Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease.

BACKGROUND: Real-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to disease progression. OBJECTIVES: The aim was to identify real-world mobility measures that reflect PD severity and show discriminant ability and sensitivity to disease progression, compared to the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scale. METHODS: Multicenter real-world continuous (24/7) digital mobility data from 587 persons with PD and 68 matched healthy controls were collected using an accelerometer adhered to the lower back. Machine learning feature selection and regression algorithms evaluated associations of the digital measures using the MDS-UPDRS (I-III). Binary logistic regression assessed discriminatory value using controls, and longitudinal observational data from a subgroup (n = 33) evaluated sensitivity to change over time. RESULTS: Digital measures were only moderately correlated with the MDS-UPDRS (part II-r = 0.60 and parts I and III-r = 0.50). Most associated measures reflected activity quantity and distribution patterns. A model with 14 digital measures accurately distinguished recently diagnosed persons with PD from healthy controls (81.1%, area under the curve: 0.87); digital measures showed larger effect sizes (Cohen's d: [0.19-0.66]), for change over time than any of the MDS-UPDRS parts (Cohen's d: [0.04-0.12]). CONCLUSIONS: Real-world mobility measures are moderately associated with clinical assessments, suggesting that they capture different aspects of motor capacity and function. Digital mobility measures are sensitive to early-stage disease and to disease progression, to a larger degree than conventional clinical assessments, demonstrating their utility, primarily for clinical trials but ultimately also for clinical care. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Glucocerebrosidase Activity is not Associated with Parkinson's Disease Risk or Severity.

BACKGROUND: Mutations in the GBA gene, which encodes the lysosomal enzyme glucocerebrosidase (GCase), are risk factors for Parkinson's disease (PD). OBJECTIVE: To explore the association between GCase activity, PD phenotype, and probability for prodromal PD among carriers of mutations in the GBA and LRRK2 genes. METHODS: Participants were genotyped for the G2019S-LRRK2 and nine GBA mutations common in Ashkenazi Jews. Performance-based measures enabling the calculation of the Movement Disorder Society (MDS) prodromal probability score were collected. RESULTS: One hundred and seventy PD patients (102 GBA-PD, 38 LRRK2-PD, and 30 idiopathic PD) and 221 non-manifesting carriers (NMC) (129 GBA-NMC, 45 LRRK2-NMC, 15 GBA-LRRK2-NMC, and 32 healthy controls) participated in this study. GCase activity was lower among GBA-PD (3.15 ± 0.85 µmol/L/h), GBA-NMC (3.23 ± 0.91 µmol/L/h), and GBA-LRRK2-NMC (3.20 ± 0.93 µmol/L/h) compared to the other groups of participants, with no correlation to clinical phenotype. CONCLUSIONS: Low GCase activity does not explain the clinical phenotype or risk for prodromal PD in this cohort. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Detecting Sensitive Mobility Features for Parkinson's Disease Stages Via Machine Learning.

BACKGROUND: It is not clear how specific gait measures reflect disease severity across the disease spectrum in Parkinson's disease (PD). OBJECTIVE: To identify the gait and mobility measures that are most sensitive and reflective of PD motor stages and determine the optimal sensor location in each disease stage. METHODS: Cross-sectional wearable-sensor records were collected in 332 patients with PD (Hoehn and Yahr scale I-III) and 100 age-matched healthy controls. Sensors were adhered to the participant's lower back, bilateral ankles, and wrists. Study participants walked in a ~15-meter corridor for 1 minute under two walking conditions: (1) preferred, usual walking speed and (2) walking while engaging in a cognitive task (dual-task). A subgroup (n = 303, 67% PD) also performed the Timed Up and Go test. Multiple machine-learning feature selection and classification algorithms were applied to discriminate between controls and PD and between the different PD severity stages. RESULTS: High discriminatory values were found between motor disease stages with mean sensitivity in the range 72%-83%, specificity 69%-80%, and area under the curve (AUC) 0.76-0.90. Measures from upper-limb sensors best discriminated controls from early PD, turning measures obtained from the trunk sensor were prominent in mid-stage PD, and stride timing and regularity were discriminative in more advanced stages. CONCLUSIONS: Applying machine-learning to multiple, wearable-derived features reveals that different measures of gait and mobility are associated with and discriminate distinct stages of PD. These disparate feature sets can augment the objective monitoring of disease progression and may be useful for cohort selection and power analyses in clinical trials of PD. © 2021 International Parkinson and Movement Disorder Society.

Mild cognitive impairment among LRRK2 and GBA1 patients with Parkinson's disease.

BACKGROUND: Mild cognitive impairment (MCI) is common in Parkinson's disease (PD). We aimed to assess the incidence of MCI among patients with PD, carriers of mutations in LRRK2 and GBA1 genes, based on the movement disorder society (MDS) criteria for the diagnosis of MCI in early-stage PD. METHODS: Patients with PD were included if they scored ≤2 on the Hoehn and Yahr and ≤6 years since motor symptom onset. A group of age and gender matched healthy adults served as controls. A neuropsychological cognitive battery was used covering five cognitive domains (executive functions, working memory, memory, visuospatial and language). MCI was explored while applying two methods (level I and II). Frequency of MCI was assessed in comparison between groups. RESULTS: 70 patients with idiopathic PD (iPD) (68 % males), 42 patients with LRRK2-PD (61 % males), 83 patients with GBA1-PD (63 % males) and 132 age and gender matched controls (61 % males), participated in this study. PD groups were similar in clinical characteristics. Level I criteria were positive in 57.5 % of iPD, 43 % of LRRK2-PD and 63.4 % of the GBA1-PD (p = 0.071). Level II criteria was met by 39 % of iPD, 14 % LRRK2-PD and 41 % of GBA1-PD (p < 0.001), when using a 2 standard-deviation (SD) threshold. GBA1-PD and iPD showed impairments on multiple domains even in the more conservative 2 SD, reflecting MCI. CONCLUSIONS: The majority of our PD cohort was classified as MCI when assessed with strict criteria. GBA1-PD and iPD showed a more widespread pattern of MCI compared with LRRK2-PD.

The Influence of GBA and LRRK2 on Mood Disorders in Parkinson's Disease.

Background: Mood disorders have emerged as major non-motor comorbidities in Parkinson's disease (PD) even at the prodromal stage of the disease. Mutations in the LRRK2 and GBA genes are common among Ashkenazi Jews, with more severe phenotype reported for GBA-PD. Objective: To explore the association between genetic status and mood related disorders before and after diagnosis of PD and the association between mood-related medications, phenotype, and genetic status. Methods: Participants were genotyped for mutations in the LRRK2 and GBA genes. State of depression, anxiety and non-motor features were evaluated using validated questionnaires. History of mood disorders prior to diagnosis of PD and use of mood-related medications were assessed. Results: The study included 105 idiopathic PD (iPD), 55 LRRK2-PD and 94 GBA-PD. Scores on mood related questionnaires and frequency of depression and anxiety before diagnosis were similar between the groups (p>0.05). However, more GBA-PD patients used mood related medications before PD diagnosis than LRRK2-PD and iPD (16.5% vs 7.1% and 8.2%, p=0.044). LRRK2-PD and GBA-PD receiving mood-related medications at time of assessment had worse motor and non-motor phenotype compared to those that did not (p<0.05). LRRK2-PD receiving mood related-medications at time of assessment, scored higher on mood-related questionnaires compared to LRRK2-PD not receiving such medications (p<0.04). Conclusions: Prodromal GBA-PD are more frequently treated with mood related-medications despite equal rates of reported mood-related disorders, while LRRK2-PD with mood-related disorders experience high rates of anxiety and depression despite treatment, attesting to the need of more precise assessment and treatment of these genetic subgroups.

Prevalence of ten LRRK2 variants in Parkinson's disease: A comprehensive review.

INTRODUCTION: Variants in the leucine-rich repeat kinase 2 gene (LRRK2) are risk factors for Parkinson's disease (PD), but their prevalence varies geographically, reflecting the locations of founder events and dispersion of founders' descendants. METHODS: A comprehensive literature review was conducted to identify studies providing prevalence estimates for any of ten variants in LRRK2 (G2019S, R1441C, R1441G, R1441H, I2020T, N1437H, Y1699C, S1761R, G2385R, R1628P) among individuals with PD globally. We calculated crude country-specific variant prevalence estimates and, when possible, adjusted estimates for ethno-racial composition. For clinic-based studies, probands were used over other familial cases, whereas for population-based studies, all PD cases were used. RESULTS: The analysis included 161 articles from 52 countries yielding 581 prevalence estimates across the ten variants. G2019S was the most common variant, exceeding 1.0% in 26 of 51 countries with estimates. The other variants were far less common. G2385R and R1628P were observed almost exclusively in East Asian countries, where they were found in ∼5-10% of cases. All prevalence estimates adjusted for ethno-racial composition were lower than their unadjusted counterparts, although data permitting this adjustment was only available for six countries. CONCLUSIONS: Except for G2019S, the LRRK2 variants covered in this review were uncommon in most countries studied. However, there were countries with higher prevalence for some variants, reflecting the uneven geographic distribution of LRRK2 variants. The fact that ethno-racial group‒adjusted estimates were lower than crude estimates suggests that estimates derived largely from clinic-based studies may overstate the true prevalence of some LRRK2 variants in PD.

Quantitative digital clock drawing test as a sensitive tool to detect subtle cognitive impairments in early stage Parkinson's disease.

INTRODUCTION: The prevalence of subtle cognitive decline in the early stages of Parkinson's Disease (PD) is common and is thought to be even greater in patients carrying genetic mutations in the GBA gene. Current cognitive tests often lack sensitivity to identify subtle impairments. Technological advancements may offer greater precision. We explored the utility of a digitized cognitive clock-drawing test to assess cognition in patients with PD compared to healthy controls (HC) and its sensitivity compared to that of standardized neuropsychological tests. Further, we investigated the existence of a cognitive profile based on genotype. METHODS: The study included 75 early stage PD patients (24 with GBA-PD, 23 LRRK2-PD, 28 idiopathic PD cases) and 59 HC. Participants underwent a cognitive assessment which included the Montreal Cognitive Assessment (MoCA), the Color Trails Test (CTT) and a digital clock drawing test (DCTclock). RESULTS: Patients with PD presented lower scores than HC on all cognitive tests. The DCTclock best discriminated PD from HC (AUC: 0.807) compared to the MoCA (0.590) and CTT (0.636 and 0.717 for CTT-1 and CTT-2 respectively). In-depth quantitative analysis of the DCTclock revealed that LRRK2-PD showed better performance than other PD sub-groups. CONCLUSION: The use of quantitative digital cognitive assessment showed greater sensitivity in identifying subtle cognitive decline than the current standardized tests. Differences in cognitive profiles were observed based on genotype. The identification of early cognitive decline may improve the clinical management of PD patients and be useful for cognitive related clinical trials.

Mutations in GBA and LRRK2 Are Not Associated with Increased Inflammatory Markers.

BACKGROUND: Inflammation is an integral part of neurodegeneration including in Parkinson's disease (PD). Ashkenazi Jews have high rates of genetic PD with divergent phenotypes among GBA-PD and LRRK2-PD. The role of inflammation in the prodromal phase of PD and the association with disease phenotype has yet to be elucidated. OBJECTIVE: To assess central and peripheral cytokines among PD patients with mutations in the LRRK2 and GBA genes and among non-manifesting carriers (NMC) of these mutations in order to determine the role of inflammation in genetic PD. METHODS: The following cytokines were assessed from peripheral blood and cerebrospinal fluid (CSF): TNF-α, IL-1ß, IL-2, IL-4, IL-6, IL-8, IL-10 and INF- γ. A comprehensive intake including general medical conditions, use of anti-inflammatory treatments, motor and cognitive assessments and additional laboratory measures were recorded, enabling the construction of the MDS probable prodromal score. RESULTS: Data from 362 participants was collected: 31 idiopathic PD (iPD), 30 LRRK2-PD, 77 GBA-PD, 3 homozygote GBA-PD, 3 GBA-LRRK2-PD, 67 LRRK2-NMC, 105 GBA-NMC, 14 LRRK2-GBA-NMC, and 32 healthy controls. No between-group differences in peripheral or CSF cytokines were detected. No correlation between disease characteristics or risk for prodromal PD could be associated with any inflammatory measure. CONCLUSION: In this study, we could not detect any evidence on dysregulated immune response among GBA and LRRK2 PD patients and non-manifesting mutation carriers.

Glucosylceramide in cerebrospinal fluid of patients with GBA-associated and idiopathic Parkinson's disease enrolled in PPMI.

Protein-coding variants in the GBA gene modulate susceptibility and progression in ~10% of patients with Parkinson's disease (PD). GBA encodes the ß-glucocerebrosidase enzyme that hydrolyzes glucosylceramide. We hypothesized that GBA mutations will lead to glucosylceramide accumulation in cerebrospinal fluid (CSF). Glucosylceramide, ceramide, sphingomyelin, and lactosylceramide levels were measured by liquid chromatography-tandem mass spectrometry in CSF of 411 participants from the Parkinson's Progression Markers Initiative (PPMI) cohort, including early stage, de novo PD patients with abnormal dopamine transporter neuroimaging and healthy controls. Forty-four PD patients carried protein-coding GBA variants (GBA-PD) and 227 carried wild-type alleles (idiopathic PD). The glucosylceramide fraction was increased (P = 0.0001), and the sphingomyelin fraction (a downstream metabolite) was reduced (P = 0.0001) in CSF of GBA-PD patients compared to healthy controls. The ceramide fraction was unchanged, and lactosylceramide was below detection limits. We then used the ratio of glucosylceramide to sphingomyelin (the GlcCer/SM ratio) to explore whether these two sphingolipid fractions altered in GBA-PD were useful for stratifying idiopathic PD patients. Idiopathic PD patients in the top quartile of GlcCer/SM ratios at baseline showed a more rapid decline in Montreal Cognitive Assessment scores during longitudinal follow-up compared to those in the lowest quartile with a P-value of 0.036. The GlcCer/SM ratio was negatively associated with α-synuclein levels in CSF of PD patients. This study highlights glucosylceramide as a pathway biomarker for GBA-PD patients and the GlcCer/SM ratio as a potential stratification tool for clinical trials of idiopathic PD patients. Our sphingolipids data together with the clinical, imaging, omics, and genetic characterization of PPMI will contribute a useful resource for multi-modal biomarkers development.

Neuropathologic correlates of amyloid and dopamine transporter imaging in Lewy body disease.

OBJECTIVE: To develop imaging biomarkers of diseases in the Lewy body spectrum and to validate these markers against postmortem neuropathologic findings. METHODS: Four cognitively normal participants with Parkinson disease (PD), 4 with PD with cognitive impairments, and 10 with dementia with Lewy bodies underwent amyloid imaging with [11C]Pittsburgh compound B (PiB) and dopamine transporter (DAT) imaging with [11C]Altropane. All 18 had annual neurologic examinations. All cognitively normal participants with PD developed cognitive impairment before death. Neuropathologic examinations assessed and scored Braak Lewy bodies, Thal distribution of amyloid, Consortium to Establish a Registry for Alzheimer's Disease neuritic amyloid plaques, Braak neurofibrillary tangles, and cerebral amyloid angiopathy, as well as total amyloid plaque burden in the superior frontal, superior parietal, occipital, and inferior temporal cortical regions. PET data were expressed as the standardized uptake value ratio with cerebellar reference. Analyses accounted for the interval between imaging and autopsy. RESULTS: All 18 patients met neuropathologic criteria for Lewy body disease; the DAT concentration was low in each case. All patients with elevated [11C]PiB retention measured in a neocortical aggregate had ß-amyloid deposits at autopsy. [11C]PiB retention significantly correlated with neuritic plaque burden and with total plaque burden. [11C]PiB retention also significantly correlated with the severity of both Braak stages of neurofibrillary tangle and Lewy body scores. Neuritic plaque burden was significantly associated with neurofibrillary tangle pathology. CONCLUSION: Antemortem [11C]Altropane PET is a sensitive measure of substantia nigra degeneration. [11C]PiB scans accurately reflect cortical amyloid deposits seen at autopsy. These findings support the use of molecular imaging in the evaluation of patients with Lewy body diseases.