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Updated: Jan 31, 2026

Evaluation of Motor Impairment in C. elegans Models of Amyotrophic Lateral Sclerosis
Published on: September 2, 2021
Biomarkers for Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Associated With Hexanucleotide Expansion
Mary Kay Floeter1, Tania F Gendron2
1National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.
Abstract:
Now that genetic testing can identify persons at risk for developing amyotrophic lateral sclerosis (ALS) many decades before symptoms begin, there is a critical need for biomarkers that signal the onset and progression of degeneration. The search for candidate disease biomarkers in patients with mutations in the gene C9orf72 has included imaging, physiology, and biofluid measurements. In cross-sectional imaging studies, C9+ ALS patients display diffuse reductions of gray and white matter integrity compared to ALS patients without mutations. This structural imaging signature overlaps with frontotemporal dementia (FTD), reflecting the frequent co-occurrence of cognitive impairment, even frank FTD, in C9+ ALS patients. Changes in functional connectivity occur as critical components of the networks associated with cognition and behavior degenerate. In presymptomatic C9+carriers, subtle differences in volumes of subcortical structures and functional connectivity can be detected, often decades before the typical family age of symptom onset. Dipeptide repeat proteins produced by the repeat expansion mutation are also measurable in the cerebrospinal fluid (CSF) of presymptomatic gene carriers, possibly throughout their lives. In contrast, a rise in the level of neurofilament proteins in the CSF appears to presage the onset of degeneration in presymptomatic carriers in one longitudinal study. Cross-sectional studies indicate that neurofilament protein levels may provide prognostic information for survival in C9+ ALS patients. Longitudinal studies will be needed to validate the candidate biomarkers discussed here. Understanding how these candidate biomarkers change over time is critical if they are to be used in future therapeutic decisions.
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