Parkinson's disease (PD) is a neurodegenerative disorder characterized by the progressive degeneration of midbrain neurons (MBNs). Recent evidence suggests contribution of the adaptive immune system in PD. Here, we show a role for human T lymphocytes as cell death inducers of induced pluripotent stem cell (iPSC)-derived MBNs in sporadic PD. Higher Th17 frequencies were found in the blood of PD patients and increased numbers of T lymphocytes were detected in postmortem PD brain tissues. We modeled this finding using autologous co-cultures of activated T lymphocytes and iPSC-derived MBNs of sporadic PD patients and controls. After co-culture with T lymphocytes or the addition of IL-17, PD iPSC-derived MBNs underwent increased neuronal death driven by upregulation of IL-17 receptor (IL-17R) and NFκB activation. Blockage of IL-17 or IL-17R, or the addition of the FDA-approved anti-IL-17 antibody, secukinumab, rescued the neuronal death. Our findings indicate a critical role for IL-17-producing T lymphocytes in sporadic PD.

Distinct gait characteristics like short steps and shuffling gait are prototypical signs commonly observed in Parkinson’s disease. Routinely assessed by observation through clinicians, gait is rated as part of categorical clinical scores. There is an increasing need to provide quantitative measurements of gait, e.g. to provide detailed information about disease progression. Recently, we developed a wearable sensor-based gait analysis system as diagnostic tool that objectively assesses gait parameter in Parkinson’s disease without the need of having a specialized gait laboratory. This system consists of inertial sensor units attached laterally to both shoes. The computed target of measures are spatiotemporal gait parameters including stride length and time, stance phase time, heel-strike and toe-off angle, toe clearance, and inter-stride variation from gait sequences. To translate this prototype into medical care, we conducted a cross-sectional study including 190 Parkinson’s disease patients and 101 age-matched controls and measured gait characteristics during a 4x10 meter walk at the subjects’ preferred speed. To determine intraindividual changes in gait, we monitored the gait characteristics of 63 patients longitudinally. Cross-sectional analysis revealed distinct spatiotemporal gait parameter differences reflecting typical Parkinson’s disease gait characteristics including short steps, shuffling gait, and postural instability specific for different disease stages and levels of motor impairment. The longitudinal analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson’s disease and corresponded to physician ratings. Taken together, we successfully show that wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson’s disease. These data demonstrate the feasibility and applicability of objective wearable sensor-based gait measurement in Parkinson’s disease reaching high technological readiness levels for both, large scale clinical studies and individual patient care.

The autophagy-lysosome pathway (ALP) regulates intracellular homeostasis of the cytosolic protein SNCA/alpha-synuclein and is impaired in synucleinopathies, including Parkinson disease and dementia with Lewy bodies (DLB). Emerging evidence suggests that ALP influences SNCA release, but the underlying cellular mechanisms are not well understood. Several studies identified SNCA in exosome/extracellular vesicle (EV) fractions. EVs are generated in the multivesicular body compartment and either released upon its fusion with the plasma membrane, or cleared via the ALP. We therefore hypothesized that inhibiting ALP clearance 1) enhances SNCA release via EVs by increasing extracellular shuttling of multivesicular body contents, 2) alters EV biochemical profile, and 3) promotes SNCA cell-to-cell transfer. Indeed, ALP inhibition increased the ratio of extra- to intracellular SNCA and upregulated SNCA association with EVs in neuronal cells. Ultrastructural analysis revealed a widespread, fused multivesicular body-autophagosome compartment. Biochemical characterization revealed the presence of autophagosome-related proteins, such as LC3-II and SQSTM1. This distinct "autophagosome-exosome-like" profile was also identified in human cerebrospinal fluid (CSF) EVs. After a single intracortical injection of SNCA-containing EVs derived from CSF into mice, human SNCA colocalized with endosome and neuronal markers. Prominent SNCA immunoreactivity and a higher number of neuronal SNCA inclusions were observed after DLB patient CSF EV injections. In summary, this study provides compelling evidence that a) ALP inhibition increases SNCA in neuronal EVs, b) distinct ALP components are present in EVs, and c) CSF EVs transfer SNCA from cell to cell in vivo. Thus, macroautophagy/autophagy may regulate EV protein composition and consequently progression in synucleinopathies.

Motor impairments are the prerequisite for the diagnosis in Parkinson's disease (PD). The cardinal symptoms (bradykinesia, rigor, tremor, and postural instability) are used for disease staging and assessment of progression. They serve as primary outcome measures for clinical studies aiming at symptomatic and disease modifying interventions. One major caveat of clinical scores such as the Unified Parkinson Disease Rating Scale (UPDRS) or Hoehn&Yahr (H&Y) staging is its rater and time-of-assessment dependency. Thus, we aimed to objectively and automatically classify specific stages and motor signs in PD using a mobile, biosensor based Embedded Gait Analysis using Intelligent Technology (eGaIT). eGaIT consist of accelerometers and gyroscopes attached to shoes that record motion signals during standardized gait and leg function. From sensor signals 694 features were calculated and pattern recognition algorithms were applied to classify PD, H&Y stages, and motor signs correlating to the UPDRS-III motor score in a training cohort of 50 PD patients and 42 age matched controls. Classification results were confirmed in a second independent validation cohort (42 patients, 39 controls). eGaIT was able to successfully distinguish PD patients from controls with an overall classification rate of 81%. Classification accuracy increased with higher levels of motor impairment (91% for more severely affected patients) or more advanced stages of PD (91% for H&Y III patients compared to controls), supporting the PD-specific type of analysis by eGaIT. In addition, eGaIT was able to classify different H&Y stages, or different levels of motor impairment (UPDRS-III). In conclusion, eGaIT as an unbiased, mobile, and automated assessment tool is able to identify PD patients and characterize their motor impairment. It may serve as a complementary mean for the daily clinical workup and support therapeutic decisions throughout the course of the disease.

Parkinson's disease (PD), the second most common neurodegenerative disorder, affects 1-2 % of humans aged 60 years and older. The diagnosis of PD is based on motor symptoms such as bradykinesia, rigidity, tremor, and postural instability associated with the striatal dopaminergic deficit that is linked to neurodegenerative processes in the substantia nigra (SN). In the past, cellular replacement strategies have been evaluated for their potential to alleviate these symptoms. Adult neurogenesis, the generation of new neurons within two proliferative niches in the adult brain, is being intensively studied as one potential mode for cell-based therapies. The subventricular zone provides new neurons for the olfactory bulb functionally contributing to olfaction. The subgranular zone of the hippocampus produces new granule neurons for the dentate gyrus, required for memory formation and proper processing of anxiety provoking stimuli. Recent years have revealed that PD is associated with non-motor symptoms such as hyposmia, anhedonia, lack of novelty seeking behavior, depression, and anxiety that are not directly associated with neurodegenerative processes in the SN. This broad spectrum of non-motor symptoms may partly rely on proper olfactorial processing and hippocampal function. Therefore, it is conceivable that some non-motor deficits in PD are related to defective adult neurogenesis. Accordingly, in animal models and postmortem studies of PD, adult neurogenesis is severely affected, although the exact mechanisms and effects of these changes are not yet fully understood or are under debate due to conflicting results. Here, we review the current concepts related to the dynamic interplay between endogenous cellular plasticity and PD-associated pathology.

In familial and sporadic forms of Parkinson’s disease (PD), alpha‐synuclein pathology is present in the brain stem nuclei and olfactory bulb (OB) long before Lewy bodies are detected in the substantia nigra. The OB is an active region of adult neurogenesis, where newly generated neurons physiologically integrate. While accumulation of wild‐type alpha‐synuclein is one of the pathogenic hallmarks of non‐genetic forms of PD, the A30P alpha‐synuclein mutation results in an earlier disease onset and a severe clinical phenotype. Here, we study the regulation of adult neurogenesis in the subventricular zone (SVZ)/OB system in a tetracycline‐suppressive (tet‐off) transgenic model of synucleinopathies, expressing human mutant A30P alpha‐synuclein under the control of the calcium/calmodulin‐dependent protein kinase II alpha (CaMK) promoter. In A30P transgenic mice alpha‐synuclein was abundant at the site of integration in the glomerular cell layer of the OB. Without changes in proliferation in the SVZ, significantly fewer newly generated neurons were observed in the OB granule cell and glomerular layers of A30P transgenic mice than in controls, most probably due to increased cell death. By tetracycline‐dependent abrogation of A30P alpha‐synuclein expression, OB neurogenesis and programmed cell death was restored to control levels. Our results indicate that, using A30P conditional (tet‐off) mice, A30P alpha‐synuclein has a negative impact on olfactory neurogenesis and suppression of A30P alpha‐synuclein enhances survival of newly generated neurons. This finding suggests that interfering with alpha‐synuclein pathology can rescue newly generated neurons, possibly leading to new targets for therapeutic interventions in synucleinopathies.

In this study, we intended to differentiate patients with essential tremor (ET) from tremor dominant Parkinson disease (PD). Accelerometer and electromyographic signals of hand movement from standardized upper extremity movement tests (resting, holding, carrying weight) were extracted from 13 PD and 11 ET patients. The signals were filtered to remove noise and non-tremor high frequency components. A set of statistical features was then extracted from the discrete wavelet transformation of the signals. Principal component analysis was utilized to reduce dimensionality of the feature space. Classification was performed using support vector machines. We evaluated the proposed method using leave one out cross validation and we report overall accuracy of the classification. With this method, it was possible to discriminate 12/13 PD patients from 8/11 patients with ET with an overall accuracy of 83%. In order to individualize this finding for clinical application we generated a posterior probability for the test result of each patient and compared the misclassified patients, or low probability scores to available clinical follow up information for individual cases. This non-standardized post hoc analysis revealed that not only the technical accuracy but also the clinical accuracy limited the overall classification rate. We show that, in addition to the successful isolation of diagnostic features, longitudinal and larger sized validation is needed in order to prove clinical applicability.

IntroductionCognitive and gait deficits are common symptoms in Parkinson’s disease (PD). Motor-cognitive dual tasks (DTs) are used to explore the interplay between gait and cognition. However, it is unclear if DT gait performance is indicative for cognitive impairment. Therefore, the aim of this study was to investigate if cognitive deficits are reflected by DT costs of spatiotemporal gait parameters.MethodsCognitive function, single task (ST) and DT gait performance were investigated in 67 PD patients. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) followed by a standardized, sensor-based gait test and the identical gait test while subtracting serial 3’s. Cognitive impairment was defined by a MoCA score <26. DT costs in gait parameters [(DT − ST)/ST × 100] were calculated as a measure of DT effect on gait. Correlation analysis was used to evaluate the association between MoCA performance and gait parameters. In a linear regression model, DT gait costs and clinical confounders (age, gender, disease duration, motor impairment, medication, and depression) were correlated to cognitive performance. In a subgroup analysis, we compared matched groups of cognitively impaired and unimpaired PD patients regarding differences in ST, DT, and DT gait costs.ResultsCorrelation analysis revealed weak correlations between MoCA score and DT costs of gait parameters (r/rSp ≤ 0.3). DT costs of stride length, swing time variability, and maximum toe clearance (|r/rSp| > 0.2) were included in a regression analysis. The parameters only explain 8% of the cognitive variance. In combination with clinical confounders, regression analysis showed that these gait parameters explained 30% of MoCA performance. Group comparison revealed strong DT effects within both groups (large effect sizes), but significant between-group effects in DT gait costs were not observed.ConclusionThese findings suggest that DT gait performance is not indicative for cognitive impairment in PD. DT effects on gait parameters were substantial in cognitively impaired and unimpaired patients, thereby potentially overlaying the effect of cognitive impairment on DT gait costs. Limits of the MoCA in detecting motor-function specific cognitive performance or variable individual response to the DT as influencing factors cannot be excluded. Therefore, DT gait parameters as marker for cognitive performance should be carefully interpreted in the clinical context.