Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India.
Multimodal Brain Image Analysis Laboratory (MBIAL), Neurobiology Research Center (NRC), National Institute of Mental Health and Neurosciences, Bangalore, India.
Brain Connect. 2019 Nov;9(9):730-741. doi: 10.1089/brain.2019.0676. Epub 2019 Oct 31.
Brain resting-state functional connectivity (rsFC), white matter (WM) integrity, and cortical morphometry, as well as neuropsychological performance, have seldom been studied together to differentiate Alzheimer's disease (AD), mild cognitive impairment (MCI), and elderly cognitively healthy comparison (eCHC) samples in the context of the same study. We examined brain rsFC in samples of patients with mild AD ( = 50) and MCI ( = 49) in comparison with eCHC samples ( = 48) and then explored whether rsFC abnormalities can be linked to underlying gray matter (GM) volumetric and/or WM microstructural abnormalities. The mild AD sample showed significantly increased rsFC in the executive control network (ECN) and dorsal attention network (DAN) compared with the eCHC sample, and increased rsFC in ECN compared with MCI. Brain regions corresponding to both these resting-state networks (RSNs) showed significant reduction in fractional anisotropy in mild AD in comparison with eCHC. Significant GM volumetric reductions were observed in brain regions corresponding to both RSNs in the mild AD sample compared with MCI as well as eCHC samples. The association of default mode network-DAN anticorrelation with cognitive performances differentiated mild AD and MCI from eCHC sample. These findings highlight the association between brain structural and functional abnormalities as well as cognitive impairment that enables differentiation between early AD, MCI, and eCHC samples.
脑静息态功能连接(rsFC)、白质(WM)完整性和皮质形态,以及神经心理学表现,很少在同一研究中同时研究以区分阿尔茨海默病(AD)、轻度认知障碍(MCI)和老年认知健康对照组(eCHC)样本。我们检查了轻度 AD 患者(n=50)和 MCI 患者(n=49)的脑 rsFC,然后探索 rsFC 异常是否与潜在的灰质(GM)体积和/或 WM 微观结构异常有关。与 eCHC 样本相比,轻度 AD 样本的执行控制网络(ECN)和背侧注意网络(DAN)的 rsFC 显著增加,与 MCI 相比,ECN 的 rsFC 也增加了。与这两个静息态网络(RSN)相对应的脑区在轻度 AD 中与 eCHC 相比,各向异性分数显著降低。与 MCI 相比,轻度 AD 样本中与这两个 RSN 相对应的脑区的 GM 体积显著减少,与 eCHC 样本相比也是如此。默认模式网络-DAN 反相关与认知表现的关联将轻度 AD 和 MCI 与 eCHC 样本区分开来。这些发现强调了脑结构和功能异常与认知障碍之间的关联,这使得能够区分早期 AD、MCI 和 eCHC 样本。