基于体素形态测量的多变量中介分析揭示了从基因变异到阿尔茨海默病的神经变性途径。

Shizhuo Mu, Jingxuan Bao, Hanxiang Xu, Manu Shivakumar, Shu Yang, Xia Ning, Dokyoon Kim, Christos Davatzikos, Haochang Shou, Li Shen
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引用次数: 0

摘要

神经退行性过程越来越被认为是阿尔茨海默病(AD)发病机制的潜在致病因素。虽然许多研究都利用中介分析模型来阐明遗传变异与阿尔茨海默病诊断结果之间的内在机制,但大多数研究都主要关注作为中介因素的大脑区域测量,从而影响了成像数据的粒度。在我们的研究中,我们利用一个具有里程碑意义的AD队列的影像遗传学数据,对比了基于区域和基于体素的脑部测量结果作为影像内表型,并研究了它们在介导AD结果的遗传效应中的作用。我们的研究结果表明,使用基于体素的形态测量可提高统计能力。此外,我们还划定了SNP、脑容量和AD结果之间的特定中介途径,揭示了这些变量之间错综复杂的关系。
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Multivariate mediation analysis with voxel-based morphometry revealed the neurodegeneration pathways from genetic variants to Alzheimer's Disease.

Neurodegenerative processes are increasingly recognized as potential causative factors in Alzheimer's disease (AD) pathogenesis. While many studies have leveraged mediation analysis models to elucidate the underlying mechanisms linking genetic variants to AD diagnostic outcomes, the majority have predominantly focused on regional brain measure as a mediator, thereby compromising the granularity of the imaging data. In our investigation, using the imaging genetics data from a landmark AD cohort, we contrasted both region-based and voxel-based brain measurements as imaging endophenotypes, and examined their roles in mediating genetic effects on AD outcomes. Our findings underscored that using voxel-based morphometry offers enhanced statistical power. Moreover, we delineated specific mediation pathways between SNP, brain volume, and AD outcomes, shedding light on the intricate relationship among these variables.

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