Lu Yinping, Wang Luyao, Murai Toshiya, Wu Jinglong, Liang Dong, Zhang Zhilin
Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Institute of Biomedical Engineering, School of Life Sciences, Shanghai University, Shanghai 200444, China.
Neuroimage Clin. 2025 Mar 8;46:103764. doi: 10.1016/j.nicl.2025.103764.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the disconnection of white matter fibers and disrupted functional connectivity of gray matter; however, the pathological mechanisms linking structural and functional changes remain unclear. This study aimed to explore the interaction between the structural and functional brain network in AD using advanced structural-functional coupling (S-F coupling) models to assess whether these changes correlate with cognitive function, Aβ deposition levels, and gene expression. In this study, we utilized multimodal magnetic resonance imaging data from 41 individuals with AD, 112 individuals with mild cognitive impairment, and 102 healthy controls to explore these mechanisms. We applied different computational models to examine the changes in the S-F coupling associated with AD. Our results showed that the communication and graph harmonic models demonstrated greater heterogeneity and were more sensitive than the statistical models in detecting AD-related pathological changes. In addition, S-F coupling increases with AD progression at the global, subnetwork, and regional node levels, especially in the medial prefrontal and anterior cingulate cortices. The S-F coupling of these regions also partially mediated cognitive decline and Aβ deposition. Furthermore, gene enrichment analysis revealed that changes in S-F coupling were strongly associated with the regulation of cellular catabolic processes. This study advances our understanding of the interaction between structural and functional connectivity and highlights the importance of S-F coupling in elucidating the neural mechanisms underlying cognitive decline in AD.
阿尔茨海默病（AD）是一种进行性神经退行性疾病，其特征是白质纤维断开连接和灰质功能连接中断；然而，连接结构和功能变化的病理机制仍不清楚。本研究旨在使用先进的结构 - 功能耦合（S - F耦合）模型探索AD患者大脑结构和功能网络之间的相互作用，以评估这些变化是否与认知功能、淀粉样β蛋白（Aβ）沉积水平和基因表达相关。在本研究中，我们利用了来自41名AD患者、112名轻度认知障碍患者和102名健康对照者的多模态磁共振成像数据来探索这些机制。我们应用不同的计算模型来检查与AD相关的S - F耦合变化。我们的结果表明，在检测与AD相关的病理变化方面，通信模型和图调和模型表现出更大的异质性，并且比统计模型更敏感。此外，在全局、子网和区域节点水平上，S - F耦合随着AD进展而增加，特别是在内侧前额叶和前扣带回皮质。这些区域的S - F耦合也部分介导了认知衰退和Aβ沉积。此外，基因富集分析表明，S - F耦合的变化与细胞分解代谢过程的调节密切相关。本研究增进了我们对结构和功能连接之间相互作用的理解，并突出了S - F耦合在阐明AD认知衰退潜在神经机制方面的重要性。
