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Recent developments in alpha-synuclein research – Clinical and preclinical data
22
Abstracts / Basal Ganglia 8 (2017) 1–22
and also [123 I]IBZM SPECT of postsynaptic dopamine D2/D3 receptor availability do not allow for a sufficient differentiation between PD and the so-called atypical PS (APS). Thus, they should not be applied for this purpose. [123 I]MIBG scintigraphy of sympathetic myocardial innervation permits a differentiation between PD and multiple system atrophy (MSA) with moderate diagnostic accuracy. Thus, it might be applied for his purpose. Assessment of regional cerebral glucose metabolism by [18 F]FDG PET achieves a very accurate differentiation between PD and APS as well as between different APS subtypes (i.e., MSA, progressive supranuclear palsy [PSP], and corticobasal degeneration [CBD]). Therefore, according to the recent guidelines, [18 F]FDG PET might be applied to achieve optimal differential diagnosis of PS. Finally, recent publications also indicate a probable prognostic value of [18 F]FDG PET concerning overall survival of PS patients and development of cognitive impairments in PD patients. Recent German S3 guidelines provide detailed evidence-based recommendations for the use of nuclear medicine imaging techniques, of which [123 I]FP-CIT SPECT and [18 F]FDG PET are most suited for the diagnosis and differential diagnosis of neurodegenerative PS, respectively. http://dx.doi.org/10.1016/j.baga.2017.02.064 Recent developments in alpha-synuclein research – Clinical and preclinical data Björn Falkenburger 1,∗ , Karin Danzer 2 , Anja Schneider 3 , Brit Mollenhauer 4 1
University Aachen, Germany University Ulm, Germany 3 University Bonn, Germany 4 Elena-Klinik, Kassel, Germany 2
Lewy bodies are aggregates consisting of alpha-synuclein protein. Lewy bodies characterize Parkinson disease and further synucleinopathies. They explain symptoms of Parkinson disease, in particular the prevalent non motor symptoms. We expect that a better understanding of aggregation, degradation, secretion and spread of alpha-synuclein will allow the development of new protective strategies against Parkinson disease. In this symposium, we will present important developments in the field of alpha-synuclein research. We will talk about the cellular mechanisms that degrade alphasynuclein aggregates. One of these mechanisms is autophagy, in which cytosolic components are enclosed by a membrane and subsequently degraded by the lysosome. In addition, membraneenclosed aggregates can be secreted into the extracellular space in the form of microvesicles or exosomes. Such exosomes can transport aggregates from a donor cell to a recipient cell. Transfer of alpha-synuclein can be demonstrated in cellular models, and also in mouse models of Parkinson disease. Consequently, the amount of extracellular alpha-synuclein has received increased attention as a diagnostic biomarker for Parkinson disease. Alpha-synuclein can now be quantified in the cerebrospinal fluid, blood, saliva and tissue biopsies of symptomatic Parkinson patients and in “premotor” subjects with REM sleep behaviour disorder. http://dx.doi.org/10.1016/j.baga.2017.02.065
Long-term detection of motor fluctuations by wrist-worn sensors in Parkinson’s disease Daniel Pichler 1,∗ , Urban Fietzek 1 , Franz Pfister 1 , Ahmad Ahmadi 2 , Felix Achilles 3,4 , Kian Abedinpour 1 , Kai Bötzel 2 , Andres Ceballos-Baumann 1 1
Schön Klinik München Schwabing, Department of Neurology and Clinical Neurophysiology, Munich, Germany 2 Ludwig-Maximilians-Universität, Department of Neurology, Munich, Germany 3 Ludwig-Maximilians-Universität, Department of Surgery, Munich, Germany 4 Technical University of Munich, Chair for Computer Aided Medical Procedures & Augmented Reality, Munich, Germany Introduction: The description and treatment of the symptoms of patients suffering from Parkinson’s disease should be based on objective criteria. Therapy decisions are made upon assessment of motor symptoms. Therefore, suitable evaluation criteria should not only be captured on a one-off basis, but should also be captured over longer periods of time. Motion sensors, which are built in mobile devices and can be imperceptibly carried on the body, could serve as a future solution for patients and care givers. Methods: After a positive vote by the ethics committee of the TU Munich, we included patients with Parkinson’s disease in a pilot project, which examined the use of a commercially available sensor (Microsoft Band 2) for the detection of motor fluctuations. The three-dimensional data from its accelerometer and gyroscope were recorded at a frequency of 62.5 Hz by a wrist worn sensor worn at the stronger affected body side. At the same time, the MDS-UPDRSitems GAIT, FREEZING, GLOBAL-BRADYKINESIA and TREMOR as well as the mAIMS item ARM-MOVEMENT were evaluated every minute. Further analysis took place offline using machine learning algorithms (long short-term memory networks), which categorized the sensor data into the three classes BRADYKINETIC (OFF), NORMAL (ON) and DYSKINETIC (ON+/++). The F1 score expresses the accuracy (precision and recall) of this method. Results: We recorded movement data from 27 patients with a median Hoehn-Yahr stage of 2, an age of 67 ± 10 years, 11 ± 5 years of disease duration, and a MoCA score of 26 ± 3. A total of 219 h of data were collected, on average 8.1 h/patient. The first evaluation took place with the Euclidean norm of the data and a step size of 4 s. The algorithmic classification into the three categories OFF, ON and ON+/++ reached an F1 score of up to 0.605 in the first series of experiments and is currently being optimized further. Discussion: In this pilot project, we were able to show that movement data can be recorded with comparatively little effort by a mobile recording device. The objective algorithmic classification allows the description of clinically relevant information in previously unattained temporal resolution. This opens up new possibilities for the detection and monitoring of motor symptoms of people with Parkinson’s disease. http://dx.doi.org/10.1016/j.baga.2017.02.066
Abstracts / Basal Ganglia 8 (2017) 1–22
and also [123 I]IBZM SPECT of postsynaptic dopamine D2/D3 receptor availability do not allow for a sufficient differentiation between PD and the so-called atypical PS (APS). Thus, they should not be applied for this purpose. [123 I]MIBG scintigraphy of sympathetic myocardial innervation permits a differentiation between PD and multiple system atrophy (MSA) with moderate diagnostic accuracy. Thus, it might be applied for his purpose. Assessment of regional cerebral glucose metabolism by [18 F]FDG PET achieves a very accurate differentiation between PD and APS as well as between different APS subtypes (i.e., MSA, progressive supranuclear palsy [PSP], and corticobasal degeneration [CBD]). Therefore, according to the recent guidelines, [18 F]FDG PET might be applied to achieve optimal differential diagnosis of PS. Finally, recent publications also indicate a probable prognostic value of [18 F]FDG PET concerning overall survival of PS patients and development of cognitive impairments in PD patients. Recent German S3 guidelines provide detailed evidence-based recommendations for the use of nuclear medicine imaging techniques, of which [123 I]FP-CIT SPECT and [18 F]FDG PET are most suited for the diagnosis and differential diagnosis of neurodegenerative PS, respectively. http://dx.doi.org/10.1016/j.baga.2017.02.064 Recent developments in alpha-synuclein research – Clinical and preclinical data Björn Falkenburger 1,∗ , Karin Danzer 2 , Anja Schneider 3 , Brit Mollenhauer 4 1
University Aachen, Germany University Ulm, Germany 3 University Bonn, Germany 4 Elena-Klinik, Kassel, Germany 2
Lewy bodies are aggregates consisting of alpha-synuclein protein. Lewy bodies characterize Parkinson disease and further synucleinopathies. They explain symptoms of Parkinson disease, in particular the prevalent non motor symptoms. We expect that a better understanding of aggregation, degradation, secretion and spread of alpha-synuclein will allow the development of new protective strategies against Parkinson disease. In this symposium, we will present important developments in the field of alpha-synuclein research. We will talk about the cellular mechanisms that degrade alphasynuclein aggregates. One of these mechanisms is autophagy, in which cytosolic components are enclosed by a membrane and subsequently degraded by the lysosome. In addition, membraneenclosed aggregates can be secreted into the extracellular space in the form of microvesicles or exosomes. Such exosomes can transport aggregates from a donor cell to a recipient cell. Transfer of alpha-synuclein can be demonstrated in cellular models, and also in mouse models of Parkinson disease. Consequently, the amount of extracellular alpha-synuclein has received increased attention as a diagnostic biomarker for Parkinson disease. Alpha-synuclein can now be quantified in the cerebrospinal fluid, blood, saliva and tissue biopsies of symptomatic Parkinson patients and in “premotor” subjects with REM sleep behaviour disorder. http://dx.doi.org/10.1016/j.baga.2017.02.065
Long-term detection of motor fluctuations by wrist-worn sensors in Parkinson’s disease Daniel Pichler 1,∗ , Urban Fietzek 1 , Franz Pfister 1 , Ahmad Ahmadi 2 , Felix Achilles 3,4 , Kian Abedinpour 1 , Kai Bötzel 2 , Andres Ceballos-Baumann 1 1
Schön Klinik München Schwabing, Department of Neurology and Clinical Neurophysiology, Munich, Germany 2 Ludwig-Maximilians-Universität, Department of Neurology, Munich, Germany 3 Ludwig-Maximilians-Universität, Department of Surgery, Munich, Germany 4 Technical University of Munich, Chair for Computer Aided Medical Procedures & Augmented Reality, Munich, Germany Introduction: The description and treatment of the symptoms of patients suffering from Parkinson’s disease should be based on objective criteria. Therapy decisions are made upon assessment of motor symptoms. Therefore, suitable evaluation criteria should not only be captured on a one-off basis, but should also be captured over longer periods of time. Motion sensors, which are built in mobile devices and can be imperceptibly carried on the body, could serve as a future solution for patients and care givers. Methods: After a positive vote by the ethics committee of the TU Munich, we included patients with Parkinson’s disease in a pilot project, which examined the use of a commercially available sensor (Microsoft Band 2) for the detection of motor fluctuations. The three-dimensional data from its accelerometer and gyroscope were recorded at a frequency of 62.5 Hz by a wrist worn sensor worn at the stronger affected body side. At the same time, the MDS-UPDRSitems GAIT, FREEZING, GLOBAL-BRADYKINESIA and TREMOR as well as the mAIMS item ARM-MOVEMENT were evaluated every minute. Further analysis took place offline using machine learning algorithms (long short-term memory networks), which categorized the sensor data into the three classes BRADYKINETIC (OFF), NORMAL (ON) and DYSKINETIC (ON+/++). The F1 score expresses the accuracy (precision and recall) of this method. Results: We recorded movement data from 27 patients with a median Hoehn-Yahr stage of 2, an age of 67 ± 10 years, 11 ± 5 years of disease duration, and a MoCA score of 26 ± 3. A total of 219 h of data were collected, on average 8.1 h/patient. The first evaluation took place with the Euclidean norm of the data and a step size of 4 s. The algorithmic classification into the three categories OFF, ON and ON+/++ reached an F1 score of up to 0.605 in the first series of experiments and is currently being optimized further. Discussion: In this pilot project, we were able to show that movement data can be recorded with comparatively little effort by a mobile recording device. The objective algorithmic classification allows the description of clinically relevant information in previously unattained temporal resolution. This opens up new possibilities for the detection and monitoring of motor symptoms of people with Parkinson’s disease. http://dx.doi.org/10.1016/j.baga.2017.02.066