The Parkinson's disease (PD) research field has seen the advent of several promising biomarkers and a deeper understanding of the clinical features of the disease from the earliest stages of pathology to manifest disease. Despite progress, a biologically based PD staging system does not exist. Such staging would be a useful framework within which to model the disease, develop and validate biomarkers, guide therapeutic development, and inform clinical trials design. We propose that the presence of aggregated neuronal α-synuclein, dopaminergic neuron dysfunction/degeneration, and clinical signs and symptoms identifies a group of individuals that have Lewy body pathology, which in early stages manifests with what is now referred to as prodromal non-motor features and later stages with the manifestations of PD and related Lewy body diseases as defined by clinical diagnostic criteria. Based on the state of the field, we herein propose a definition and staging of PD based on biology. We present the biologic basis for such a staging system and review key assumptions and evidence that support the proposed approach. We identify gaps in knowledge and delineate crucial research priorities that will inform the ultimate integrated biologic staging system for PD.

Now that wearable sensors have become more commonplace, it is possible to monitor individual healthcare-related activity outside the clinic, unleashing potential for early detection of events in diseases such as Parkinson's disease (PD). However, the unsupervised and "open world" nature of this type of data collection make such applications difficult to develop. In this proof-of-concept study, we used inertial sensor data from Verily Study Watches worn by individuals for up to 23 h per day over several months to distinguish between seven subjects with PD and four without. Since motor-related PD symptoms such as bradykinesia and gait abnormalities typically present when a PD subject is walking, we initially used human activity recognition (HAR) techniques to identify walk-like activity in the unconstrained, unlabeled data. We then used these "walk-like" events to train one-dimensional convolutional neural networks (1D-CNNs) to determine the presence of PD. We report classification accuracies near 90% on single 5-s walk-like events and 100% accuracy when taking the majority vote over single-event classifications that span a duration of one day. Though based on a small cohort, this study shows the feasibility of leveraging unconstrained wearable sensor data to accurately detect the presence or absence of PD.

3R/4R-tau species are found in Alzheimer disease (AD) and ∼50% of Lewy body dementias at autopsy (LBD+tau); 4R-tau accumulations are found in progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). Digital image analysis techniques can elucidate patterns of tau pathology more precisely than traditional methods but repeatability across centers is unclear. We calculated regional percentage areas occupied by tau pathological inclusions from the middle frontal cortex (MFC), superior temporal cortex (STC), and angular gyrus (ANG) from cases from the University of Pennsylvania and the University of California San Diego with AD, LBD+tau, PSP, or CBD (n = 150) using QuPath. In both cohorts, AD and LBD+tau had the highest grey and white matter tau burden in the STC (p ≤ 0.04). White matter tau burden was relatively higher in 4R-tauopathies than 3R/4R-tauopathies (p < 0.003). Grey and white matter tau were correlated in all diseases (R2=0.43-0.79, p < 0.04) with the greatest increase of white matter per unit grey matter tau observed in PSP (p < 0.02 both cohorts). Grey matter tau negatively correlated with MMSE in AD and LBD+tau (r = -4.4 to -5.4, p ≤ 0.02). These data demonstrate the feasibility of cross-institutional digital histology studies that generate finely grained measurements of pathology which can be used to support biomarker development and models of disease progression.

Background

Improved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.

Objectives

To examine whether baseline measures and their 1-year change predict longer-term progression in early PD.

Methods

Parkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.

Results

Among 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.

Conclusions

Baseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding.

Background

The penetrance of common genetic risk variants for Parkinson's disease (PD) is low. Pesticide exposure increases PD risk, but how exposure affects penetrance is not well understood.

Objective

To determine the relationship between occupational pesticide exposure and PD in people with LRRK2 and GBA risk variants.

Methods

Participants of the Parkinson's Progression Markers Initiative (PPMI) with a LRRK2-G2019 S or GBA risk variant provided information about occupational pesticide exposure. We compared exposure in carriers with and without PD. Among carriers with PD, we used Cox proportional hazard models to compare time-to impairment in balance, cognition, and activities of daily living (ADLs) between participants with and without prior occupational pesticide exposure.

Results

378 participants with a risk variant provided exposure information; 176 with LRRK2-G2019 S (54 with and 122 without PD) and 202 with GBA variants (47 with and 155 without PD). Twenty-six participants reported pesticide exposure. People with a GBA variant and occupational pesticide exposure had much higher odds of PD (aOR: 5.4, 95% CI 1.7-18.5, p < 0.01). People with a LRRK2 variant and a history of occupational pesticide exposure had non-significantly elevated odds of PD (aOR 1.3, 95% CI 0.4-4.6, p = 0.7). Among those with PD, pesticide exposure was associated with a higher risk of balance problems and cognitive impairment in LRRK2-PD and functional impairment in GBA-PD, although associations were not statistically significant.

Conclusions

Occupational pesticide exposure may increase penetrance of GBA-PD and may be associated with faster symptom progression. Further studies in larger cohorts are necessary.

Cognitive impairment, including dementia, is common in Parkinson's disease (PD). The Mini-Mental State Examination (MMSE) has been recommended as a screening tool for Parkinson's disease dementia (PDD), with values below 26 indicative of possible dementia. Using a detailed neuropsychological battery, we examined the range of cognitive impairment in PD patients with an MMSE score of 26 or higher. In this multicenter, cross-sectional, observational study, we performed neuropsychological testing in a sample of 788 PD patients with MMSE scores of 26 or higher. Evaluation included tests of global cognition, executive function, language, memory, and visuospatial skills. A consensus panel reviewed results for 342 subjects and assigned a diagnosis of no cognitive impairment, mild cognitive impairment, or dementia. Sixty-seven percent of the 788 subjects performed 1.5 standard deviations below the normative mean on at least one test. On eight of the 15 tests, more than 20% of subjects scored 1.5 standard deviations or more below the normative mean. Greatest impairments were found on Hopkins Verbal Learning and Digit Symbol Coding tests. The sensitivity of the MMSE to detect dementia was 45% in a subset of participants who underwent clinical diagnostic procedures. A remarkably wide range of cognitive impairment can be found in PD patients with a relatively high score on the MMSE, including a level of cognitive impairment consistent with dementia. Given these findings, clinicians must be aware of the limitations of the MMSE in detecting cognitive impairment, including dementia, in PD.

Background

Aggregation of α-synuclein is central to the pathophysiology of PD. Biomarkers related to α-synuclein may be informative for PD diagnosis/progression.

Objectives

To analyze α-synuclein in CSF in drug-naïve PD, healthy controls, and prodromal PD in the Parkinson's Progression Markers Initiative.

Methods

Over up to 36-month follow-up, CSF total α-synuclein and its association with MDS-UPDRS motor scores, cognitive assessments, and dopamine transporter imaging were assessed.

Results

The inception cohort included PD (n = 376; age [mean {standard deviation} years]: 61.7 [9.62]), healthy controls (n = 173; age, 60.9 [11.3]), hyposmics (n = 16; age, 68.3 [6.15]), and idiopathic rapid eye movement sleep behavior disorder (n = 32; age, 69.3 [4.83]). Baseline CSF α-synuclein was lower in manifest and prodromal PD versus healthy controls. Longitudinal α-synuclein decreased significantly in PD at 24 and 36 months, did not change in prodromal PD over 12 months, and trended toward an increase in healthy controls. The decrease in PD was not shown when CSF samples with high hemoglobin concentration were removed from the analysis. CSF α-synuclein changes did not correlate with longitudinal MDS-UPDRS motor scores or dopamine transporter scan.

Conclusions

CSF α-synuclein decreases early in the disease, preceding motor PD. CSF α-synuclein does not correlate with progression and therefore does not reflect ongoing dopaminergic neurodegeneration. Decreased CSF α-synuclein may be an indirect index of changes in the balance between α-synuclein secretion, solubility, or aggregation in the brain, reflecting its overall turnover. Additional biomarkers more directly related to α-synuclein pathophysiology and disease progression and other markers to be identified by, for example, proteomics and metabolomics are needed. © 2019 International Parkinson and Movement Disorder Society.

BACKGROUND: Identifying a meaningful progression metric for Parkinsons disease (PD) that reflects heterogeneity remains a challenge. OBJECTIVE: To assess the frequency and baseline predictors of progression to clinically relevant motor and non-motor PD milestones. METHODS: Using data from the Parkinsons Progression Markers Initiative (PPMI) de novo PD cohort, we monitored 25 milestones across six domains (walking and balance; motor complications; cognition; autonomic dysfunction; functional dependence; activities of daily living). Milestones were intended to be severe enough to reflect meaningful disability. We assessed the proportion of participants reaching any milestone; evaluated which occurred most frequently; and conducted a time-to-first-event analysis exploring whether baseline characteristics were associated with progression. RESULTS: Half of participants reached at least one milestone within five years. Milestones within the cognitive, functional dependence, and autonomic dysfunction domains were reached most often. Among participants who reached a milestone at an annual follow-up visit and remained active in the study, 82% continued to meet criteria for any milestone at one or more subsequent annual visits and 55% did so at the next annual visit. In multivariable analysis, baseline features predicting faster time to reaching a milestone included age (p < 0.0001), greater MDS-UPDRS total scores (p < 0.0001), higher GDS-15 depression scores (p = 0.0341), lower dopamine transporter binding (p = 0.0043), and lower CSF total α-synuclein levels (p = 0.0030). Symptomatic treatment was not significantly associated with reaching a milestone (p = 0.1639). CONCLUSION: Clinically relevant milestones occur frequently, even in early PD. Milestones were significantly associated with baseline clinical and biological markers, but not with symptomatic treatment. Further studies are necessary to validate these results, further assess the stability of milestones, and explore translating them into an outcome measure suitable for observational and therapeutic studies.

Objective

¹⁸ F-flortaucipir (formerly ¹⁸ F-AV1451 or ¹⁸ F-T807) binds to neurofibrillary tangles in Alzheimer disease, but tissue studies assessing binding to tau aggregates in progressive supranuclear palsy (PSP) have yielded mixed results. We compared in vivo ¹⁸ F-flortaucipir uptake in patients meeting clinical research criteria for PSP (n = 33) to normal controls (n = 46) and patients meeting criteria for Parkinson disease (PD; n = 26).

Methods

Participants underwent magnetic resonance imaging and positron emission tomography for amyloid-β (¹¹ C-PiB or ¹⁸ F-florbetapir) and tau (¹⁸ F-flortaucipir). ¹⁸ F-flortaucipir standardized uptake value ratios were calculated (t = 80-100 minutes, cerebellum gray matter reference). Voxelwise and region-of-interest group comparisons were performed in template space, with receiver operating characteristic curve analyses to assess single-subject discrimination. Qualitative comparisons with postmortem tau are reported in 1 patient who died 9 months after ¹⁸ F-flortaucipir.

Results

Clinical PSP patients showed bilaterally elevated ¹⁸ F-flortaucipir uptake in globus pallidus, putamen, subthalamic nucleus, midbrain, and dentate nucleus relative to controls and PD patients (voxelwise p < 0.05 family wise error corrected). Globus pallidus binding best distinguished PSP patients from controls and PD (area under the curve [AUC] = 0.872 vs controls, AUC = 0.893 vs PD). PSP clinical severity did not correlate with ¹⁸ F-flortaucipir in any region. A patient with clinical PSP and pathological diagnosis of corticobasal degeneration had severe tau pathology in PSP-related brain structures with good correspondence between in vivo ¹⁸ F-flortaucipir and postmortem tau neuropathology.

Interpretation

¹⁸ F-flortaucipir uptake was elevated in PSP versus controls and PD patients in a pattern consistent with the expected distribution of tau pathology. Ann Neurol 2017;82:622-634.

Objectives

To assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments.

Methods

We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.

Results

By year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes).

Conclusions

Cognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.