School of Science & Technology, Nottingham Trent University, Nottingham, NG11 8NS, UK.
Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, RG6 6AS, UK.
Math Biosci. 2024 Nov;377:109289. doi: 10.1016/j.mbs.2024.109289. Epub 2024 Sep 5.
Macrophages are a type of white blood cell that play a significant role in determining the inflammatory response associated with a wide range of medical conditions. They are highly plastic, having the capacity to adopt numerous polarisation states or 'phenotypes' with disparate pro- or anti-inflammatory roles. Many previous studies divide macrophages into two categorisations: M1 macrophages are largely pro-inflammatory in nature, while M2 macrophages are largely restorative. However, there is a growing body of evidence that the M1 and M2 classifications represent the extremes of a much broader spectrum of phenotypes, and that intermediate phenotypes can play important roles in the progression or treatment of many medical conditions. In this article, we present a model of macrophage dynamics that includes a continuous description of phenotype, and hence incorporates intermediate phenotype configurations. We describe macrophage phenotype switching via nonlinear convective flux terms that scale with background levels of generic pro- and anti-inflammatory mediators. Through numerical simulation and bifurcation analysis, we unravel the model's resulting dynamics, paying close attention to the system's multistability and the extent to which key macrophage-mediator interactions provide bifurcations that act as switches between chronic states and restoration of health. We show that interactions that promote M1-like phenotypes generally result in a greater array of stable chronic states, while interactions that promote M2-like phenotypes can promote restoration of health. Additionally, our model admits oscillatory solutions reminiscent of relapsing-remitting conditions, with macrophages being largely polarised toward anti-inflammatory activity during remission, but with intermediate phenotypes playing a role in inflammatory flare-ups. We conclude by reflecting on our observations in the context of the ongoing pursuance of novel therapeutic interventions.
巨噬细胞是一种白细胞,在决定与广泛的医疗条件相关的炎症反应方面起着重要作用。它们具有高度的可塑性,能够采用多种极化状态或“表型”,具有不同的促炎或抗炎作用。许多先前的研究将巨噬细胞分为两类:M1 巨噬细胞在性质上主要是促炎的,而 M2 巨噬细胞主要是修复性的。然而,越来越多的证据表明,M1 和 M2 的分类代表了更广泛表型谱的极端情况,而中间表型在许多医疗条件的进展或治疗中可能发挥重要作用。在本文中,我们提出了一个包含表型连续描述的巨噬细胞动力学模型,因此包含了中间表型配置。我们通过与通用促炎和抗炎介质的背景水平成比例的非线性对流通量项来描述巨噬细胞表型转换。通过数值模拟和分岔分析,我们揭示了模型的动力学,密切关注系统的多稳定性以及关键巨噬细胞-介质相互作用提供分岔作为慢性状态和健康恢复之间的开关的程度。我们表明,促进 M1 样表型的相互作用通常会导致更多稳定的慢性状态,而促进 M2 样表型的相互作用可以促进健康的恢复。此外,我们的模型还允许类似于缓解-复发情况的振荡解,在缓解期间,巨噬细胞主要向抗炎活性极化,但中间表型在炎症发作中起作用。最后,我们根据正在进行的新型治疗干预的研究来反思我们的观察结果。