Ziontz Jacob, Harrison Theresa M, Fonseca Corrina, Giorgio Joseph, Han Feng, Lee JiaQie, Jagust William J
Department of Neuroscience, UC Berkeley, Berkeley, California, USA.
School of Psychological Sciences, College of Engineering, Science and the Environment, University of Newcastle, Newcastle, New South Wales, Australia.
Hum Brain Mapp. 2024 Dec 1;45(17):e70083. doi: 10.1002/hbm.70083.
Tau pathology spread into neocortex indicates a transition from healthy aging to Alzheimer's disease (AD). Connectivity between tau epicenters and later accumulating regions of cortex has been proposed as a mechanism of tau spread, but how this relationship changes with greater AD pathology burden or genotype is not understood. We investigated tau accumulation in two key regions, precuneus and inferior temporal cortex, using resting state functional connectivity (rsFC) and longitudinal PET imaging from a multicohort sample of cognitively unimpaired older adults. We examined how baseline tau PET, Aβ PET, and ApoE4 genotype status interact with rsFC between hippocampus and these downstream regions to predict rate of tau accumulation in neocortex. We found that the 3-way interaction between connectivity, baseline tau, and baseline Aβ or ApoE4 status was associated with neocortical tau accumulation in precuneus and inferior temporal cortex. In addition, baseline tau, Aβ, and ApoE4 status also moderated the association between connectivity and rate of memory decline. Together, these results suggest that the extent and distribution of future tau accumulation may be predicted by the interaction of baseline connectivity, AD pathology, and genetic risk.
tau病理扩散至新皮层表明从健康衰老向阿尔茨海默病（AD）的转变。tau蛋白聚集中心与皮层后期累积区域之间的连接性被认为是tau蛋白扩散的一种机制，但这种关系如何随AD病理负担加重或基因型改变而变化尚不清楚。我们使用静息态功能连接（rsFC）以及来自认知未受损老年人多队列样本的纵向PET成像，研究了楔前叶和颞下回这两个关键区域的tau蛋白积累情况。我们研究了基线tau PET、Aβ PET和ApoE4基因型状态如何与海马体和这些下游区域之间的rsFC相互作用，以预测新皮层中tau蛋白积累的速率。我们发现，连接性、基线tau蛋白以及基线Aβ或ApoE4状态之间的三因素相互作用与楔前叶和颞下回的新皮层tau蛋白积累相关。此外，基线tau蛋白、Aβ和ApoE4状态还调节了连接性与记忆衰退速率之间的关联。总之，这些结果表明，未来tau蛋白积累的程度和分布可能由基线连接性、AD病理和遗传风险的相互作用来预测。
