017, the use of ergot dopamine agonists and anticholinergics decreased from 19.3% to 2.0% (P<0.001) and from 12.0% to 2.7% (P=0.004), respectively. The use of monoamine oxidase B inhibitors (MAOBI) increased from 13.3% to 25.2% (P=0.033). The use of levodopa (LD)-sparing strategies decreased nonsignificantly from 33.7% to 24.5% (P=0.133). Overall, 196 (85.2%) patients were initiated on symptomatic monotherapy, with LD being the most commonly prescribed. MAOBI was the most common drug used in combination therapy. Age ≤70 (adjusted OR, 11.9; 95% CI, 4.5–31.5) and Hoehn and Yahr (HY) stage P=0.005). Conclusions. Drug-prescribing patterns in PD have changed significantly through the last decade, influenced by emerging evidence and reports of adverse drug effects. Choosing drugs based on the patient’s age and disease severity remain sound guiding principles across the years. It is important that international and national guidelines for pharmacotherapy in PD be updated consistently throughout different socioeconomic settings to optimize care.

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.

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.

BACKGROUND AND PURPOSE The aim of this study was to examine non-motor symptoms in different Parkinson's disease (PD) motor subtypes and their associations with quality of life (QoL). METHODS A total of 132 patients with early PD with comprehensive motor examinations and non-motor symptom assessments were included. Motor subtypes were classified based on Stebbins' method. Non-motor symptoms were assessed by the Non-Motor Symptom Scale (NMSS) and validated by more comprehensive instruments, including the Pittsburgh Sleep Quality Index (PSQI) and Fatigue Severity Scale (FSS). QoL was measured by the Parkinson's Disease Questionnaire-8. RESULTS We identified 66 patients (50%) with tremor-dominant (TD) subtype, 47 (35.6%) with postural instability and gait disorder (PIGD) subtype and 19 (14.4%) with Intermediate subtype. By comparing NMSS scores, patients with the PIGD subtype had more severe sleep impairment and fatigue (domain 2 score: 5.64 vs. 2.52, P < 0.001), urinary symptoms (domain 7 score: 6.96 vs. 3.48, P = 0.005) and overall more severe non-motor symptoms (NMSS total score: 25.89 vs. 17.27, P = 0.031), compared with patients with the TD subtype. Validation using the PSQI and FSS again suggested that patients with the PIGD subtype had independently and significantly more severe sleep impairment (PSQI score: 5.57 vs. 4.29, P = 0.020) and fatigue (FSS score: 34.81 vs. 25.85, P = 0.003) compared with patients with the TD subtype. Several non-motor symptoms had significant associations with QoL, among which sleep impairment and fatigue (P < 0.0001, partial r2 = 0.273) explained the largest proportion of QoL variability in patients with PD. CONCLUSIONS Patients with the PIGD subtype had more severe sleep impairment, fatigue and urinary disturbance compared with patients with the TD subtype. Sleep impairment and fatigue were the most important factors affecting QoL independent of motor subtypes. Prompt identification and treatment of these non-motor symptoms may improve patients' QoL.

Objective To investigate the impact of diabetes mellitus (DM) on cognitive performance and longitudinal volumetric brain changes in a cohort of cognitively normal mild PD patients. Methods Prospective study of idiopathic PD subjects who underwent baseline and follow-up MRI imaging and neuropsychological assessments at 6 month intervals for 3 years. Subjects were classified based on the presence (PD-DM) or absence of DM (PD-No DM) at baseline. Volumetric analysis was performed using FreeSurfer 5.3 image analysis suite. Brain volume and cognition were compared and analyzed cross-sectionally and longitudinally. Analyses were corrected for intracranial volume. Results There were 65 PD-no DM and 12 PD-DM subjects at baseline with comparable global cognition at baseline. PD-DM subjects had lower cortical grey matter (GM), amygdala, frontal white matter and temporal white matter volumes and higher total white matter hyperintensity and periventricular hyperintensities. After mean follow-up of 29.08 months, there were 51 PD-no DM and 11 PD-DM subjects. PD-DM subjects demonstrated greater decline in MMSE and MOCA scores compared to PD-No DM. PD-DM subjects had a higher rate of atrophy in the cortical WM, particularly in the parietal and occipital white matter. Conclusion Mild PD patients with DM have lower GM and WM volumes at baseline and higher WMH volumes, despite comparable cognitive scores. Longitudinally, DM in PD results in greater rate of cognitive decline, associated with higher WM atrophy.

Background and purpose Mild cognitive impairment (MCI) is associated with pronounced grey matter atrophy in various brain regions. However, the association between atrophy patterns and progression from no cognitive impairment (NCI) to Parkinson's disease (PD)-MCI is not clearly known. We investigated the pattern and progression of atrophy in subcortical structures and its impact on cognition in patients with mild PD. Methods Sixty-five patients with mild PD with baseline and longitudinal clinical and neuropsychological assessments, and structural magnetic resonance imaging scans were studied. Movement Disorder Society Task Force criteria were used to classify patients with PD into PD-NCI (n = 54) and PD-MCI (n = 11). Based on progression over time, those who remained without cognitive impairment were classified as PD-stable (n = 42) and those who converted to MCI over 18 months were classified as PD-converters (n = 12). FreeSurfer was used to measure cortical thickness and subcortical volumes at baseline and follow-up. Results Parkinson's disease-MCI showed baseline thalamus atrophy and progressive atrophy in the thalamus, caudate, presubiculum, cornu ammonis 1 and 2–3, and significant memory and executive dysfunction compared with PD-NCI. PD-converters had greater accumbens atrophy at baseline and progressive atrophy in the thalamus, caudate and accumbens with dysfunctions in memory and executive domains. Conclusions Progression of cognitive impairment in non-demented PD is associated with a specific pattern of subcortical atrophy. Findings from this study will allow future studies to investigate in the role of subcortical structures as a biomarker for PD dementia.

Background Anxiety is prevalent in patients with Parkinson's disease (PD) and may affect patients' quality of life. Yet, little is known about the neural basis of anxiety in PD, and none have used a longitudinal design. Methods 73 patients with mild PD were recruited and followed up for 18 months. A whole-brain analysis was first used to identify brain regions associated with anxiety symptoms, followed by a regional analysis focusing on a priori hypothesised regions at baseline. A multivariate generalized estimating equations analysis was then conducted to determine the longitudinal association between grey matter (GM) volumetric changes of these significant regions and changes of anxiety symptoms. Results At baseline, anxiety symptom severity was associated with decreased GM volumes in the bilateral precuneus and anterior cingulate cortex (ACC). Over 18 months, increased severity of anxiety symptoms was associated with decreased GM volume in the left precuneus and ACC, independent of age, gender, education, depressive symptom severity or use of psychiatric medication. Conclusions These results mainly implicate the precuneus and ACC in the pathogenesis of anxiety in PD. We speculate that these structural changes could reflect the disrupted default mode network due to PD pathology, contributing to spontaneous anxiety-related self-focused thoughts.

Background and purpose This study quantified the total brain and periventricular white matter hyperintensity (WMH) burdens in patients with early Parkinson's disease (PD) and explored their associations with cardiovascular risk factors and cognitive performance. Methods A total of 175 non-demented patients with early PD who had undergone baseline brain magnetic resonance imaging were included. Comprehensive neurocognitive testing was conducted to identify PD with mild cognitive impairment (PD-MCI) and to evaluate performances in individual cognitive domains. Cardiovascular risk was expressed as a modified Framingham 10-year cardiovascular risk score (mFRS). Results A total of 53.7% of this early PD cohort fulfilled the diagnostic criteria for PD-MCI. An increase in mFRS was significantly associated with increases in the total brain WMH (P = 0.015) and periventricular WMH (P = 0.040) burden, independent of age and gender. The periventricular WMH burden was significantly associated with PD-MCI (P = 0.046) in early PD, independent of cardiovascular risk factors. Patients in the 5th quintile of periventricular WMH burden were 8.6 times more likely to have PD-MCI compared with patients in the 1st quintile of periventricular WMH burden (P = 0.004). However, total brain WMH burden was not associated with PD-MCI (P = 0.158). In individual cognitive domains, heavier periventricular WMH burden was associated with worse executive function and visuospatial function independent of cardiovascular risk factors. Conclusion Periventricular WMHs are a useful imaging biomarker for cognitive impairment in early PD. Cardiovascular risk factors, although associated with periventricular WMHs, were unable to fully explain the association between periventricular WMHs and cognitive impairment in early PD.

Histopathological examination of brain tissue is required for better understanding of neurodegenerative conditions such as Parkinson’s disease and related disorders. However, patient willingness remains the greatest hurdle hampering participation in brain donation for research. While there is extensive research being conducted on the subject in West, to the best of our knowledge, there are no studies done in this regard in Asia. This cross-sectional survey was conducted on 105 Parkinson’s disease patients to assess their knowledge, beliefs and attitude towards brain donation in an Asian population. The majority of the participants (78%) acknowledged the importance of donation of brain for research, and 70% believed that their donated brain samples would be handled professionally. Fifty percent participants were willing to consider donating their brain for research. Motivating factors for brain donation included altruism (87%) and contribution to advance medical knowledge (80%). Common reasons for unwillingness towards brain donation were stress for family (30%), disfigurement of body (25%), and having a conservative mindset (23%). About one-third of the participants preferred to be approached for brain donation after their first clinic visit. Most patients preferred either their treating neurologists (66%) or research staff (18%) to discuss brain donation with. Participation for brain donation may be increased further with greater patient and public education to overcome misconceptions and change mindsets.

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.

BACKGROUND While the association between alpha-synuclein gene promoter (Rep1) variability and risk of PD is well established, its association with cognition is unclear. OBJECTIVES To investigate the association between Rep1 and motor and cognitive outcomes in PD. METHODS Rep1 allele lengths were determined in 172 PD patients who were grouped into "long" and "short" carriers according to previous methods. Multivariable regression analysis was performed to investigate the effect of Rep1 length on cognitive and motor scores. RESULTS Long Rep1 allele carriers had significantly lower MMSE (P = 0.010) and higher UPDRS Part III (P = 0.026) and H & Y (P = 0.008) scores compared to short allele carriers (controlled for age, sex, and disease duration). Interaction analyses of Rep1 with apolipoprotein 4 revealed no significant effect on clinical outcomes. CONCLUSIONS PD patients carrying long Rep1 alleles are more impaired on cognitive and motor function independent of apolipoprotein 4 genotype. © 2019 International Parkinson and Movement Disorder Society.

Parkinson’s disease patients are at risk of falls due to freezing of gait (FoG). Wearable detection systems providing biofeedback for aid rely on accurate FoG classifiers, but such algorithms have yet to propose a dedicated hardware implementation. This paper is a first proposal of a dedicated hardware for a real-time FoG feature extractor and classifier on a single chip. The neural network classifier and FoG feature extractor exploit an FoG system’s inherent time-sharing affinity to reduce area consumption which is crucial in wearable applications. The design has been fitted onto a small form-factor 10×10 mm2 Artix-7 FPGA. It consumes 6.716 μJ per classification which surpasses non-dedicated FoG system implementations in terms of efficiency, while remaining competitive with 91.32% and 93.64% in sensitivity and specificity, respectively.