Biomarkers.

Background: Population-based functional connectomes help explain heterogeneity in tau spread in Alzheimer's disease by demonstrating spread among connected neurons from canonical epicenters. However, if the hypothesis of cell-to-cell transmission of tau is correct, individual structural connectomes seeded from individual-specific epicenters of PET-tau pathology should improve prediction of regional tau patterns.

Method: 86 participants from the Penn Aging Brain Cohort and 158 participants from ADNI with multi-shell diffusion MRI and AV1451 Tau PET within 18 months of each other were included. A schematic of methods is shown in Figure 1. Tau PET standard uptake value ratios were converted to Tau Pathology Indices (TPI) based on Gaussian-mixed models. Regions > 2.5 standard deviations above the mean TPI within an individual were used as individualized epicenters, while entorhinal cortex (ERC) was used as a canonical group epicenter. Probabilistic tractography generated individual connectomes and a group connectome in amyloid-negative participants. Network-analysis calculated structural connectivity distances from epicenters for each region. Data were re-arranged by tau pathology rank to average across all participants using each combination of individualized and group epicenters and connectomes. The model of Regional TPI = β*Distance + ε was tested in the training dataset using each of the 4 approaches: 1) Group canonical epicenter and group connectome (GE-GC), 2) Group canonical epicenter and individual connectome (GE-IC), 3) Individualized epicenters and group connectome (IE-GC), and 4) Individualized epicenters and connectomes (IE-IC). The resulting models were then applied to the validation dataset to predict regional TPI and compare to actual TPI.

Result: The fully individualized model demonstrated a significantly stronger relationship between connectivity and regional tau burden (β = -0.95[-1.03, -0.87]) compared to all other models (Z = -5.81, p < .001, Figure 2). When the four trained models were applied to the validation dataset, the fully individualized model explained 80% of regional TPI variance, while the other models explained ≤ 52% (Figure 3).

Conclusion: Individualized structural connectomes and tau epicenters capture the heterogeneity of Alzheimer's disease and provide strong support for the cell-to-cell transmission of tau pathology in vivo.