Dementia Spreads via Connected Brain Networks

Technology Networks | October 15, 2019

In a new study, UC San Francisco scientists used maps of brain connections to predict how brain atrophy would spread in individual patients with frontotemporal dementia (FTD), adding to growing evidence that the loss of brain cells associated with dementia spreads via the synaptic connections between established brain networks. The results advance scientists’ knowledge of how neurodegeneration spreads and could lead to new clinical tools to evaluate how well novel treatments slow or block the predicted trajectory of these diseases. “Knowing how dementia spreads opens a window onto the biological mechanisms of the disease — what parts of our cells or neural circuits are most vulnerable,” said study lead author Jesse Brown, PhD, an assistant professor of neurology at the UCSF Memory and Aging Center and UCSF Weill Institute for Neurosciences. “You can’t really design a treatment until you know what you’re treating.” FTD, the most common form of dementia in people under the age of 60, comprises a group of neurodegenerative conditions with diverse linguistic and behavioral symptoms. As in Alzheimer’s disease, the diversity of FTD symptoms reflects significant differences in how the neurodegenerative disease spreads through patients’ brains. This variability makes it difficult for scientists searching for cures to pin down the biological drivers of brain atrophy and for clinical trials to evaluate whether a novel treatment is making a difference in the progression of a patient’s disease.

Spotlight

This white paper employs a case study of three biotechnology and three pharmaceutical companies to demonstrate how those techniques can be applied to examining large data sets to measure large and small molecule drug pipeline trends. Nerac’s information analysis was applied to non-patent and patent data to reach conclusions about drug development trends.

Spotlight

This white paper employs a case study of three biotechnology and three pharmaceutical companies to demonstrate how those techniques can be applied to examining large data sets to measure large and small molecule drug pipeline trends. Nerac’s information analysis was applied to non-patent and patent data to reach conclusions about drug development trends.

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