Wang Selena, Wang Yiting, Xu Frederick H, Tian Xinyuan, Fredericks Carolyn A, Shen Li, Zhao Yize
Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Department of Statistics, University of Virginia, Charlottesville, Virginia, USA.
Alzheimers Dement. 2024 Dec;20(12):8387-8401. doi: 10.1002/alz.14266. Epub 2024 Nov 12.
We investigate sex-specific topological structures associated with typical Alzheimer's disease (AD) dementia using a novel state-of-the-art latent space estimation technique.
This study applies a probabilistic approach for latent space estimation that extends current multiplex network modeling approaches and captures the higher-order dependence in functional connectomes by preserving transitivity and modularity structures.
We find sex differences in network topology with females showing more default mode network (DMN)-centered hyperactivity and males showing more limbic system (LS)-centered hyperactivity, while both show DMN-centered hypoactivity. We find that centrality plays an important role in dementia-related dysfunction with stronger association between connectivity changes and regional centrality in females than in males.
The study contributes to the current literature by providing a more comprehensive picture of dementia-related neurodegeneration linking centrality, network segregation, and DMN-centered changes in functional connectomes, and how these components of neurodegeneration differ between the sexes.
We find evidence supporting the active role network topology plays in neurodegeneration with an imbalance between the excitatory and inhibitory mechanisms that can lead to whole-brain destabilization in dementia patients. We find sex-based differences in network topology with females showing more default mode network (DMN)-centered hyperactivity, males showing more limbic system (LS)-centered hyperactivity, while both show DMN-centered hypoactivity. We find that brain region centrality plays an important role in dementia-related dysfunction with a stronger association between connectivity changes and regional centrality in females than in males. Females, compared to males, tend to exhibit stronger dementia-related changes in regions that are the central actors of the brain networks. Taken together, this research uniquely contributes to the current literature by providing a more comprehensive picture of dementia-related neurodegeneration linking centrality, network segregation, and DMN-centered changes in functional connectomes, and how these components of neurodegeneration differ between the sexes.
我们使用一种新颖的先进潜在空间估计技术，研究与典型阿尔茨海默病（AD）痴呆相关的性别特异性拓扑结构。
本研究应用一种用于潜在空间估计的概率方法，该方法扩展了当前的多重网络建模方法，并通过保留传递性和模块化结构来捕捉功能连接组中的高阶依赖性。
我们发现网络拓扑结构存在性别差异，女性表现出更多以默认模式网络（DMN）为中心的活动亢进，男性表现出更多以边缘系统（LS）为中心的活动亢进，而两者均表现出以DMN为中心的活动减退。我们发现中心性在痴呆相关功能障碍中起重要作用，女性连接性变化与区域中心性之间的关联比男性更强。
该研究通过提供一幅更全面的与痴呆相关的神经退行性变图景，将中心性、网络分离以及功能连接组中以DMN为中心的变化联系起来，以及这些神经退行性变的组成部分在性别之间如何不同，为当前文献做出了贡献。
我们发现有证据支持网络拓扑结构在神经退行性变中发挥的积极作用，即兴奋和抑制机制之间的失衡会导致痴呆患者全脑不稳定。我们发现网络拓扑结构存在基于性别的差异，女性表现出更多以默认模式网络（DMN）为中心的活动亢进，男性表现出更多以边缘系统（LS）为中心的活动亢进，而两者均表现出以DMN为中心的活动减退。我们发现脑区中心性在痴呆相关功能障碍中起重要作用，女性连接性变化与区域中心性之间的关联比男性更强。与男性相比，女性往往在作为脑网络核心参与者的区域表现出更强的与痴呆相关的变化。综上所述，本研究通过提供一幅更全面的与痴呆相关的神经退行性变图景，将中心性、网络分离以及功能连接组中以DMN为中心的变化联系起来，以及这些神经退行性变的组成部分在性别之间如何不同，为当前文献做出了独特贡献。
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