Menardi Arianna, Saglam Ceren, La Rocca Beatrice, Cecchin Diego, Venneri Annalena, Cagnin Annachiara, Vallesi Antonino
Department of Neuroscience, University of Padova, 35128 Padova, Italy.
Padova Neuroscience Center, University of Padova, 35131 Padova, Italy.
Brain Commun. 2025 Aug 28;7(5):fcaf320. doi: 10.1093/braincomms/fcaf320. eCollection 2025.
Alzheimer's disease can be classified based on amyloid, tau and neurodegeneration status. The Default Mode Network is notably vulnerable to these processes, making early structural alterations in this network of particular interest for identifying prodromal biomarkers. In this longitudinal cross-sectional study, we analysed data from 279 participants in the Alzheimer's Disease Neuroimaging Initiative (mean age = 73.7 ± 9 years, 53.2% males). Structural measures-sulcal depth, gyrification and cortical thickness-were extracted for all Default Mode Network regions. Their ability to predict memory performance (encoding, retrieval and recall) was tested at baseline and 2-year follow-up by means of multiple linear regression models, which were all corrected for the risk of multiple comparisons. Covariates included Mini Mental State Examination scores, amyloid status and regional tau burden, to examine interactions with structural changes. Our results showed distinct Default Mode Network alteration patterns based on tau burden and amyloid status, highlighting patterns of morphological features with different susceptibility to proteinopathy. In individuals with concordant (both positive or both negative) amyloid and tau status, preserved structural integrity and complexity were linked to better cognitive performance and appeared protective against decline. However, mainly negative associations were instead observed in individuals with discordant amyloid or tau status (i.e. positive for only either amyloid or tau accumulation). We discuss these findings as a possible reflection of a mismatch between abnormal protein accumulation and structural damage in these populations. The multimodal nature of this study helps clarifying the heterogeneous findings reported in existing literature regarding structural integrity and cognitive outcomes in Alzheimer's disease.
阿尔茨海默病可根据淀粉样蛋白、tau蛋白和神经退行性变状态进行分类。默认模式网络对这些过程尤为敏感，使得该网络早期的结构改变对于识别前驱生物标志物具有特别的研究价值。在这项纵向横断面研究中，我们分析了来自阿尔茨海默病神经影像倡议组织的279名参与者的数据（平均年龄=73.7±9岁，男性占53.2%）。提取了默认模式网络所有区域的结构测量指标——脑沟深度、脑回化和皮质厚度。通过多元线性回归模型在基线和2年随访时测试了它们预测记忆表现（编码、检索和回忆）的能力，所有模型均对多重比较风险进行了校正。协变量包括简易精神状态检查表得分、淀粉样蛋白状态和区域tau蛋白负荷，以检验与结构变化的相互作用。我们的结果显示，基于tau蛋白负荷和淀粉样蛋白状态存在不同的默认模式网络改变模式，突出了形态学特征对蛋白病易感性不同的模式。在淀粉样蛋白和tau蛋白状态一致（均为阳性或均为阴性）的个体中，保留的结构完整性和复杂性与更好的认知表现相关，并且似乎对认知衰退具有保护作用。然而，在淀粉样蛋白或tau蛋白状态不一致（即仅淀粉样蛋白或tau蛋白积累为阳性）的个体中，主要观察到的是负相关。我们将这些发现讨论为这些人群中异常蛋白质积累与结构损伤之间不匹配的一种可能反映。本研究的多模态性质有助于阐明现有文献中关于阿尔茨海默病结构完整性和认知结果的异质性发现。
