A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2.
A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2.
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一种用于比较主机内SARS-COV-2，MERS-COV和SARS-COV动力学的定量模型提供了有关SARS-COV-2的发病机理和治疗的见解。
DOI：
10.1371/journal.pbio.3001128
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发表时间：
2021-03
期刊：
影响因子：
9.8
通讯作者：
Iwami S
中科院分区：
文献类型：
--
作者：
Kim KS;Ejima K;Iwanami S;Fujita Y;Ohashi H;Koizumi Y;Asai Y;Nakaoka S;Watashi K;Aihara K;Thompson RN;Ke R;Perelson AS;Iwami S
科学界专注于开发抗病毒疗法，以减轻持续的2019新型冠状病毒病（COVID-19）爆发的影响。这将有助于提高对感染宿主内病毒动力学的理解。在这里，使用一个数学模型结合已发表的病毒载量数据，我们比较宿主内的病毒动态的SARS-CoV-2与类似的动态MERS-CoV和SARS-CoV。我们的定量分析使用的数学模型显示，在症状发作的SARS-CoV-2的宿主内繁殖数在统计学上显着大于MERS-CoV和类似的SARS-CoV。此外，SARS-CoV-2感染从症状发作到病毒载量峰值的时间比MERS-CoV和SARS-CoV短。这些发现表明抗病毒药物控制SARS-CoV-2感染的难度。我们进一步使用病毒动力学模型来预测具有不同作用模式的潜在抗病毒药物的疗效。通过病毒载量曲线下面积（AUC）的减少来测量疗效。我们的研究结果表明，阻断从头感染或病毒产生的治疗可能是有效的，当且仅当在病毒载量峰值（出现症状后2-3天）之前开始，但促进感染细胞的细胞毒性的治疗可能具有对治疗开始时间不太敏感的效果。此外，将促进细胞毒性的疗法与阻断从头感染或病毒产生的疗法组合协同降低早期治疗的AUC。我们独特的建模方法提供了深入了解SARS-CoV-2的发病机制，并可能有助于开发抗病毒治疗。
The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2–3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.
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