Computational modeling of tau pathology spread reveals patterns of regional vulnerability and the impact of a genetic risk factor

tau 病理扩散的计算模型揭示了区域脆弱性的模式和遗传风险因素的影响

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作者:Eli J Cornblath, Howard L Li, Lakshmi Changolkar, Bin Zhang, Hannah J Brown, Ronald J Gathagan, Modupe F Olufemi, John Q Trojanowski, Danielle S Bassett, Virginia M Y Lee, Michael X Henderson

Abstract

Neuropathological staging studies have suggested that tau pathology spreads through the brain in Alzheimer's disease (AD) and other tauopathies, but it is unclear how neuroanatomical connections, spatial proximity, and regional vulnerability contribute. In this study, we seed tau pathology in the brains of nontransgenic mice with AD tau and quantify pathology development over 9 months in 134 brain regions. Network modeling of pathology progression shows that diffusion through the connectome is the best predictor of tau pathology patterns. Further, deviations from pure neuroanatomical spread are used to estimate regional vulnerability to tau pathology and identify related gene expression patterns. Last, we show that pathology spread is altered in mice harboring a mutation in leucine-rich repeat kinase 2. While tau pathology spread is still constrained by anatomical connectivity in these mice, it spreads preferentially in a retrograde direction. This study provides a framework for understanding neuropathological progression in tauopathies.

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