The disease caused by SARS-CoV-2 is a global pandemic that threatens to bring long-term changes worldwide. Approximately 80% of infected patients are asymptomatic or have mild symptoms such as fever or cough, while rest of the patients have varying degrees of severity of symptoms, with 3-4% mortality rate. Severe symptoms such as pneumonia and Acute Respiratory Distress Syndrome can be caused by tissue damage mostly due to aggravated and unresolved innate and adaptive immune response, often resulting from a cytokine storm. However, the mechanistic underpinnings of such responses remain elusive, with an incomplete understanding of how an intricate interplay among infected cells and cells of innate and adaptive immune system can lead to such diverse clinicopathological outcomes. Here, we use a dynamical systems approach to dissect the emergent nonlinear intra-host dynamics among virally infected cells, the immune response to it and the consequent immunopathology. By mechanistic analysis of cell-cell interactions, we have identified key parameters affecting the diverse clinical phenotypes associated with COVID-19. This minimalistic yet rigorous model can explain the various phenotypes observed across the clinical spectrum of COVID-19, various co-morbidity risk factors such as age and obesity, and the effect of antiviral drugs on different phenotypes. It also reveals how a fine-tuned balance of infected cell killing and resolution of inflammation can lead to infection clearance, while disruptions can drive different severe phenotypes. These results will help further the case of rational selection of drug combinations that can effectively balance viral clearance and minimize tissue damage simultaneously.

中文翻译：

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SARS-CoV-2与免疫系统相互作用的机理模型揭示了各种临床病理结果的设计原则

由SARS-CoV-2引起的疾病是全球性大流行，有可能在世界范围内带来长期变化。大约80％的感染患者无症状或有轻微症状，例如发烧或咳嗽，而其余患者的症状严重程度不同，死亡率为3-4％。严重的症状，例如肺炎和急性呼吸窘迫综合症，可能是由组织损伤引起的，这主要是由于细胞因子风暴导致的先天性和适应性免疫应答的加重和未解决而引起的。但是，这种反应的机制基础仍然难以捉摸，对感染细胞与先天性和适应性免疫系统细胞之间复杂的相互作用如何导致这种多样的临床病理结果尚不完全了解。这里，我们使用动力学系统方法来剖析病毒感染细胞之间出现的非线性宿主内部动力学，对它的免疫反应以及随之而来的免疫病理学。通过细胞间相互作用的机理分析，我们确定了影响与COVID-19相关的多种临床表型的关键参数。这种简约而严谨的模型可以解释在整个COVID-19临床范围内观察到的各种表型，各种合并症危险因素（例如年龄和肥胖）以及抗病毒药物对不同表型的影响。它还揭示了感染细胞杀伤和炎症消退的微妙平衡如何可以导致感染清除，而破坏则可以驱动不同的严重表型。