Department of Biological Science and Chemistry, Krea University, Sri City, India.
Stadtapotheke Calw Pharmacy, Calw, Germany.
NPJ Syst Biol Appl. 2024 Jul 30;10(1):80. doi: 10.1038/s41540-024-00408-7.
A complex interplay between various processes underlies the neuropathology of Alzheimer's disease (AD) and its progressive course. Several lines of evidence point to the coupling between Aβ aggregation and neuroinflammation and its role in maintaining brain homeostasis during the long prodromal phase of AD. Little is however known about how this protective mechanism fails and as a result, an irreversible and progressive transition to clinical AD occurs. Here, we introduce a minimal model of a coupled system of Aβ aggregation and inflammation, numerically simulate its dynamical behavior, and analyze its bifurcation properties. The introduced model represents the following events: generation of Aβ monomers, aggregation of Aβ monomers into oligomers and fibrils, induction of inflammation by Aβ aggregates, and clearance of various Aβ species. Crucially, the rates of Aβ generation and clearance are modulated by inflammation level following a Hill-type response function. Despite its relative simplicity, the model exhibits enormously rich dynamics ranging from overdamped kinetics to sustained oscillations. We then specify the region of inflammation- and coupling-related parameters space where a transition to oscillatory dynamics occurs and demonstrate how changes in Aβ aggregation parameters could shift this oscillatory region in parameter space. Our results reveal the propensity of coupled Aβ aggregation-inflammation systems to oscillatory dynamics and propose prolonged sustained oscillations and their consequent immune system exhaustion as a potential mechanism underlying the transition to a more progressive phase of amyloid pathology in AD. The implications of our results in regard to early diagnosis of AD and anti-AD drug development are discussed.
阿尔茨海默病(AD)的神经病理学及其进行性过程是多种过程复杂相互作用的结果。有几条证据表明 Aβ 聚集和神经炎症之间的耦合及其在 AD 长前驱期维持大脑内稳态的作用。然而,人们对这种保护机制如何失效知之甚少,因此会发生不可逆转和进行性的向临床 AD 的转变。在这里,我们引入了一个 Aβ 聚集和炎症耦合系统的最小模型,对其动力学行为进行数值模拟,并分析其分岔特性。所提出的模型代表了以下事件:Aβ 单体的产生、Aβ 单体聚集为寡聚物和原纤维、Aβ 聚集物诱导炎症以及各种 Aβ 物种的清除。至关重要的是,Aβ 产生和清除的速率根据 Hill 型响应函数被炎症水平调节。尽管该模型相对简单,但它表现出极其丰富的动力学,从过阻尼动力学到持续振荡。然后,我们指定了与炎症和耦合相关的参数空间区域,其中会发生向振荡动力学的转变,并演示了 Aβ 聚集参数的变化如何改变参数空间中的这个振荡区域。我们的结果揭示了耦合 Aβ 聚集-炎症系统向振荡动力学的倾向,并提出了延长的持续振荡及其随后的免疫系统衰竭,作为 AD 中淀粉样蛋白病理向更进行性阶段转变的潜在机制。讨论了我们的结果对 AD 的早期诊断和抗 AD 药物开发的影响。