Aberrant morphometric networks in Alzheimer's disease have hemispheric asymmetry and age dependence

内嗅皮质 中心性 萎缩 神经科学 脑功能偏侧化 心理学 相关性 皮质(解剖学) 海马旁回 阿尔茨海默病 痴呆 疾病 海马结构 医学 颞叶 内科学 癫痫 组合数学 几何学 数学
作者
Hiroyuki Maruoka,Takaaki Hattori,Takeshi Hase,Kunihiko Takahashi,Masahiro Ohara,Satoshi Orimo,Takanori Yokota
出处
期刊:European Journal of Neuroscience [Wiley]
卷期号:59 (6): 1332-1347 被引量:1
标识
DOI:10.1111/ejn.16225
摘要

Abstract Alzheimer's disease (AD) is associated with abnormal accumulations of hyperphosphorylated tau and amyloid‐β proteins, resulting in unique patterns of atrophy in the brain. We aimed to elucidate some characteristics of the AD's morphometric networks constructed by associating different morphometric features among brain areas and evaluating their relationship to Mini‐Mental State Examination total score and age. Three‐dimensional T1‐weighted (3DT1) image data scanned by the same 1.5T magnetic resonance imaging (MRI) were obtained from 62 AD patients and 41 healthy controls (HCs) and were analysed by using FreeSurfer. The associations of the extracted six morphometric features between regions were estimated by correlation coefficients. The global and local graph theoretical measures for this network were evaluated. Associations between graph theoretical measures and age, sex and cognition were evaluated by multiple regression analysis in each group. Global measures of integration: global efficiency and mean information centrality were significantly higher in AD patients. Local measures of integration: node global efficiency and information centrality were significantly higher in the entorhinal cortex, fusiform gyrus and posterior cingulate cortex of AD patients but only in the left hemisphere. All global measures were correlated with age in AD patients but not in HCs. The information centrality was associated with age in AD's broad brain regions. Our results showed that altered morphometric networks due to AD are left‐hemisphere dominant, suggesting that AD pathogenesis has a left–right asymmetry. Ageing has a unique impact on the morphometric networks in AD patients. The information centrality is a sensitive graph theoretical measure to detect this association.
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