Brain aging is a complex process involving many functions of our body and described by the interplay of a sleep pattern and changes in the metabolic waste concentration regulated by the microglial function and the glymphatic system. We review the existing modelling approaches to this topic and derive a novel mathematical model to describe the crosstalk between these components within the conceptual framework of inflammaging. Analysis of the model gives insight into the dynamics of garbage concentration and linked microglial senescence process resulting from a normal or disrupted sleep pattern, hence, explaining an underlying mechanism behind healthy or unhealthy brain aging. The model incorporates accumulation and elimination of garbage, induction of glial activation by garbage, and glial senescence by over-activation, as well as the production of pro-inflammatory molecules by their senescence-associated secretory phenotype (SASP). Assuming that insufficient sleep leads to the increase of garbage concentration and promotes senescence, the model predicts that if the accumulation of senescent glia overcomes an inflammaging threshold, further progression of senescence becomes unstoppable even if a normal sleep pattern is restored. Inverting this process by “rejuvenating the brain” is only possible via a reset of concentration of senescent glia below this threshold. Our model approach enables analysis of space-time dynamics of senescence, and in this way, we show that heterogeneous patterns of inflammation will accelerate the propagation of senescence profile through a network, confirming a negative effect of heterogeneity.

大脑衰老是一个复杂的过程，涉及我们身体的许多功能，可以通过睡眠模式与小胶质细胞功能和类淋巴系统调节的代谢废物浓度变化之间的相互作用来描述。我们回顾了该主题的现有建模方法，并推导了一种新颖的数学模型来描述炎症概念框架内这些组件之间的串扰。该模型的分析可以深入了解垃圾浓度的动态以及由正常或中断的睡眠模式引起的相关小胶质细胞衰老过程，从而解释健康或不健康的大脑衰老背后的潜在机制。该模型结合了垃圾的积累和消除、垃圾诱导神经胶质细胞活化、过度激活导致的神经胶质细胞衰老，以及通过衰老相关分泌表型（SASP）产生促炎分子。假设睡眠不足导致垃圾浓度增加并促进衰老，该模型预测，如果衰老胶质细胞的积累超过炎症阈值，即使恢复正常睡眠模式，衰老的进一步进展也将不可阻挡。只有通过将衰老神经胶质细胞的浓度重置到该阈值以下，才能通过“使大脑恢复活力”来逆转这一过程。我们的模型方法能够分析衰老的时空动态，通过这种方式，我们表明炎症的异质模式将加速衰老特征通过网络的传播，证实了异质性的负面影响。