Journal of neurology, neurosurgery, and psychiatry
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J. Neurol. Neurosurg. Psychiatr. · Nov 2019
ReviewUnderstanding neurodegeneration after traumatic brain injury: from mechanisms to clinical trials in dementia.
Traumatic brain injury (TBI) leads to increased rates of dementia, including Alzheimer's disease. The mechanisms by which trauma can trigger neurodegeneration are increasingly understood. For example, diffuse axonal injury is implicated in disrupting microtubule function, providing the potential context for pathologies of tau and amyloid to develop. ⋯ Fluid biomarkers such as neurofilament light can complement neuroimaging, representing sensitive potential methods to track neurodegenerative processes that develop after TBI. These biomarkers could characterise endophenotypes associated with distinct types of post-traumatic neurodegeneration. In addition, they might profitably be used in clinical trials of neuroprotective and disease-modifying treatments, improving trial design by providing precise and sensitive measures of neuronal loss.
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J. Neurol. Neurosurg. Psychiatr. · Nov 2019
A multimodal MRI-based classification signature emerges just prior to symptom onset in frontotemporal dementia mutation carriers.
Multimodal MRI-based classification may aid early frontotemporal dementia (FTD) diagnosis. Recently, presymptomatic FTD mutation carriers, who have a high risk of developing FTD, were separated beyond chance level from controls using MRI-based classification. However, it is currently unknown how these scores from classification models progress as mutation carriers approach symptom onset. In this longitudinal study, we investigated multimodal MRI-based classification scores between presymptomatic FTD mutation carriers and controls. Furthermore, we contrasted carriers that converted during follow-up ('converters') and non-converting carriers ('non-converters'). ⋯ Our findings imply that presymptomatic FTD mutation carriers may remain similar to controls in terms of MRI-based classification scores until they are close to symptom onset. This proof-of-concept study shows the promise of longitudinal MRI data acquisition in combination with machine learning to contribute to early FTD diagnosis.