Brain network dependent propagation of tau-pathology in Alzheimer disease

阿尔茨海默病中 tau 病理学的脑网络依赖性传播

• 批准号: 329109473
• 负责人: Professor Dr. Alexander Drzezga
• 金额: --
• 依托单位: Max-Planck-Institut für Stoffwechselforschung
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/329109473?language=en
• 关键词: Brain; network; dependent; propagation; tau

In Alzheimer disease, two major forms of protein aggregation, discussed as potential causal factors of disease, are the extracellular deposits of beta-amyloid (amyloid-plaques) and the intracellular aggregates of tau-protein (neurofibrillary tangles). In the past years, research on Alzheimer disease has been has been strongly focused on amyloid-pathology. However, more recently, tau-aggregation pathology is moving into the focus of attention, particularly as numerous clinical trials aiming to reduce amyloid-aggregation pathology have not shown ground-breaking success. It has been suggested that the extent of tau-deposition in the brain correlates more closely to the degree/progression of cognitive impairment as compared to amyloid. A key role of tau-pathology in the pathogenesis appears particularly plausible in the context of the so-called network degeneration hypothesis. The introduction of functional MRI (rsfMRI) resting state connectivity analysis today allows the identification of functional connectivity networks in the brain. The network degeneration hypothesis suggests that the expansion of neurodegeneration follows specific functional connectivity networks across the brain. Recent findings indicate that a prion-like mechanism may be involved in the spreading of tau-pathology. It has been shown that tau-aggregates appear to be capable of trans-synaptic spreading, i.e. to leak out of the synaptic terminal of one specific affected neuron, cross the synaptic cleft and potentially induce further aggregation of tau-proteins in the subsequent connected neuron. This finding would explain why neurodegenerative pathology may show an expansion pattern following functional connectivity pathways across the brain.Consequently, the investigation of deposition of tau-aggregates in vivo over time and its relation to other neurodegenerative pathologies and the functional networks of the brain is of major scientific interest and may aid significantly in the understanding of pathophysiological mechanisms involved in development of Alzheimer disease. Novel molecular imaging tracers for Positron Emission Tomography (PET) allowing to measure tau-aggregates in vivo may be ideally suited to serve this scientific purpose. Thus, in the current study, we will apply a multimodal imaging protocol including rsfMRI, amyloid-PET and tau-PET in subjects with Alzheimer disease and subjects at risk in a longitudinal approach, to address the following hypotheses:1. Tau-pathology expands along neuronal networks of the brain. 2. This expansion of tau pathology leads to progressive functional impairment of affected networks and consecutive network-specific cognitive decline.3. Using a mathematical model integrating baseline tau deposition, amyloid deposition and network architecture, the progression of tau pathology over time can be predicted in the individual patient.

在阿尔茨海默病中，蛋白质聚集的两种主要形式被认为是疾病的潜在致病因素，即β-淀粉样蛋白的细胞外沉积物（淀粉样斑块）和tau蛋白的细胞内聚集物（神经原纤维缠结）。在过去的几年中，对阿尔茨海默病的研究一直集中在淀粉样蛋白病理学上。然而，最近，tau 聚集病理学正成为人们关注的焦点，特别是因为旨在减少淀粉样蛋白聚集病理学的大量临床试验尚未取得突破性的成功。有人认为，与淀粉样蛋白相比，大脑中 tau 蛋白沉积的程度与认知障碍的程度/进展关系更密切。 在所谓的网络变性假说的背景下，tau 病理学在发病机制中的关键作用似乎特别合理。如今，功能性 MRI (rsfMRI) 静息态连接分析的引入可以识别大脑中的功能连接网络。网络退化假说表明，神经退化的扩展遵循大脑中特定的功能连接网络。最近的研究结果表明，类似朊病毒的机制可能与 tau 病理学的传播有关。研究表明，tau 蛋白聚集体似乎能够跨突触扩散，即从一个特定受影响神经元的突触末端漏出，穿过突触间隙，并可能诱导随后连接的神经元中 tau 蛋白的进一步聚集。这一发现可以解释为什么神经退行性病理学可能会沿着整个大脑的功能连接通路显示出扩展模式。因此，随着时间的推移体内 tau 聚集体的沉积及其与其他神经退行性病理学和大脑功能网络的关系的研究具有重要意义。重大科学兴趣，可能对理解阿尔茨海默病发展的病理生理机制有很大帮助。用于正电子发射断层扫描 (PET) 的新型分子成像示踪剂可以在体内测量 tau 聚集体，可能非常适合服务于这一科学目的。因此，在本研究中，我们将采用纵向方法对阿尔茨海默病受试者和高危受试者应用包括 rsfMRI、淀粉样蛋白 PET 和 tau-PET 在内的多模态成像方案，以解决以下假设：1。 Tau 蛋白病理学沿着大脑的神经元网络扩展。 2. tau 病理学的这种扩展导致受影响网络的进行性功能损伤和连续的网络特异性认知能力下降。3.使用整合基线 tau 沉积、淀粉样蛋白沉积和网络结构的数学模型，可以预测个体患者的 tau 病理随时间的进展。