Identifying Associations between Brain Iron, Neurocognitive Networks and Protective Factors

确定脑铁，神经认知网络和 保护因素 阿尔茨海默病（AD）涉及病理水平的淀粉样蛋白β（Aβ）的积累 和磷酸化tau蛋白。然而，很大一部分患有AD病理学的个体 没有临床AD，表明其他因素的贡献。新的体内措施是 需要跟踪导致AD相关认知下降的其他因素。增加 有证据表明，与年龄相关的脑铁积累及其相关因素有助于 记忆力衰退的表现。我们最近的神经成像结果表明， 用体内定量磁化率图（QSM）测量脑铁浓度， 与大脑记忆网络的连接性差有关。该建议旨在确定 基于QSM的铁浓度与神经认知变化之间的相关性 改善AD生物标志物的目标。我们还将定义QSM基铁之间的相互作用 信号，AD病理学，认知下降的炎症标志物。最后，我们将测试 富含抗氧化剂的饮食可能会减缓大脑铁的积累。我们 建议使用包括fMRI在内的神经成像方法研究140名健康老年人， QSM，CSF和血浆Aβ、p-tau和t-tau以及炎症标志物的测量。 其他结构性神经成像测量将包括区域体积、FLAIR成像 用于量化WMH体积，扩散张量成像用于量化 区域性分布的白色物质连通性。一部分参与者将完成 大约3年后的CSF和成像测量结果相同。我们的目标是确定（1）影响 基于QSM的铁信号对支持认知的功能和结构脑网络的影响; (2)脑铁、炎症标志物、AD病理学和认知之间的关联 （3）脑铁的修饰剂或其对认知的影响。我们将测试假设 基于QSM的脑铁含量高与记忆回路的连通性低有关， 与AD病理学无关，但可能随时间推移与AD协同相互作用。我们 还将测试假设，储备因素将抵消脑铁的影响， 认知功能通过大脑维护机制或可塑性功能大脑 一些老年人大规模大脑功能网络的重组。

Identifying Associations between Brain Iron, Neurocognitive Networks and Protective Factors Alzheimer’s disease (AD) involves accumulation of pathological levels of amyloid-beta (Aβ) and phospho-tau proteins. However, a significant proportion of individuals with AD pathology do not have clinical AD, indicating contributions of other factors. Novel in-vivo measures are required to track other factors contributing to AD-related cognitive declines. Increasing evidence suggests that age-related accumulation of brain iron and its correlates contribute to the manifestation of memory declines. Our recent neuroimaging results suggest that high brain iron concentration, measured with in vivo quantitative susceptibility mapping (QSM), is associated poor connectivity within brain memory networks. This proposal seeks to identify associations between QSM-based iron concentration and neurocognitive changes toward a goal of improving AD biomarkers. We will also define the interplay between QSM-based iron signal, AD pathology, inflammatory markers on cognitive declines. Finally, we will test the possibility that brain iron accumulation may be slowed by an antioxidant rich diet. We propose to study 140 healthy older adults using neuroimaging measures including fMRI and QSM, measures of CSF and plasma Aβ, p-tau and t-tau and inflammatory markers. Additional structural neuroimaging measures will include regional volumes, FLAIR imaging for quantification of WMH volumes and diffusion tensor imaging for quantification of regionally distributed white matter connectivity. A subset of participants will be complete the same CSF and imaging measures approximately 3 years later. We aim to identify (1) effects of QSM-based iron signal on functional and structural brain networks supporting cognition; (2) associations between brain iron, inflammatory markers, AD pathology and cognitive declines and; (3) modifiers of brain iron or its effects on cognition. We will test hypotheses that high QSM-based brain iron is associated with low connectivity in memory circuits independently of AD pathology but may and synergistically interacts with AD over time. We will also test the hypothesis that reserve factors will offset the effects of brain iron on cognitive functions via mechanisms of brain maintenance or plastic functional brain reorganization of large-scale brain functional networks in some older adults.