Active clinical trials for "Parkinson Disease"

Given the emerging evidence on LRRK2-related biomarkers, this project will focus on identifying leucocyte and urine biomarkers that are altered by the LRRK2 G2385R variant, and investigating the effects of LRRK2 kinase inhibitor (MLi-2) on these biomarkers, using immunoblotting and mass spectrometry.

Parkinson Disease (PD) is a neurodegenerative disorder who begin around 55 years old, characterized by brain's backmatter's dopamine neuron destruction, involved in motor control. Diagnosis is made with presence of 3 of 4 disease's cardinal sign: bradykinesia, rigidity, resting tremor, walking troubles. Treatments enhance patient's quality of life, but do not allow to stop disease's evolution, who is specific depending on a lot of factors. For some years, PD's non motor symptoms (NMS) - in particular pain, anxiety, depression, sleep disorders - have been highlighted and turn out to impair sometimes quality of life even though motor symptoms are controlled. This project's main aim is to evaluate if aquatic environment's care lead to an advantage on PD's NMS, symptoms currently underestimated, insufficiently in care and having a harmful influence on quality of life. Collaboration of the University Hospital (Neurology Dpt), the Physical Medicine and Rehabilitation Regional Institute, Grand Nancy Thermal, and France Parkinson Association, will allow in this way to offer on PD's NMS, postural control impairments, and walking troubles an alternative or further non-pharmacological therapy.

Impulse control disorders are frequent and troublesome in patients with Parkinson's disease. However, the cerebral functional alterations related to impulse control disorders in Parkinson's disease are poorly understood and may involve the serotoninergic system besides alterations in the dopaminergic system. The primary objective of this study is to investigate the cerebral functional alterations in the serotoninergic system in patients with Parkinson's disease and impulse control disorders using Positron Emission Tomography with highly specific radiotracers of serotonin transporter (SERT) using [11 Carbon]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile ([11C]-DASB) and of serotonin 5-Hydroxytryptamine 2A (5-HT2A) receptor using [18 Fluorine]-altanserin ([18F]-altanserin), in comparison to patients with Parkinson's disease without impulse control disorders and healthy volunteers.

The aim of the study is to improve estimation of cognitive outcome after STN-DBS in PD in order to avoid risk factors by optimizing peri- and intraoperative management personalize therapeutic strategies for optimal long-term benefit The investigators will test possible predictors (clinical, neuropsychological, neuroimaging, electrophysiological and molecular) for the risk of cognitive dysfunction after deep brain stimulation of the subthalamic nucleus (STN-DBS) in Parkinson's disease (PD) at a single center (Charité - Universitätsmedizin Berlin, Germany). Data collection takes place prior to as well as 3 and 12 months after the STN-DBS operation. Participation is proposed to all PD patients that are planned to undergo STN-DBS after careful examination of eligibility for this treatment according to standard operation procedures.

The first goal of the study is to investigate whether an algorithm can reliably detect Freezing of Gait (FOG) in Parkinson patients based on participant gait data generated by a pressure insole. The second goal is to investigate whether Auditive Cueing (AC) based on such a detection reduces the frequency and length of FOG episodes in those participants. The study will be conducted per Good Clinical Practice principles.

Parkinson's disease (PD) is a progressive and disabling neurodegenerative disease, clinically characterized by motor and non-motor symptoms. The potential of the "Transcranial direct current stimulation" (tDCS) for symptomatic improvement in these patients has been demonstrated, but the factors associated with the best therapeutic response are not known. The electroencephalogram (EEG) is considered as a diagnostic and prognostic biomarker of PD, and has been used in recent studies associated with machine-learning methods to identify predictors of responses in neurological and psychiatric conditions. Using connectivity-based prediction and machine-learning, the investigators intend to identify and compare characteristics related to baseline resting EEG between PD responders and non-responders to tDCS treatment. The recruited participants will be randomized to treatment with active tDCS associated with dual-task motor therapy or motor therapy with visual cues. A resting-state electroencephalography (EEG) will be recorded prior to the start of the treatment. The investigators will determine clinical improvement labels used for machine learning classification, in baseline and posttreatment assessments and will use three different methods to categorize the data into two classes (low or high improvement): Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Extreme Learning Machine (ELM). The functional label will be based on the Timed Up and Go Test recorded at baseline and posttreament of tDCS treatment.

Levodopa-carbidopa intestinal gel (LCIG) infusion has demonstrated to improve motor fluctuations. The aim of this study is to assess the long-term safety and effectiveness of LCIG infusion in advanced Parkinson's disease (PD) patients with motor fluctuations and its effect in non-motor symptoms.

The aim of the study is to evaluate if patients' personality could be considerate as predictive factor of quality of life after the establishment of continuous infusion of dopaminergic treatments to observe if there are predictive personality's profiles of specific therapeutic response (Deep Brain Stimulation (DBS) of the subthalamic nucleus (STN) or continuous infusion).

The diagnosis and management of movement disorders, such as Parkinson's disease (PD), parkinson-plus syndromes (PPS), dystonia, essential tremor (ET), normal pressure hydrocephalus (NPH) and others is challenging given the lack of objective diagnostic and monitoring tools with high sensitivity and specificity. A cornerstone in research of neurological disorders manifesting as MDi is the investigation of neurophysiological changes as potential biomarkers that could help in diagnosis, monitoring disease progression and response to therapies. Such a neuro-marker that would overcome the major disadvantages of clinical questionnaires and rating scales (such as the Unified Parkinson's disease rating scale -UPDRS, for PD, The Essential Tremor Rating Assessment Scale -TETRAS, for ET and others), including low test-retest repeatability and subjective judgment of different raters, would have real impact on disease diagnosis and choice of interventions and monitoring of effects of novel therapeutics, including disease modifying therapies. To address this, ElMindA has developed over the last decade a non-invasive, low-cost technology named Brain Network Activation (BNA), which is a new imaging approach that can detect changes in brain activity and functional connectivity. Results from proof-of concept studies on PD patients have demonstrated that: 1) PD patients exhibited a significant decrease in BNA scores relatively to healthy controls; 2) notable changes in functional network activity in correlation with different dopamine-agonist doses; 3) significant correlation between BNA score and the UPDRS). 4) BNA could also differentiate early PD from healthy controls

The goal of the study is to compare the impact of different actigraphy procedures on the healthcare organization of Parkinson's disease (PK) patients using an apomorphine pump. To do so, the study design includes a patients' randomisation in two groups that will be followed during 6 months.