Altered Activation Patterns within the Olfactory Network in Parkinson's Disease

Olfactory impairment is a consistent premotor symptom in sporadic Parkinson's disease (PD), presumably caused by pathological processes in the olfactory bulb and olfactory structures within mesolimbic brain areas. The objective of the present study was to obtain an in-depth insight into olfactory network dysfunction in PD patients. Event-related functional magnetic resonance imaging (3 T) was conducted with 16 early-stage PD patients and 16 matched controls during an odor detection task. Activation within the olfactory network was analyzed both in terms of strength of activation (whole-brain random effects, regions of interest [ROI] analysis based on the hemodynamic response function) as well as time-course characteristics (finite impulse response–based ROI analysis). Olfactory-induced activation in patients with PD in comparison to a standard activation pattern obtained from controls revealed profound hyperactivation in piriform and orbitofrontal cortices. However, whereas orbitofrontal areas seem to be unable to discriminate between signal and noise, primary olfactory cortex shows preserved discriminatory ability. These results support a complex network dysfunction that exceeds structural pathology observed in the olfactory bulb and mesolimbic cortices and thus demonstrate the important contribution of functional data to describe network dynamics occurring in the degenerating brain

An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

New smart technologies and the internet of things increasingly play a key role in healthcare and wellness, contributing to the development of novel healthcare concepts. These technologies enable a comprehensive view of an individual’s movement and mobility, potentially supporting healthy living as well as complementing medical diagnostics and the monitoring of therapeutic outcomes. This overview article specifically addresses smart shoes, which are becoming one such smart technology within the future internet of health things, since the ability to walk defines large aspects of quality of life in a wide range of health and disease conditions. Smart shoes offer the possibility to support prevention, diagnostic work-up, therapeutic decisions, and individual disease monitoring with a continuous assessment of gait and mobility. This overview article provides the technological as well as medical aspects of smart shoes within this rising area of digital health applications, and is designed especially for the novel reader in this specific field. It also stresses the need for closer interdisciplinary interactions between technological and medical experts to bridge the gap between research and practice. Smart shoes can be envisioned to serve as pervasive wearable computing systems that enable innovative solutions and services for the promotion of healthy living and the transformation of health care

A Single Bout of Aerobic Exercise Improves Motor Skill Consolidation in Parkinson’s Disease

Background: Motor learning is impaired in Parkinson’s disease (PD), with patients demonstrating deficits in skill acquisition (online learning) and consolidation (offline learning) compared to healthy adults of similar age. Recent studies in young adults suggest that single bouts of aerobic exercise (AEX), performed in close temporal proximity to practicing a new motor task, may facilitate motor skill learning. Thus, we aimed at investigating the effects of a single bout of aerobic cycling on online and offline learning in PD patients.Methods: 17 PD patients (Hoehn and Yahr 1 – 2.5, age: 64.4 ± 6.2) participated in this crossover study. Immediately prior to practicing a novel balance task, patients either performed 30 min of (i) moderate intensity (60–70% VO2max) aerobic cycling, or (ii) seated rest (order counterbalanced). The task required patients to stabilize a balance platform (stabilometer) in a horizontal position for 30 s. For each experimental condition, patients performed 15 acquisition trials, followed by a retention test 24 h later. We calculated time in balance (platform within ± 5° from horizontal) for each trial, and analyzed within- and between-subjects differences in skill acquisition (online learning) and skill retention (offline learning) using mixed repeated-measures ANOVA.Results: We found that the exercise bout had no effect on performance level or online gains during acquisition, despite affecting the time course of skill improvements (larger initial and reduced late skill gains). Aerobic cycling significantly improved offline learning, as reflected by larger 24-h skill retention compared to the rest condition.Conclusion: Our results suggest that a single bout of moderate-intensity AEX is effective in improving motor skill consolidation in PD patients. Thus, acute exercise may represent an effective strategy to enhance motor memory formation in this population. More work is necessary to understand the underlying mechanisms, the optimal scheduling of exercise, and the applicability to other motor tasks. Further, the potential for patients in later disease stages need to be investigated. The study was a priori registered at ClinicalTrials.gov (NCT03245216)

The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations

Background: Differentiating idiopathic Parkinson's disease (IPD) from atypical Parkinsonian disorders (APD) is challenging, especially in early disease stages. Postural instability and gait difficulty (PIGD) are substantial motor impairments of IPD and APD. Clinical evidence implies that patients with APD have larger PIGD impairment than IPD patients. Sensor-based gait analysis as instrumented bedside test revealed more gait deficits in APD compared to IPD. However, the diagnostic value of instrumented bedside tests compared to clinical assessments in differentiating APD from IPD patients have not been evaluated so far.Objective: The objectives were (a) to evaluate whether sensor-based gait parameters provide additional information to validated clinical scores in differentiating APD from matched IPD patients, and (b) to investigate if objective, instrumented gait assessments have comparable discriminative power to clinical scores.Methods: In a previous study we have recorded instrumented gait parameters in patients with APD (Multiple System Atrophy and Progressive Supranuclear Palsy). Here, we compared gait parameters to those of retrospectively pairwise disease duration-, age-, and gender-matched IPD patients in order to address this new research questions. To this aim, the PIGD score was calculated as sum of the MDS-UPDRS-3-items “gait,” “postural stability,” “arising from chair,” and “posture.” Gait characteristics were evaluated in standardized gait tests using an instrumented, sensor-based gait analysis system. Machine learning algorithms were used to extract spatio-temporal gait parameters. Receiver Operating Characteristic analysis was performed in order to detect the discriminative power of the instrumented vs. the clinical bedside tests in differentiating IPD from APD.Results: Sensor-based stride length, gait velocity, toe off angle, and parameters representing gait variability significantly differed between IPD and APD groups. ROC analysis revealed a high Area Under the Curve (AUC) for PIGD score (0.919), and UPDRS-3 (0.848). Particularly, the objective parameters stance time variability (0.841), swing time variability (0.834), stride time variability (0.821), and stride length variability (0.804) reached high AUC's as well.Conclusions: PIGD symptoms showed high discriminative power in differentiating IPD from APD supporting gait disorders as substantial diagnostic target. Sensor-based gait variability parameters provide metric, objective added value, and serve as complementary outcomes supporting clinical diagnostics and long-term home-monitoring concepts

The Co-chaperone Carboxyl Terminus of Hsp70-interacting Protein (CHIP) Mediates α-Synuclein Degradation Decisions between Proteasomal and Lysosomal Pathways

Alpha-synuclein is a major component of Lewy bodies, the pathological hallmark of Parkinson disease, dementia with Lewy bodies, and related disorders. Misfolding and aggregation of alpha-synuclein is thought to be a critical cofactor in the pathogenesis of certain neurodegenerative diseases. In the current study, we investigate the role of the carboxyl terminus of Hsp70-interacting protein (CHIP) in alpha-synuclein aggregation. We demonstrate that CHIP is a component of Lewy bodies in the human brain, where it colocalizes with alpha-synuclein and Hsp70. In a cell culture model, endogenous CHIP colocalizes with alpha-synuclein and Hsp70 in intracellular inclusions, and overexpression of CHIP inhibits alpha-synuclein inclusion formation and reduces alpha-synuclein protein levels. We demonstrate that CHIP can mediate alpha-synuclein degradation by two discrete mechanisms that can be dissected using deletion mutants; the tetratricopeptide repeat domain is critical for proteasomal degradation, whereas the U-box domain is sufficient to direct alpha-synuclein toward the lysosomal degradation pathway. Furthermore, alpha-synuclein, synphilin-1, and Hsp70 all coimmunoprecipitate with CHIP, raising the possibility of a direct alpha-synuclein-CHIP interaction. The fact that the tetratricopeptide repeat domain is required for the effects of CHIP on alpha-synuclein inclusion morphology, number of inclusions, and proteasomal degradation as well as the direct interaction of CHIP with Hsp70 implicates a cooperation of CHIP and Hsp70 in these processes. Taken together, these data suggest that CHIP acts a molecular switch between proteasomal and lysosomal degradation pathways

Recommendations for Standards of Network Care for Patients with Parkinson’s Disease in Germany

Although our understanding of Parkinson’s disease (PD) has improved and effective treatments are available, caring for people with PD remains a challenge. The large heterogeneity in terms of motor symptoms, nonmotor symptoms, and disease progression makes tailored individual therapy and individual timing of treatment necessary. On the other hand, only limited resources are available for a growing number of patients, and the high quality of treatment cannot be guaranteed across the board. At this point, networks can help to make better use of resources and improve care. The working group PD Networks and Integrated Care, part of the German Parkinson Society, is entrusted to convene clinicians, therapists, nurses, researchers, and patients to promote the development of PD networks. This article summarizes the work carried out by the working group PD Networks and Integrated Care in the development of standards of network care for patients with PD in Germany

Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson’s disease

Background Gait symptoms and balance impairment are characteristic indicators for the progression in Parkinson’s disease (PD). Current gait assessments mostly focus on straight strides with assumed constant velocity, while acceleration/deceleration and turning strides are often ignored. This is either due to the set up of typical clinical assessments or technical limitations in capture volume. Wearable inertial measurement units are a promising and unobtrusive technology to overcome these limitations. Other gait phases such as initiation, termination, transitioning (between straight walking and turning) and turning might be relevant as well for the evaluation of gait and balance impairments in PD. Method In a cohort of 119 PD patients, we applied unsupervised algorithms to find different gait clusters which potentially include the clinically relevant information from distinct gait phases in the standardized 4x10 m gait test. To clinically validate our approach, we determined the discriminative power in each gait cluster to classify between impaired and unimpaired PD patients and compared it to baseline (analyzing all straight strides). Results As a main result, analyzing only one of the gait clusters constant, non-constant or turning led in each case to a better classification performance in comparison to the baseline (increase of area under the curve (AUC) up to 19% relative to baseline). Furthermore, gait parameters (for turning, constant and non-constant gait) that best predict motor impairment in PD were identified. Conclusions We conclude that a more detailed analysis in terms of different gait clusters of standardized gait tests such as the 4x10 m walk may give more insights about the clinically relevant motor impairment in PD patients

Thigh-Derived Inertial Sensor Metrics to Assess the Sit-to-Stand and Stand-to-Sit Transitions in the Timed Up and Go (TUG) Task for Quantifying Mobility Impairment in Multiple Sclerosis

INTRODUCTION: Inertial sensors generate objective and sensitive metrics of movement disability that may indicate fall risk in many clinical conditions including multiple sclerosis (MS). The Timed-Up-And-Go (TUG) task is used to assess patient mobility because it incorporates clinically-relevant submovements during standing. Most sensor-based TUG research has focused on the placement of sensors at the spine, hip or ankles; an examination of thigh activity in TUG in multiple sclerosis is wanting. METHODS: We used validated sensors (x-IMU by x-io) to derive transparent metrics for the sit-to-stand (SI-ST) transition and the stand-to-sit (ST-SI) transition of TUG, and compared effect sizes for metrics from inertial sensors on the thighs to effect sizes for metrics from a sensor placed at the L3 level of the lumbar spine. 23 healthy volunteers were compared to 17 ambulatory persons with MS (PwMS, HAI <= 2). RESULTS: During the SI-ST transition, the metric with the largest effect size comparing healthy volunteers to PwMS was the Area Under the Curve of the thigh angular velocity in the pitch direction -- representing both thigh and knee extension; the peak of the spine pitch angular velocity during SI-ST also had a large effect size, as did some temporal measures of duration of SI-ST, although less so. During the ST-SI transition the metric with the largest effect size in PwMS was the peak of the spine angular velocity curve in the roll direction. A regression was performed. DISCUSSION: We propose for PwMS that the diminished peak angular velocities during SI-ST directly represents extensor weakness, while the increased roll during ST-SI represents diminished postural control. CONCLUSIONS: During the SI-ST transition of TUG, angular velocities can discriminate between healthy volunteers and ambulatory PwMS better than temporal features. Sensor placement on the thighs provides additional discrimination compared to sensor placement at the lumbar spine

Classification of advanced stages of Parkinson's disease: translation into stratified treatments.

Advanced stages of Parkinson's disease (advPD) still impose a challenge in terms of classification and related stage-adapted treatment recommendations. Previous concepts that define advPD by certain milestones of motor disability apparently fall short in addressing the increasingly recognized complexity of motor and non-motor symptoms and do not allow to account for the clinical heterogeneity that require more personalized approaches. Therefore, deep phenotyping approaches are required to characterize the broad-scaled, continuous and multidimensional spectrum of disease-related motor and non-motor symptoms and their progression under real-life conditions. This will also facilitate the reasoning for clinical care and therapeutic decisions, as neurologists currently have to refer to clinical trials that provide guidance on a group level; however, this does not always account for the individual needs of patients. Here, we provide an overview on different classifications for advPD that translate into critical phenotypic patterns requiring the differential therapeutic adjustments. New concepts refer to precision medicine approaches also in PD and first studies on genetic stratification for therapeutic outcomes provide a potential for more objective treatment recommendations. We define novel treatment targets that align with this concept and make use of emerging device-based assessments of real-life information on PD symptoms. As these approaches require empowerment of patients and integration into treatment decisions, we present communication strategies and decision support based on new technologies to adjust treatment of advPD according to patient demands and safety