RUI: Mathematical Modeling of Immune Response to SARS-CoV-2

RUI：SARS-CoV-2 免疫反应的数学模型

• 批准号: 2151990
• 负责人: Hwayeon Ryu
• 金额: $ 30万
• 依托单位: Elon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2151990&HistoricalAwards=false
• 关键词: RUI; Mathematical; Modeling; Immune; Response

This research investigates the human immune response to SARS-CoV-2 virus to elucidate the key mechanisms responsible for disease severity exhibited by some COVID-19 patients. Despite a significant volume of clinical and experimental studies for the detailed mechanisms of SARS-CoV-2 virus, there is a lack of understanding about the host immune response to the virus, which is largely responsible for the variability in disease severity. To accelerate and supplement our understanding of key target pathways in the immune response, this project will develop and analyze a fundamental, comprehensive model for the host immune dynamics of SARS-CoV-2. Given we continue as a nation under pandemic conditions with new variants emerging and vaccination rollouts, the theoretical explorations through mathematical modeling will serve as a complement to lab-based and data-based approaches. Other features of this work include student involvement in this research, development of a network of collaborators across three institutions, curricula development, recruitment of students from underrepresented groups, and efforts to bring a broad community of researchers studying the host immune dynamics of COVID-19 together to advance our understanding of the interactions between the immune system and SARS-CoV-2. This project aims to accomplish two specific research goals: (i) development of a mathematical model of the host immune dynamics of COVID-19; and (ii) exploration of the model to address important COVID-19 treatment-related questions. For the first goal, the PI will develop and analyze a mathematical model that explicitly represents the virus, immune cells, cytokines, and their interactions, formulated in a system of coupled ordinary and delay differential equations. The main objective is to obtain a better understanding of key aspects of immune response to SARS-CoV-2, specifically its sensitive pathways. For the second goal, the PI will investigate the importance of timing of specific immune responses in disease severity and divergent outcomes, and the emergence of the so-called cytokine storm, excessive production of proinflammatory cytokines in the immune system. The aim is to identify the key mechanisms responsible for disease severity, which could help to identify other pathways to target therapeutically. The primary tools to be used for this project are model parameterization using a series of clinical and experimental data, sensitivity analysis, and numerical simulations. The primary mathematical contribution is the development of computational techniques to analyze high-dimensional nonlinear dynamical systems. In addition, the results from this study on the mechanisms involved in COVID-19 pathology and identification of several therapeutic targets would provide hypotheses to be clinically tested, thus, serving as a foundation for the development of evidence-based treatment protocols to address the global challenge.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项研究调查了人类对SARS-CoV-2病毒的免疫反应，以阐明一些COVID-19患者表现出的疾病严重程度的关键机制。尽管对SARS-CoV-2病毒的详细机制进行了大量的临床和实验研究，但对宿主对病毒的免疫反应缺乏了解，这在很大程度上是疾病严重程度的可变性的原因。为了加速和补充我们对免疫反应中关键靶向通路的理解，该项目将开发和分析SARS-CoV-2宿主免疫动力学的基本综合模型。鉴于我们继续作为一个国家在大流行的条件下，新的变种出现和疫苗接种的推出，通过数学建模的理论探索将作为基于实验室和基于数据的方法的补充。这项工作的其他特点包括学生参与这项研究，在三个机构之间建立合作者网络，课程开发，从代表性不足的群体中招募学生，以及努力将研究COVID-19宿主免疫动力学的广泛研究人员聚集在一起，以促进我们对免疫系统和SARS-CoV-2之间相互作用的理解。 该项目旨在实现两个具体的研究目标：（i）开发COVID-19宿主免疫动力学的数学模型;以及（ii）探索该模型以解决重要的COVID-19治疗相关问题。对于第一个目标，PI将开发和分析一个数学模型，该模型明确表示病毒，免疫细胞，细胞因子及其相互作用，并在耦合的常微分方程和延迟微分方程系统中制定。主要目的是更好地了解SARS-CoV-2免疫反应的关键方面，特别是其敏感途径。对于第二个目标，PI将研究疾病严重程度和不同结局中特异性免疫应答时机的重要性，以及所谓的细胞因子风暴的出现，即免疫系统中促炎细胞因子的过度产生。其目的是确定导致疾病严重程度的关键机制，这可能有助于确定其他治疗靶向途径。该项目使用的主要工具是使用一系列临床和实验数据的模型参数化，敏感性分析和数值模拟。主要的数学贡献是发展了计算技术来分析高维非线性动力系统。此外，这项关于COVID-19病理学机制和几个治疗靶点的鉴定的研究结果将提供有待临床检验的假设，因此，作为证据发展的基础-该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准。