UCSF

Introduction

The stereotypical progression of Alzheimer's disease (AD) pathology is not fully understood. The selective impact of AD on distinct regions has led the field to question if innate vulnerability exists. This study aims to determine if the causative factors of regional vulnerability are dependent on cell-autonomous or transneuronal (non-cell autonomous) processes.

Methods

Using mathematical and statistical models, we analyzed the contribution of cell-autonomous and non-cell autonomous factors to predictive linear models of AD pathology.

Results

Results indicate gene expression as a weak contributor to predictive linear models of AD. Instead, the network diffusion model acts as a strong predictor of observed AD atrophy and hypometabolism.

Discussion

We propose a convenient methodology for identifying genes and their role in determining AD topography, in comparison with network spread. Results reinforce the role of transneuronal network spread on disease progression and suggest that innate gene expression plays a secondary role in seeding and subsequent disease progression.