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针对大脑和认知的与年龄相关的差异进行多模态成像和连接组拓扑特征分析。

Targeting age-related differences in brain and cognition with multimodal imaging and connectome topography profiling.

机构信息

Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

Laboratory of Brain and Cognition, Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.

出版信息

Hum Brain Mapp. 2019 Dec 15;40(18):5213-5230. doi: 10.1002/hbm.24767. Epub 2019 Aug 24.

Abstract

Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open-access healthy cohort (n = 102, age range = 30-89 years) with MRI and Aβ PET data, we estimated age-related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface-based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting-state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory-motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long-axis. While age-related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher-order transmodal regions. Age-related atrophy was greater toward the posterior end of the hippocampal long-axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography-specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain-based biomarkers of aging.

摘要

衰老是大脑结构和代谢变化的积累。最近的研究表明,跨模态脑网络对衰老特别敏感,我们假设这可能是由于它们在皮质层次结构中的顶端位置。我们研究了一个具有 MRI 和 Aβ PET 数据的开放访问健康队列(n=102,年龄范围为 30-89 岁),估计了与年龄相关的皮质变薄、海马萎缩和 Aβ 沉积。除了进行基于表面的形态学和代谢映射实验外,我们还沿着来自独立数据集的新皮质和海马静息态功能连接组梯度分层了效应。皮质梯度描绘了从感觉运动区域到跨模态区域的功能分化轴,而海马梯度则再现了其长轴。虽然与年龄相关的变薄和 Aβ 沉积发生在整个皮质地形上,但在更高阶的跨模态区域,Aβ 沉积的增加更为明显。与海马长轴的后端相比,与年龄相关的萎缩更为明显。在海马体中未观察到年龄对 Aβ 沉积有显著影响。成像标志物以特定于地形的方式与流体智力和情景记忆的行为测量相关,这一点通过单变量和多变量分析得到了证实。我们的结果加强了衰老大脑中结构和代谢变化的现有证据,并支持使用连接梯度作为分析和概念化衰老大脑生物标志物的紧凑框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02a9/6864903/d963b801969b/HBM-40-5213-g001.jpg

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