Bitra Veera Raghavulu, Challa Siva Reddy, Adiukwu Paul C, Rapaka Deepthi
School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana.
Department of Cancer Biology and Pharmacology, University of Illinois College of Medicine, Peoria, IL 61614, USA; KVSR Siddartha College of Pharmaceutical Sciences, Vijayawada, Andhra Pradesh, India.
Brain Res Bull. 2023 Oct 15;203:110777. doi: 10.1016/j.brainresbull.2023.110777. Epub 2023 Oct 7.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an impairment of cognition and memory. Current research on connectomics have now related changes in the network organization in AD to the patterns of accumulation and spread of amyloid and tau, providing insights into the neurobiological mechanisms of the disease. In addition, network analysis and modeling focus on particular use of graphs to provide intuition into key organizational principles of brain structure, that stipulate how neural activity propagates along structural connections. The utility of connectome-based computational models aids in early predicting, tracking the progression of biomarker-directed AD neuropathology. In this article, we present a short review of tau trajectory, the connectome changes in tau pathology, and the dependent recent connectome-based computational modelling approaches for tau spreading, reproducing pragmatic findings, and developing significant novel tau targeted therapies.
阿尔茨海默病(AD)是一种进行性神经退行性疾病,伴有认知和记忆障碍。目前关于连接组学的研究已将AD中网络组织的变化与淀粉样蛋白和tau蛋白的积累及传播模式联系起来,为该疾病的神经生物学机制提供了见解。此外,网络分析和建模专注于特定的图的应用,以直观呈现脑结构的关键组织原则,这些原则规定了神经活动如何沿结构连接传播。基于连接组的计算模型的效用有助于早期预测、追踪生物标志物导向的AD神经病理学进展。在本文中,我们简要综述了tau蛋白轨迹、tau蛋白病理学中的连接组变化,以及最近基于连接组的计算建模方法,这些方法用于tau蛋白传播、再现实际发现以及开发重要的新型tau蛋白靶向疗法。