Bifurcations in coupled amyloid-β aggregation-inflammation systems.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2024-07-30 DOI:10.1038/s41540-024-00408-7
Kalyan S Chakrabarti, Davood Bakhtiari, Nasrollah Rezaei-Ghaleh
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Abstract

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.

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淀粉样蛋白-β聚集-炎症耦合系统中的分岔。
阿尔茨海默病(AD)的神经病理学及其进展过程是由各种过程之间复杂的相互作用造成的。多种证据表明,在阿尔茨海默病的漫长前驱期,Aβ聚集与神经炎症之间存在耦合关系,并在维持大脑稳态方面发挥作用。然而,人们对这一保护机制是如何失效并因此不可逆转地逐渐过渡到临床 AD 的却知之甚少。在此,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了数值模拟,并分析了其分岔特性。引入的模型表示了以下事件:Aβ 单体的产生、Aβ 单体聚集成低聚物和纤维、Aβ 聚集物诱发炎症以及各种 Aβ 物种的清除。最重要的是,Aβ 的生成和清除率受炎症水平的调节,并遵循希尔型反应函数。尽管该模型相对简单,但却表现出从过阻尼动力学到持续振荡的丰富动态。然后,我们明确了向振荡动力学过渡的炎症和耦合相关参数空间区域,并演示了 Aβ 聚集参数的变化如何改变参数空间中的振荡区域。我们的研究结果揭示了 Aβ 聚集-炎症耦合系统的振荡动力学倾向,并提出了长时间的持续振荡和随之而来的免疫系统衰竭是向 AD 淀粉样病理学更进展阶段过渡的潜在机制。本文还讨论了我们的研究结果对早期诊断 AD 和开发抗 AD 药物的意义。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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