The finding, based on new magnetic resonance imaging research (MRI), raises
hopes that physicians may be able to use MRI to predict the course of dementias
-- depending on where within an affected network degenerative damage is first
discovered -- and that researchers may use these predicted outcomes to determine
whether a new treatment is working. Network modeling combined with functional
MRI might serve as an intermediate biomarker to gauge drug efficacy in clinical
trials before behavioral changes become measurable, according to Seeley.
"Our next goal is to further develop methods to predict disease progression, using these models to create a template for how disease will progress in the brain of an affected individual," Seeley said. "Already this work suggests that if we know the wiring diagram in a healthy brain, we can predict where the disease is going to go next. Once we can predict how the network will change over time we can predict how the patient's behavior will change over time and we can monitor whether a potential therapy is working."
The new evidence suggests that different kinds of dementias spread from neuron to neuron in similar ways, even though they act on different brain networks, according to Seeley. Seeley's previous work and earlier clinical and anatomical studies showed that the patterns of damage in the dementias are linked to particular networks of nerve cells, but until now scientists have found it difficult to evaluate in humans their ideas about how this neurodegeneration occurs.
In the current study, the researchers modeled not only the normal nerve network that can be affected by Alzheimer's disease, but also those networks affected by frontotemporal dementia (FTD) and related disorders, a class of degenerative brain diseases identified by their devastating impact on social behaviors or language skills.
The scientists mapped brain connectedness in 12 healthy people. Then they used data from patients with the five different diseases to map and compare specific regions within the networks that are damaged by the different dementias.
"For each dementia, we looked at four ideas that scientists often bring up to explain how dementia might target brain networks," Seeley said. "The different proposed mechanisms lead to different predictions about how a region's place in the healthy network affects its vulnerability to disease."
In the "nodal stress" hypothesis, small regions within the brain that serve as hubs to carry heavy signaling traffic would undergo wear and tear that gives rise to or worsens disease. In the "trophic failure" mechanism, breakdowns in connectivity would disrupt transport through the network of growth factors needed to maintain neurons. In the "shared vulnerability" mechanism, specific genes or proteins common to neurons in a network would make them more susceptible to disease. But predictions from the "trans-neuronal spread" mechanism model best fit the network connectivity maps constructed by the researchers.
"The trans-neuronal spread model predicts that the more closely connected a region is to the node of disease onset -- which we call the epicenter -- then the more vulnerable that region will be once the disease begins to spread," Seeley said. "It's as if the disease is emanating from a point of origin, but it can reach any given target faster if there is a stronger connection."
The scientists tracked and analyzed linkages within nerve networks that the dementias target. They used a technique called functional connectivity MRI to measure and spatially represent activity in specific regions of key networks in the brains of the healthy subjects. The MRI readout allowed the researchers to model each region within the network as a distinct but interconnected node. They ranked the nodes that most consistently fired together as being the most closely connected.
Across the five diseases investigated in the study, trans-neuronal spread was the proposed mechanism for which the data best matched the predictions. Previous studies of animals and cells in the laboratory also support the idea that disease-related proteins can spread from an affected neuron to other neurons via intercellular connections.
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"Our next goal is to further develop methods to predict disease progression, using these models to create a template for how disease will progress in the brain of an affected individual," Seeley said. "Already this work suggests that if we know the wiring diagram in a healthy brain, we can predict where the disease is going to go next. Once we can predict how the network will change over time we can predict how the patient's behavior will change over time and we can monitor whether a potential therapy is working."
The new evidence suggests that different kinds of dementias spread from neuron to neuron in similar ways, even though they act on different brain networks, according to Seeley. Seeley's previous work and earlier clinical and anatomical studies showed that the patterns of damage in the dementias are linked to particular networks of nerve cells, but until now scientists have found it difficult to evaluate in humans their ideas about how this neurodegeneration occurs.
In the current study, the researchers modeled not only the normal nerve network that can be affected by Alzheimer's disease, but also those networks affected by frontotemporal dementia (FTD) and related disorders, a class of degenerative brain diseases identified by their devastating impact on social behaviors or language skills.
The scientists mapped brain connectedness in 12 healthy people. Then they used data from patients with the five different diseases to map and compare specific regions within the networks that are damaged by the different dementias.
"For each dementia, we looked at four ideas that scientists often bring up to explain how dementia might target brain networks," Seeley said. "The different proposed mechanisms lead to different predictions about how a region's place in the healthy network affects its vulnerability to disease."
In the "nodal stress" hypothesis, small regions within the brain that serve as hubs to carry heavy signaling traffic would undergo wear and tear that gives rise to or worsens disease. In the "trophic failure" mechanism, breakdowns in connectivity would disrupt transport through the network of growth factors needed to maintain neurons. In the "shared vulnerability" mechanism, specific genes or proteins common to neurons in a network would make them more susceptible to disease. But predictions from the "trans-neuronal spread" mechanism model best fit the network connectivity maps constructed by the researchers.
"The trans-neuronal spread model predicts that the more closely connected a region is to the node of disease onset -- which we call the epicenter -- then the more vulnerable that region will be once the disease begins to spread," Seeley said. "It's as if the disease is emanating from a point of origin, but it can reach any given target faster if there is a stronger connection."
The scientists tracked and analyzed linkages within nerve networks that the dementias target. They used a technique called functional connectivity MRI to measure and spatially represent activity in specific regions of key networks in the brains of the healthy subjects. The MRI readout allowed the researchers to model each region within the network as a distinct but interconnected node. They ranked the nodes that most consistently fired together as being the most closely connected.
Across the five diseases investigated in the study, trans-neuronal spread was the proposed mechanism for which the data best matched the predictions. Previous studies of animals and cells in the laboratory also support the idea that disease-related proteins can spread from an affected neuron to other neurons via intercellular connections.
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