Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Qc, H3A 1Y2, Canada.
Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada.
Brain. 2020 Feb 1;143(2):635-649. doi: 10.1093/brain/awz414.
Age being the main risk factor for Alzheimer's disease, it is particularly challenging to disentangle structural changes related to normal brain ageing from those specific to Alzheimer's disease. Most studies aiming to make this distinction focused on older adults only and on a priori anatomical regions. Drawing on a large, multi-cohort dataset ranging from young adults (n = 468; age range 18-35 years), to older adults with intact cognition (n = 431; age range 55-90 years) and with Alzheimer's disease (n = 50 with late mild cognitive impairment and 71 with Alzheimer's dementia, age range 56-88 years), we investigated grey matter organization and volume differences in ageing and Alzheimer's disease. Using independent component analysis on all participants' structural MRI, we first derived morphometric networks and extracted grey matter volume in each network. We also derived a measure of whole-brain grey matter pattern organization by correlating grey matter volume in all networks across all participants from the same cohort. We used logistic regressions and receiver operating characteristic analyses to evaluate how well grey matter volume in each network and whole-brain pattern could discriminate between ageing and Alzheimer's disease. Because increased heterogeneity is often reported as one of the main features characterizing brain ageing, we also evaluated interindividual heterogeneity within morphometric networks and across the whole-brain organization in ageing and Alzheimer's disease. Finally, to investigate the clinical validity of the different grey matter features, we evaluated whether grey matter volume or whole-brain pattern was related to clinical progression in cognitively normal older adults. Ageing and Alzheimer's disease contributed additive effects on grey matter volume in nearly all networks, except frontal lobe networks, where differences in grey matter were more specific to ageing. While no networks specifically discriminated Alzheimer's disease from ageing, heterogeneity in grey matter volumes across morphometric networks and in the whole-brain grey matter pattern characterized individuals with cognitive impairments. Preservation of the whole-brain grey matter pattern was also related to lower risk of developing cognitive impairment, more so than grey matter volume. These results suggest both ageing and Alzheimer's disease involve widespread atrophy, but that the clinical expression of Alzheimer's disease is uniquely associated with disruption of morphometric organization.
年龄是阿尔茨海默病的主要风险因素,因此很难将与正常大脑衰老相关的结构变化与特定于阿尔茨海默病的结构变化区分开来。大多数旨在做出这种区分的研究都只关注老年人和预先确定的解剖区域。本研究利用一个大型的多队列数据集,其中包括从年轻成年人(n=468;年龄范围 18-35 岁)到认知功能正常的老年人(n=431;年龄范围 55-90 岁)和患有阿尔茨海默病的老年人(n=50 例有轻度认知障碍和 71 例阿尔茨海默病痴呆,年龄范围 56-88 岁),研究了衰老和阿尔茨海默病中的灰质组织和体积差异。我们对所有参与者的结构 MRI 进行独立成分分析,首先得出形态网络,并提取每个网络中的灰质体积。我们还通过在同一队列的所有参与者中对所有网络的灰质体积进行相关,得出了一个全脑灰质模式组织的度量。我们使用逻辑回归和接收器操作特征分析来评估每个网络和全脑模式的灰质体积在多大程度上可以区分衰老和阿尔茨海默病。由于增加的异质性通常被报道为大脑衰老的主要特征之一,因此我们还评估了衰老和阿尔茨海默病中形态网络内和整个大脑组织内的个体间异质性。最后,为了研究不同灰质特征的临床有效性,我们评估了在认知正常的老年人中,灰质体积或全脑模式是否与临床进展有关。衰老和阿尔茨海默病对几乎所有网络中的灰质体积都有相加效应,除了额叶网络,那里的灰质差异更特定于衰老。虽然没有网络专门区分阿尔茨海默病与衰老,但形态网络之间和整个大脑灰质模式中的灰质体积异质性特征化了认知障碍个体。全脑灰质模式的保留也与认知障碍发展风险降低有关,比灰质体积更为相关。这些结果表明,衰老和阿尔茨海默病都涉及广泛的萎缩,但阿尔茨海默病的临床表现与形态组织的破坏独特相关。