Despite decades of research and dozens of trials, effective disease-modifying treatments for amyotrophic lateral sclerosis (ALS) and other neurodegenerative disorders still elude us. A primary source of the litany of negative trials is the increasing recognition that experimental therapeutics are frequently administered too late in the course of disease, after irreversible neuronal loss has already occurred. These delays stem in part from the fact that the degenerative processes in ALS begins prior to overt clinical disease, and in part from delays in diagnosis (approximately 12 months from symptom onset) and delays between onset and clinical trial enrollment (approximately 17 months interventional delay). The overall goal of this project is to address the challenge to ALS drug development that is posed by the relatively late stage in the course of disease when diagnosis is made and patients are enrolled in clinical trials. The study of pre-symptomatic disease is currently only possible in (but also most relevant to) those with the genetic forms of ALS, most commonly due to point mutations in the SOD1 gene or a repeat expansion in C9orf72. But earlier diagnosis of symptomatic disease is relevant to patients with all forms of ALS (both genetic and non-genetic). In this project, we outline two strategies for addressing these challenges, with a view to preparing for a future of clinical trials that enroll patients at significantly earlier stages in the course of their disease.
In Aim 1 of this project we propose to use multimodal neuroimaging (MRI, DTI, and perfusion MRI) combined with pseudo-longitudinal, exploratory longitudinal, and multivariate network statistical techniques to characterize the anatomic distribution and temporal course of structural and functional changes in pre-symptomatic C9orf72 and SOD1 mutation carriers. We hypothesize that this approach will help us better understand how and when anatomic changes occur across adult aging in pre-symptomatic individuals at risk for ALS (or FTD) relative to age-matched non- mutation controls. We also hypothesize that network and multivariate approaches will help increase our biological understanding of C9orf72 and SOD1, as well as how these distinct etiologies of familial ALS may differ from one another.
In Aim 2 of this project we will use a ?cohort? approach to evaluate the diagnostic accuracy (sensitivity, specificity and positive/negative predictive value) of serum and CSF measurement of neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH) for the early diagnosis of ALS. This approach will fill a critical gap in the current literature about the utility of neurofilaments for the diagnosis, and particularly in earlier stages of ALS. Since the currently available evidence is based on case-control studies (i.e. a comparison of patients already known to have ALS vs. patients already known to have some other disease), current estimates of sensitivity, specificity and positive/negative predictive value may be inflated and cut-offs need to be redefined. Together, by identifying the earliest anatomic loci of neurodegeneration and recalibrating biofluid biomarkers using a cohort rather than case-control design, we will facilitate the critical need for earlier interventions to ensure the success of emergent clinical trials.
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