Affiliations: [a] Department of Computer Science, Wake Forest University, Winston-Salem, NC, USA
| [b] Department of Mathematics, University of North Georgia, Oakwood, GA, USA
| [c] Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| [d] Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| [e] Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| [f] Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Correspondence:
[*]
Correspondence to: Minghan Chen, Department of Computer Science, Wake Forest University, 1834 Wake Forest Road, Winston-Salem, NC 27109, USA. E-mail: chenm@wfu.edu.
Abstract: Background:Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-β (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive. Objective:To disentangle the massive heterogeneities in Alzheimer’s disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology. Methods:In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains. Results:Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development. Conclusions:Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-β and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.
Keywords: Alzheimer’s disease, AT[N] biomarkers, brain network, reaction-diffusion model, vulnerable and critical regions
