Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer's disease
Xiao, Y.; Spotorno, N.; An, L.; Bazinet, V.; Hansen, J. Y.; Strandberg, O.; Shafiei, G.; Bejhat, H. H.; Funck, T.; Salvado, G.; Stomrud, E.; Smith, R.; Palmqvist, S.; Ossenkoppele, R.; Mattsson-Carlgren, N.; Palomero-Gallagher, N.; Dagher, A.; Misic, B.; Hansson, O.; Vogel, J. W.
Show abstract
In Alzheimers disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale, biologically informed disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional {beta}-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- AI-driven fusion of neurological work-up for assessment of biological Alzheimer’s disease 98%
- Molecular estimation of neurodegeneration pseudotime in older brains 97%
- Cell-type-specific Alzheimer’s disease polygenic risk scores are associated with distinct disease processes in Alzheimer’s disease 96%
Similar papers in this journal
- Distinctive Whole-brain Cell-Types Predict Tissue Damage Patterns in Thirteen Neurodegenerative Conditions 95%
- Neurotransmitter Transporter/Receptor Co-Expression Shares Organizational Traits With Brain Structure And Function 95%
- Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex 94%
Similar papers in this journal
- Selective vulnerability and resilience to Alzheimer's disease tauopathy as a function of genes and the connectome 97%
- Tau-first subtype of Alzheimer's disease consistently identified across in vivo and post mortem studies 96%
- Default mode network tau predicts future clinical decline in atypical early Alzheimer’s disease 96%
Similar papers in this journal
- Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation 94%
- Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer's disease 94%
- How tasks change whole-brain functional organization to reveal brain-phenotype relationships 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.