Neuron
Volume 73, Issue 6, 22 March 2012, Pages 1216-1227
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Article
Predicting Regional Neurodegeneration from the Healthy Brain Functional Connectome

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Summary

Neurodegenerative diseases target large-scale neural networks. Four competing mechanistic hypotheses have been proposed to explain network-based disease patterning: nodal stress, transneuronal spread, trophic failure, and shared vulnerability. Here, we used task-free fMRI to derive the healthy intrinsic connectivity patterns seeded by brain regions vulnerable to any of five distinct neurodegenerative diseases. These data enabled us to investigate how intrinsic connectivity in health predicts region-by-region vulnerability to disease. For each illness, specific regions emerged as critical network “epicenters” whose normal connectivity profiles most resembled the disease-associated atrophy pattern. Graph theoretical analyses in healthy subjects revealed that regions with higher total connectional flow and, more consistently, shorter functional paths to the epicenters, showed greater disease-related vulnerability. These findings best fit a transneuronal spread model of network-based vulnerability. Molecular pathological approaches may help clarify what makes each epicenter vulnerable to its targeting disease and how toxic protein species travel between networked brain structures.

Highlights

► Task-free fMRI identified network “epicenters” for five neurodegenerative diseases ► Graph theory used to test model-based connectivity-vulnerability predictions ► Network connectivity in health predicted vulnerability to each disease ► Findings best fit a transneuronal spread model of network-based vulnerability

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Present address: Neuroscience and Behavioral Disorders Program, Duke-NUS Graduate Medical School, and Agency for Science, Technology and Research, Neuroscience Research Partnership, 169857 Singapore