Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease.
Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease.
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DOI：
10.1093/braincomms/fcad058
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发表时间：
2023
影响因子：
4.8
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中科院分区：
文献类型：
--
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从复杂系统的角度来看，神经退行性疾病的临床症状被认为是错误折叠的蛋白质聚集体之间的多尺度相互作用的结果，以及支撑认知现象的大规模网络协调功能操作的失衡。在阿尔茨海默病的所有症状表现中，淀粉样蛋白沉积加速了与年龄相关的默认模式网络的破坏。相反，综合征变异性可能反映了支持特定认知能力的模块化网络的选择性神经退化。在这项研究中，我们利用人类连接组项目的广度-非痴呆患者的老龄化队列(N=724)作为标准队列，评估阿尔茨海默病默认模式网络功能障碍的生物标记物-网络失败商-跨年龄谱的稳健性。然后，我们检查了神经退行性变的网络失效商和局部标记物在患者水平上区分健忘型(N=8)或执行障碍型(N=10)阿尔茨海默病患者和正常队列患者的能力，以及阿尔茨海默病表型之间的区别。重要的是，所有参与者和患者都使用Human Connectome Project-Aging协议进行了扫描，从而能够获得高分辨率的结构成像和更长的静息状态连接性获取时间。使用回归框架，我们发现在标准化的人类连接组项目-老龄化队列中，网络故障商数与年龄、整体和局部皮质厚度、海马体体积和认知有关，复制了梅奥诊所使用不同扫描方案进行的老龄化研究的先前结果。然后，我们使用分位数曲线和分组比较来表明，网络失败商通常将执行障碍和健忘型阿尔茨海默病患者与正常队列区分开来。相反，局灶性神经变性标记物更具表型特异性，其中顶额区的神经变性与难治性阿尔茨海默病有关，而海马区和颞区的神经变性与遗忘性阿尔茨海默病有关。利用大量的标准队列和优化的成像采集方案，我们突出了默认模式网络故障的生物标记物和局灶性神经变性的生物标记物，该生物标记物反映了衰老、执行障碍和遗忘性阿尔茨海默病之间共享的系统级病理生理机制，以及局灶性神经变性的生物标记物，反映了遗忘性和执行障碍的阿尔茨海默病表型的不同致病过程。这些发现提供了证据，表明阿尔茨海默病患者个体间认知障碍的变异性可能与模块化网络退化和默认模式网络中断有关。这些结果为推进认知老化和退化的复杂系统方法提供了重要信息，扩大了可用于辅助诊断、监测进展和为临床试验提供信息的生物标志物的资料库。Corriveau-Lecavalier等人。表明与年龄相关的默认模式网络功能障碍在执行困难和遗忘性阿尔茨海默病中累积。然而，局灶性神经变性是这些表型的一个明显特征。这与认知老化和退化的先进复杂系统方法以及针对网络病理生理学的治疗方法有关。
From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer’s disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer’s disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer’s disease from the normative cohort at the patient level, as well as between Alzheimer’s disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer’s disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer’s disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer’s disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer’s disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer’s disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer’s disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials. Corriveau-Lecavalier et al. show that age-related default mode network dysfunction is accrued in dysexecutive and amnestic Alzheimer’s disease. However, focal neurodegeneration is a distinctive feature across these phenotypes. This is relevant to advance complex systems approaches to cognitive aging and degeneration and therapeutic approaches targeting network pathophysiology.
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影响因子：
6
作者：
Corriveau-Lecavalier N;Li W;Ramanan VK;Drubach DA;Day GS;Jones DT
通讯作者：
Jones DT
影响因子：
7.7
作者：
Adams, Jenna N.;Maass, Anne;Jagust, William J.
通讯作者：
Jagust, William J.
DOI：
10.1016/s1474-4422(20)30440-3
发表时间：
2021-03
期刊：
The Lancet. Neurology
影响因子：
--
作者：
Graff-Radford J;Yong KXX;Apostolova LG;Bouwman FH;Carrillo M;Dickerson BC;Rabinovici GD;Schott JM;Jones DT;Murray ME
通讯作者：
Murray ME
DOI：
10.1073/pnas.0308627101
发表时间：
2004-03-30
影响因子：
11.1
作者：
Greicius, MD;Srivastava, G;Menon, V
通讯作者：
Menon, V
影响因子：
16.2
作者：
Bakker A;Krauss GL;Albert MS;Speck CL;Jones LR;Stark CE;Yassa MA;Bassett SS;Shelton AL;Gallagher M
通讯作者：
Gallagher M