Active clinical trials for "Motor Neuron Disease"

The purpose of the HSP Sequencing Initiative is to better understand the role of genetics in hereditary spastic paraplegia (HSP) and related disorders. The HSPs are a group of more than 80 inherited neurological diseases that share the common feature of progressive spasticity. Collectively, the HSPs present the most common cause of inherited spasticity and associated disability, with a combined prevalence of 2-5 cases per 100,000 individuals worldwide. In childhood-onset forms, initial symptoms are often non-specific and many children may not receive a diagnosis until progressive features are recognized, often leading to a significant diagnostic delay. Genetic testing in children with spastic paraplegia is not yet standard practice. In this study, the investigators hope to identify genetic factors related to HSP. By identifying different genetic factors, the investigators hope that over time we can develop better treatments for sub-categories of HSP based on cause.

Psychological distress (anxiety and depression) is common in and experienced differently by people living with long-term health conditions (LTCs). Being able to measure whether psychological distress is related to living with a LTC would allow researchers and clinicians to provide interventions specifically tailored to the challenges of living with a LTC and therefore provide the most appropriate support for these patients. Such a measure would also be useful in research to identify the presence of illness-related distress in different patient groups. This project will therefore create a new measure of illness-related distress that has applications for both research and clinical practice. This will involve the psychometric validation of the new illness-related distress measure to test how valid and reliable the measure is. The aim of the project is to provide initial validation of the Illness Related Distress Scale in a community sample, recruited through online platforms. The objective of the study is to gather initial validity and reliability data for the scale.

This study is evaluating the use of two painless, non-invasive technologies in the assessment of muscle health over time in both healthy volunteers and patients who have diseases that affect the nervous system.

Investigation of the epidemiological factors associated with amyotrophic lateral sclerosis (ALS) in Israel with a view to future international collaboration. Particularly addressing:- Differences between ethnic subgroups Differences between immigrant and native-born populations Differences according to military service profile Clinical features gathered at each routine visit ,throughout the entire course of the disease, will be recorded in database format, in order to correlate with potential epidemiological factors.

Background: Neurodegenerative disorders can lead to problems in movement or memory. Some can cause abnormal proteins to build up in brain cells. Researchers want to understand whether these diseases have related causes or risk factors. Objective: To test people with movement or thinking and memory problems to see if they are eligible for research studies. Eligibility: People ages 18 and older with a neurodegenerative disorder associated with accumulation of TDP-43 or Tau proteins Design: Participants will have a screening visit. This may take place over 2-3 days. Tests include: Medical history Physical exam Questions about behavior and mood Tests of memory, attention, concentration, and thinking Movement measurement. The speed at which participants can stand up from a chair, tap their finger and foot, and walk a short distance will be measured. Some movements will be videotaped. They will be videotaped while they speak and read a paragraph. Blood tests. This might include genetic testing. Lung and breathing tests MRI. They will lie on a table that slides into a cylinder that takes pictures of the body. Some participants will get a dye through IV. Electromyography. A thin needle will be inserted into the muscles to measure electrical signals. Nerve tests. Small electrodes on the skin record muscle and nerve activity. A small piece of skin may be removed. A skin or blood sample may be taken to create stem cells. Optional lumbar puncture. A needle will be inserted into the space between the bones of the back to collect fluid. If participants are not eligible for current studies, they may be contacted in the future.

The purpose of this study is to collect CSF and blood samples that can be used in future research studies to identify potential biomarkers in blood and cerebrospinal fluid (CSF) collected in Amyotrophic Lateral Sclerosis (ALS) patients.

CRiALS is an umbrella protocol through which people are recruited to participate in a range of research studies being conducted by the ALS Research Collaboration (ARC).

This is a data repository for multi-site multi-protocol clinic-based Natural History Study of ALS and Other Motor Neuron Disorders (MND). All people living with ALS or other MNDs who attend clinics at the Study hospitals (sites) are offered to participate in the Study. The Sites collect so-called Baseline information including demographics, disease history and diagnosis, family history, etc. At each visit, the Sites also collect multiple disease-specific outcome measures and events. The information is captured in NeuroBANK, a patient-centric clinical research platform. The Sites have an option to choose to collect data into 20+ additional forms capturing biomarkers and outcome measures. Captured data after its curation are anonymized (all personal identifiers and dates are being removed), and the anonymized dataset is shared with medical researchers via a non-exclusive revocable license.

The goal of the Speech Accessibility Project at the UIUC Beckman Institute (https://speechaccessibilityproject.beckman.illinois.edu) is to collect, annotate, and curate a shared database of speech samples from people with atypical speech, and share this data set with researchers at other organizations. This two-year project plans to collect 1,200,000 speech samples from 2,000 people, each of whom will provide 600 samples. In Year 1, the initial focus will be people with Parkinson's. In Year 2, four more etiologies of interest will be recruited: Amyotrophic Lateral Sclerosis (ALS), Cerebral Palsy (CP), Down Syndrome (DS), and Stroke. UIUC will build an open-source software infrastructure to collect annotated speech samples and share these data in an appropriately secure fashion with researchers from our partner technology companies (and eventually, other organizations as well) so that they can use these data to improve their automatic speech recognition algorithms. This project promotes diversity, equity, and inclusion by helping technology companies to fully support all types of speech, and it is also more efficient and less burdensome for these specialized patient populations to have one centralized "collector" of speech samples.

BACKGROUND/RATIONALE: The paucity of biomarkers for the diagnosis and monitoring of patients affected by Amyotrophic Lateral Sclerosis (ALS) is one of the greatest concerns in ALS clinics and research. Phenotypic signs, electrophysiological test and clinical scales are currently used for ALS diagnosis and follow up before and after treatments. Nowadays, the diagnosis and differential diagnosis used to discriminate ALS from other comparable neurodegenerative diseases, are time-consuming and complex processes that reduce the time for a prompt intervention. Thus, the scientific community is asked to strive for new, measurable, fast and objective biomarkers for the diagnosis and stratification of patients. Saliva is a complex biofluid composed of bioactive molecules that can be collected by means of a non-invasive procedure. The possibility to simultaneously monitor all the variations in the endocrine, electrolytic and metabolic messengers in saliva has recently suggested its use for the diagnosis of complex diseases, like neurodegenerative diseases, but only limited information are available on the potential of saliva as alternative carrier of ALS biomarkers. OBJECTIVES: The aim of the present project is to optimize an innovative, non-invasive and fast procedure for the ALS onset and for the stratification of ALS patients, taking advantage of the sensitivity of Raman Spectroscopy (RS) and of accessible saliva. Fondazione Don Gnocchi (FDG) preliminary results on a small cohort of subjects demonstrated the feasibility of the methodology and the ability of LABION protocol to obtain a reproducible Raman fingerprint of saliva that can be used for the discrimination of healthy subjects, ALS patients and subjects affected by other types of neurological diseases. METHODS: Starting from FDG preliminary results, the biochemical composition of saliva in patients with diagnosed ALS will be evaluated and statistically compared with the one obtained from age and sex-matched healthy subjects and from patients affected by other neurological diseases (Parkinson's and Alzheimer's diseases). Moreover, an intra-group ALS clustering will be analysed in order to verify a different Raman fingerprint obtained from ALS patients with a bulbar or spinal onset. The collected Raman data will be processed using a multivariate analysis approach through Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA). The classification model will be created using cross-validation and subset validation. Thanks to RS, the overall composition of saliva will be established with minimal sample preparation, providing comprehensive biochemical fingerprint of the sample. In parallel, routine salivary parameters will be measured including viscosity, pH, total protein and carbohydrates concentration, amylase and pepsin, cortisol and Chromogranin A. EXPECTED RESULTS: By the end of this study, the investigators expected to verify the possibility to use the Raman salivary pattern as new promising biomarker for ALS diagnosis and progression to be related with clinical scales for the personalized and fine tuning of the therapeutic approach. The intent of this project is to create a classification model able to: Determine the ALS onset Discriminate the signal obtained from ALS patients from the one collected from other neurodegenerative diseases Stratify ALS patients into bulbar and spinal onset Correlate the Raman data with clinical and paraclinical scales used nowadays for ALS diagnosis and monitoring