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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 ( η p 2 = 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.

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%.

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.

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

Graphical abstract, Highlights • Putamen susceptibility value was higher in PD than controls one year into diagnosis. • Putamen susceptibility value was associated with clinical motor scores in early PD. • Mean diffusivity revealed greater cellular loss in the lateral substantial nigra. • Putamen and caudate microstructural degradation were driven by radial diffusivity. • A composite putamen-caudate DKI-QSM marker classified early PD from controls., 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 (β = 0.21, p = 0.003). A composite DKI-QSM diagnostic marker based on these findings successfully differentiated the groups (p

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.

We utilized ultrasensitive single molecule technology to measure plasma alpha‐synuclein in 221 subjects (51 controls, 170 PD). Plasma alpha‐synuclein levels were significantly higher in PD than controls (15506.3 vs. 13057.0 pg/mL, P = 0.037), adjusting for age and gender. In PD, alpha‐synuclein levels did not vary by H&Y stage or UPDRS motor scores but were significantly higher in PD patients with poorer cognition (MMSE ≤ 25) than controls (P = 0.016, Bonferroni corrected P = 0.047). Alpha‐synuclein levels quantified using ultrasensitive single molecule technology discriminate PD from controls and correlate with cognitive severity. These preliminary findings require independent validation to determine the utility of this assay.