Restriction Spectrum Imaging as a Biomarker for Amyotrophic Lateral Sclerosis
Abstract
Amyotrophic lateral sclerosis (ALS) is the most common form of adult-onset motor neuron disease and is characterized by progressive degeneration of both upper motor neurons of the motor cortex and lower motor neurons of the brainstem and spinal cord at disease onset. A small proportion of ALS results from established genetic causes inherited in a familial pattern. However, for most sporadic ALS cases, no single test can predict disease risk or provide an early definitive diagnosis. Also, given the extensive phenotypic variation in disease presentation, rate of progression, and the number of conditions that resemble ALS, many patients experience delays in diagnosis that prevents the testing and initiation of disease modifying treatments early in the course of disease when potentially most impactful. Thus, there is an urgent need for novel clinical biomarkers to improve early clinical diagnosis and prognosis in ALS, identify biologically meaningful patient subgroups, and provide surrogate endpoints in clinical trials. The goal of the proposed project is to evaluate the diagnostic and prognostic value of a novel brain imaging technique called restriction spectrum imaging (RSI) in ALS patients. RSI is an advanced diffusion-weighted imaging technique that allows detection of disease-specific changes in the brain with greater sensitivity and specificity compared to other imaging techniques, such as diffusion tensor imaging, making RSI suitable for clinical applications. We will recruit a total of 50 ALS patients (30 sporadic patients) across two institutions, UC San Diego, and UC San Francisco. All patients will receive genetic testing through an ALS sponsored genetic testing program. Longitudinal RSI and clinical data will be collected in all patients, every 4 months for a year. Cerebrospinal fluid (CSF) biomarkers (e.g., neurofilaments and inflammatory markers) will be collected in a subset of patients, also every 4 months for a year. Imaging data will be collected at a single time point from 50 age- and sex-matched healthy individuals. Our ALS clinics at UC San Diego and UC San Francisco are multi-disciplinary clinics. Combined they follow roughly 625 patients per year, of which 150 patients are new. Also, the imaging protocol we use can be incorporated into any facility with 3T General Electric and Siemens MRI technology. Therefore, our clinical biomarker has the potential of benefiting a large cohort of patients. Further, RSI has shown promise as an in-vivo biomarker of neuroinflammation. Therefore, once validated, our imaging biomarker will be clinically applicable to facilitate cohort stratification in therapeutic clinical trials targeting specific biological pathways, such as neuroinflammation, and may serve to predict therapeutic response and as an endpoint in clinical trials. Risks of the proposed study include discomfort and possible patient burden from longitudinal imaging, neuropsychological testing, and CSF data collection. The study team has plans in place to minimize any risk should they arise. Further, while there will be no direct immediate benefit to the patients from taking part in this study, the novel clinical biomarker we develop will help in the treatment of future patients with ALS. The minimum projected time it may take to achieve a patient-related outcome is 2 years. Data collection will occur the first year of funding. Data analysis and dissemination of research findings will occur over the course of 2 years and beyond. Our clinical biomarker will result in major advancements in ALS treatment and help better define subsets for clinical treatment. Specifically, our imaging biomarker will improve early clinical diagnosis, help physicians track disease progression more effectively, and accelerate the testing and initiation of disease modifying treatments early in the course of disease when potentially most impactful. Ultimately, these efforts will ensure progress toward era
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310353
Entities
People
- Iris Broce-diaz
Organizations
- United States Army
- University of California, San Diego