A Network Diffusion Model of Disease Progression in Dementia

• Published in: Neuron (Cambridge, Mass.) Mass.), 2012-03, Vol.73 (6), p.1204-1215
• Main Authors: Raj, Ashish, Kuceyeski, Amy, Weiner, Michael
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Age; Age Factors; Aged; Aging; Alzheimer Disease - pathology; Alzheimer Disease - physiopathology; Alzheimer's disease; Atrophy; Behavior; beta -Amyloid; Biophysics; Brain; Brain - pathology; Brain Mapping; Case-Control Studies; Data processing; Dementia; Dementia - pathology; Dementia - physiopathology; Dementia disorders; Differential diagnosis; Diffusion; Disease Progression; Disease transmission; Female; Frontotemporal dementia; Frontotemporal Dementia - pathology; Frontotemporal Dementia - physiopathology; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Mathematical models; Middle Aged; Models, Neurological; Neural networks; Neural Pathways - pathology; Neurodegenerative diseases; Neuropathology; Neurotransmission; Predictive Value of Tests; Propagation; Proteins; Psychiatric Status Rating Scales; Reproducibility of Results; ROC Curve; Statistics as Topic; Studies; Tau protein; Young Adult
• ISSN: 0896-6273; 1097-4199
• DOI: 10.1016/j.neuron.2011.12.040

Patterns of dementia are known to fall into dissociated but dispersed brain networks, suggesting that the disease is transmitted along neuronal pathways rather than by proximity. This view is supported by neuropathological evidence for “prion-like” transsynaptic transmission of disease agents like misfolded tau and beta amyloid. We mathematically model this transmission by a diffusive mechanism mediated by the brain's connectivity network obtained from tractography of 14 healthy-brain MRIs. Subsequent graph theoretic analysis provides a fully quantitative, testable, predictive model of dementia. Specifically, we predict spatially distinct “persistent modes,” which, we found, recapitulate known patterns of dementia and match recent reports of selectively vulnerable dissociated brain networks. Model predictions also closely match T1-weighted MRI volumetrics of 18 Alzheimer's and 18 frontotemporal dementia subjects. Prevalence rates predicted by the model strongly agree with published data. This work has many important implications, including dimensionality reduction, differential diagnosis, and especially prediction of future atrophy using baseline MRI morphometrics. ► Modeling of transsynaptic/network transmission via connectivity in healthy brain ► Network diffusion model of healthy brain connectivity predicts “persistent modes” ► Healthy-brain “persistent modes” recapitulate regions targeted in dementia Patterns of dementia vulnerability are known to fall into dissociated but dispersed brain networks. By mathematical modeling and graph theory analyses in healthy-brain and comparison with disease atrophy patterns, Raj et al. provide support for the idea of network diffusion-mediated disease transmission.