Liu Yong, Yu Chunshui, Zhang Xinqing, Liu Jieqiong, Duan Yunyun, Alexander-Bloch Aaron F, Liu Bing, Jiang Tianzi, Bullmore Ed
LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing 100190, China.
Cereb Cortex. 2014 Jun;24(6):1422-35. doi: 10.1093/cercor/bhs410. Epub 2013 Jan 11.
Alzheimer's disease (AD) is increasingly recognized as a disconnection syndrome, which leads to cognitive impairment due to the disruption of functional activity across large networks or systems of interconnected brain regions. We explored abnormal functional magnetic resonance imaging (fMRI) resting-state dynamics, functional connectivity, and weighted functional networks, in a sample of patients with severe AD (N = 18) and age-matched healthy volunteers (N = 21). We found that patients had reduced amplitude and regional homogeneity of low-frequency fMRI oscillations, and reduced the strength of functional connectivity, in several regions previously described as components of the default mode network, for example, medial posterior parietal cortex and dorsal medial prefrontal cortex. In patients with severe AD, functional connectivity was particularly attenuated between regions that were separated by a greater physical distance; and loss of long distance connectivity was associated with less efficient global and nodal network topology. This profile of functional abnormality in severe AD was consistent with the results of a comparable analysis of data on 2 additional groups of patients with mild AD (N = 17) and amnestic mild cognitive impairment (MCI; N = 18). A greater degree of cognitive impairment, measured by the mini-mental state examination across all patient groups, was correlated with greater attenuation of functional connectivity, particularly over long connection distances, for example, between anterior and posterior components of the default mode network, and greater reduction of global and nodal network efficiency. These results indicate that neurodegenerative disruption of fMRI oscillations and connectivity in AD affects long-distance connections to hub nodes, with the consequent loss of network efficiency. This profile was evident also to a lesser degree in the patients with less severe cognitive impairment, indicating that the potential of resting-state fMRI measures as biomarkers or predictors of disease progression in AD.
阿尔茨海默病(AD)越来越被认为是一种连接障碍综合征,由于相互连接的大脑区域的大型网络或系统中的功能活动中断,导致认知障碍。我们在一组重度AD患者(N = 18)和年龄匹配的健康志愿者(N = 21)中,探索了静息态功能磁共振成像(fMRI)的异常动力学、功能连接和加权功能网络。我们发现,患者在先前被描述为默认模式网络组成部分的几个区域,低频fMRI振荡的幅度和区域同质性降低,功能连接强度减弱,例如,顶叶后内侧皮质和前额叶背内侧皮质。在重度AD患者中,功能连接在物理距离较远的区域之间尤其减弱;长距离连接的丧失与整体和节点网络拓扑效率降低有关。重度AD的这种功能异常特征与另外两组轻度AD患者(N = 17)和遗忘型轻度认知障碍(MCI;N = 18)的数据可比分析结果一致。在所有患者组中,通过简易精神状态检查测量的认知障碍程度越高,与功能连接的减弱程度越大相关,尤其是在长连接距离上,例如默认模式网络的前后组件之间,以及整体和节点网络效率的更大降低。这些结果表明,AD中fMRI振荡和连接的神经退行性破坏会影响到枢纽节点的长距离连接,从而导致网络效率丧失。这种特征在认知障碍较轻的患者中也有一定程度的体现,表明静息态fMRI测量作为AD疾病进展的生物标志物或预测指标的潜力。