Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease

Abstract

In Alzheimer's disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts in clinical trials. Since tau is assumed to spread throughout connected regions, we used functional connectivity to improve tau spreading predictions over Braak staging methods. We included two samples with longitudinal tau-PET from controls and AD patients. Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences. Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters. A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage-specific readouts and reduced sample sizes by ~40% in simulated tau-targeting interventions. Thus, connectivity-based tau spreading models may show utility in clinical trials.