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New Models Predict Patterns Of Brain Damage In Dementia

March 21, 2012

Two breakthrough studies may explain why we see distinct patterns of brain damage associated with dementias, such as Alzheimer’s disease, and could be useful for predicting future cognitive decline in patients. These independent studies published by Cell Press in the March 22 issue of the journal Neuron, one studying how brain circuits wire up structurally and the other studying their functional connections, converged on a remarkably similar model that predicted the landscape of degeneration in various forms of dementia. This is particularly significant because, until now, models for predicting regional neurodegeneration in humans have remained elusive.

Different dementias involve distinct parts of the brain, and previous research has led to the theory that neurodegenerative diseases target specific networks of neurons that are linked by connectivity rather than spatial proximity. Further, this neurodegenerative process is thought to involve the accumulation of abnormal toxic proteins and possibly even the spread of these proteins between neurons, which my travel from neuron to neuron through their synaptic connections.

One study, led by Drs. Juan Zhou and William Seeley, from the University of California, San Francisco, addressed this theory. “We were interested in whether knowing the healthy brain’s functional “wiring diagram” would help us predict specific patterns of neurodegeneration seen in patients,” explains Dr. Seeley. “For each illness we studied, specific regions emerged as critical network ‘epicenters,’ and functional connectivity to these epicenters predicted each region’s vulnerability. The findings best fit a model wherein disease spreads from neuron to neuron along network connections that link brain structures.”

In a separate study, led by Dr. Ashish Raj from Weill Medical College of Cornell University, researchers modeled this same kind of “transneuronal” disease transmission by mathematically analyzing structural connectivity networks obtained from healthy brain MRIs. Their model predicted spatially distinct “eigenmodes,” tightly connected subnetworks in the brain, which mirrored classic patterns of damage seen in dementia.

“Our findings provide the first plausible explanation of why various dementias appear to selectively target distinct regions of the brain–as a simple mechanical consequence of transneuronal spread within the brain networks. This also suggests that all dementias, previously considered to be pathologically distinct, might share a common progression mechanism,” concludes Dr. Raj. “Importantly, this model of disease progression may be useful clinically for prediction of future cognitive decline in patients, based on their current MRI scans. Knowledge of what the future holds would allow patients to make informed choices regarding their lifestyle and therapeutic interventions.”

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