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与尸检确认的LATE-NC相关的灰质结构共变性网络模式与阿尔茨海默病病理学相比

Kaicheng Li¹, Xiao Luo¹, Qingze Zeng¹

¹Department of Radiology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.

Neurobiology of disease

|November 17, 2023

概括

结构共变性网络 (SCN) 揭示了与临界主导的与年龄相关的TDP-43脑病变 (LATE-NC),阿尔茨海默病 (AD) 和混合AD+LATE-NC的独特模式. 这些发现可能有助于区分痴呆症类型,并指导临床干预.

科学领域:

神经成像是一种神经成像.
神经病理学神经病理学
生物标志物发现发现

背景情况:

临主导的与年龄相关的TDP-43脑病变神经病理变化 (LATE-NC),阿尔茨海默病 (AD) 和混合AD+LATE-NC存在重叠症状,使诊断复杂化.
了解潜在的神经病理机制对于开发有效的临床干预至关重要.

研究的目的:

探索LATE-NC,AD和AD+LATE-NC中的结构共变性网络 (SCN) 模式.
为了识别潜在的神经成像生物标志物来区分这些痴呆症亚型.

主要方法:

利用来自ADNI尸检样本的死前MRI数据,包括LATE-NC,AD和AD+LATE-NC病例.
在默认模式网络 (DMN),突出网络 (SN) 和执行控制网络 (ECN) 中,由关键区域定定义的结构共变网络 (SCN).
采用基于多回归模型的线性相互作用分析来评估SCN交替.

主要成果:

尸检确认的LATE-NC和AD病例在DMN,ECN和SN中表现出增加的结构关联.
AD+LATE-NC病例显示DMN内部结构关联增加,但DMN和ECN之间的网络间关联减少.
峰值集群体积与认知功能和AD病理学有显著的相关性.

结论:

在LATE-NC,AD和AD+LATE-NC中观察到明显的SCN模式,突出了网络断开机制的进展.
SCN显示出作为有效的生物标志物,有望区分不同类型的痴呆症.

关键词:

阿尔茨海默病的疾病阿尔茨海默病的疾病.尸体解剖的结果是灰色物质的结构共变性在LATE-NC时代.边缘 TDP-43 的时间.混合病理学的混合病理.

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