School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK.
Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK.
J R Soc Interface. 2021 Feb;18(175):20200950. doi: 10.1098/rsif.2020.0950. Epub 2021 Feb 17.
While the pathological mechanisms in COVID-19 illness are still poorly understood, it is increasingly clear that high levels of pro-inflammatory mediators play a major role in clinical deterioration in patients with severe disease. Current evidence points to a hyperinflammatory state as the driver of respiratory compromise in severe COVID-19 disease, with a clinical trajectory resembling acute respiratory distress syndrome, but how this 'runaway train' inflammatory response emerges and is maintained is not known. Here, we present the first mathematical model of lung hyperinflammation due to SARS-CoV-2 infection. This model is based on a network of purported mechanistic and physiological pathways linking together five distinct biochemical species involved in the inflammatory response. Simulations of our model give rise to distinct qualitative classes of COVID-19 patients: (i) individuals who naturally clear the virus, (ii) asymptomatic carriers and (iii-v) individuals who develop a case of mild, moderate, or severe illness. These findings, supported by a comprehensive sensitivity analysis, point to potential therapeutic interventions to prevent the emergence of hyperinflammation. Specifically, we suggest that early intervention with a locally acting anti-inflammatory agent (such as inhaled corticosteroids) may effectively blockade the pathological hyperinflammatory reaction as it emerges.
虽然 COVID-19 疾病的病理机制仍未完全了解,但越来越明显的是,高水平的促炎介质在重症患者临床恶化中起主要作用。目前的证据表明,过度炎症状态是导致严重 COVID-19 疾病呼吸功能障碍的驱动因素,其临床过程类似于急性呼吸窘迫综合征,但这种“失控列车”炎症反应是如何出现并维持的尚不清楚。在这里,我们提出了第一个由于 SARS-CoV-2 感染导致肺部炎症过度的数学模型。该模型基于一个假定的机制和生理途径网络,将五个不同的与炎症反应相关的生化物质联系在一起。我们模型的模拟产生了不同的 COVID-19 患者定性类别:(i)自然清除病毒的个体,(ii)无症状携带者和(iii-v)患有轻度、中度或重度疾病的个体。这些发现得到了全面的敏感性分析的支持,为预防炎症过度产生提供了潜在的治疗干预措施。具体而言,我们建议早期使用局部作用的抗炎药物(如吸入性皮质类固醇)进行干预,可能会有效阻断病理性炎症过度反应的出现。