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一种基于宿主免疫的多房室数学模型,用于剖析新冠病毒疾病的异质性。

A multicompartment mathematical model based on host immunity for dissecting COVID-19 heterogeneity.

作者信息

Li Jianwei, Wu Jianghua, Zhang Jingpeng, Tang Lu, Mei Heng, Hu Yu, Li Fangting

机构信息

School of Physics, Center for Quantitative Biology, Peking University, Beijing 100871, China.

Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.

出版信息

Heliyon. 2022 May;8(5):e09488. doi: 10.1016/j.heliyon.2022.e09488. Epub 2022 May 18.

Abstract

The determinants underlying the heterogeneity of coronavirus disease 2019 (COVID-19) remain to be elucidated. To systemically analyze the immunopathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, we built a multicompartment mathematical model based on immunological principles and typical COVID-19-related characteristics. This model integrated the trafficking of immune cells and cytokines among the secondary lymphoid organs, peripheral blood and lungs. Our results suggested that early-stage lymphopenia was related to lymphocyte chemotaxis, while prolonged lymphopenia in critically ill patients was associated with myeloid-derived suppressor cells. Furthermore, our model predicted that insufficient SARS-CoV-2-specific naïve T/B cell pools and ineffective activation of antigen-presenting cells (APCs) would cause delayed immunity activation, resulting in elevated viral load, low immunoglobulin level, etc. Overall, we provided a comprehensive view of the dynamics of host immunity after SARS-CoV-2 infection that enabled us to understand COVID-19 heterogeneity from systemic perspective.

摘要

2019冠状病毒病(COVID-19)异质性背后的决定因素仍有待阐明。为了系统分析严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染的免疫发病机制,我们基于免疫学原理和典型的COVID-19相关特征构建了一个多房室数学模型。该模型整合了免疫细胞和细胞因子在二级淋巴器官、外周血和肺之间的运输。我们的结果表明,早期淋巴细胞减少与淋巴细胞趋化性有关,而危重症患者的持续性淋巴细胞减少与髓系来源的抑制细胞有关。此外,我们的模型预测,SARS-CoV-2特异性初始T/B细胞库不足和抗原呈递细胞(APC)的无效激活会导致免疫激活延迟,从而导致病毒载量升高、免疫球蛋白水平降低等。总体而言,我们提供了SARS-CoV-2感染后宿主免疫动力学的全面视图,使我们能够从系统角度理解COVID-19的异质性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6af/9124712/83b1af797f5b/gr1.jpg

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