Multiscale Modeling of Aortic Homeostasis

主动脉稳态的多尺度建模

• 批准号: 10471254
• 负责人: Jay D. Humphrey
• 金额: $ 8.38万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-19 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10471254
• 关键词: Aging; American; Angiotensin II; Aorta; Arteries; Biological; Biology; Biomechanics; Blood Pressure; Blood Vessels; Blood flow; Body Temperature; Caliber; Cardiac; Cardiovascular Diseases; Cardiovascular system; Cell physiology; Chronic; Collagen; Complication; Computer Models; Computing Methodologies; Country; DNA Sequence Alteration; Data; Data Set; Databases; Disease; Dissection; Elastin; Endothelial Cells; Endothelium; Ensure; Environment; Equilibrium; Failure; Feedback; Female; Fibroblasts; Funding; Future; Genes; Goals; Grant; Growth; Histology; Homeostasis; Hypertension; Inflammation; Infusion procedures; Intercellular Fluid; Intervention; Lung; Masks; Mathematics; Mechanics; Medial; Medicine; Methods; Modeling; Molecular; Morbidity - disease rate; Mus; Oncology; Ophthalmology; Organ; Pathologic; Phenotype; Process; Reproducibility; Research; Research Methodology; Research Project Grants; Risk Factors; Rupture; Signal Transduction; Smooth Muscle; Smooth Muscle Myocytes; Talents; Testing; Therapeutic Intervention; Thick; Thinness; Time; Tissue-Specific Gene Expression; Tissues; Training Support; Vascular Diseases; Work; biological systems; burden of illness; cell type; clinically significant; computer framework; design; differential expression; hypertensive; innovation; insight; kidney vascular structure; mechanical load; mechanical stimulus; monolayer; mortality; mouse model; multi-scale modeling; multiscale data; neurovascular; novel; preservation; prevent; research and development; respiratory smooth muscle; response; secondary analysis; small molecule; soft tissue; theories; transcriptome sequencing

PROJECT SUMMARY. Mechanical homeostasis is a process by which the vasculature adapts to changes in blood flow, blood pressure, and other influences. Mounting evidence suggests that compromised or lost homeostasis is a cause or consequence of many vascular diseases. There is, therefore, a pressing need for an increased understanding of vascular homeostasis, which necessarily derives from molecular and cellular processes but manifests at the tissue level via negative feedback that can be described mathematically. The goal of this project is to use an existing extensive data set on aortic remodeling in a unique mouse model of hypertension to inform and validate a new multiscale model of vascular homeostasis. Once achieved, such a model promises to help delineate compensatory mechanisms that promote tissue homeostasis via changes in cell signaling versus pathologic mechanisms that prevent homeostasis. Toward this end, we will meld recent advances in cell signaling models and continuum level growth and remodeling models to describe and predict data from a unique mouse model of hypertension wherein aortic remodeling is adaptive because of a preserved contractile phenotype and augmented synthetic phenotype, with inherently low inflammation. In this way we will avoid the typical complication of inflammation that is present in other mouse models of hypertension and drives the response away from homeostasis. We will inform our mechanobiologically motivated multiscale model using a combination of data from RNA sequencing, quantitative histology, and biaxial biomechanical (passive and active) data. Importantly, this data-informed model will enable us to explore, for the first time, the potentially adaptive versus maladaptive changes in cell signaling topology that promote or prevent effective homeostasis, thus representing a paradigm shift in the way some vascular diseases are understood and how best to treat them. Hypertension, for example, is rampant in this country and is a key risk factor for diverse cardiovascular, neurovascular, and renovascular diseases. This work is significant biologically for it has potential to provide new insight into this insidious risk factor. More generally, however, tissue homeostasis is fundamental to many different tissues and organs and our general computational approach promises to be generally applicable. Finally, this work is highly innovative for it will identify a new computational framework for integrating information across scales from differentially expressed genes to tissue-level manifestations, and it will enable delineation of potentially homeostatic versus non-homeostatic responses to diverse genetic mutations or small molecule interventions, which can guide therapeutic intervention. This proposal is submitted via the R03 mechanism since its focus is “Development of research methodology” and “Secondary analysis of existing data”, specifically, a unique multiscale data set obtained from a fortuitously discovered mouse model. It will also support the training of a promising young female biomathematician as she transitions to vascular research.

项目摘要。机械稳态是脉管系统适应变化的过程 血流、血压和其他影响。越来越多的证据表明，受到损害或丢失 体内平衡是许多血管疾病的原因或结果。因此，迫切需要一个 增加对血管稳态的了解，这必然源自分子和细胞 过程，但通过可以数学描述的负反馈在组织水平上表现出来。 该项目的目标是在独特的小鼠模型中使用现有的有关主动脉重塑的广泛数据集 高血压以告知和验证血管稳态的新多尺度模型。一旦实现，这样的 该模型有望帮助描绘通过改变来促进组织稳态的补偿机制 细胞信号传导与阻止体内平衡的病理机制。为此，我们将融合最近 细胞信号传导模型以及描述和预测的连续水平生长和重塑模型的进展 来自独特的高血压小鼠模型的数据，其中主动脉重塑是适应性的，因为保留了 收缩表型和增强的合成表型，具有固有的低炎症。这样我们就会 避免其他高血压和驱动力小鼠模型中存在的典型炎症并发症 远离稳态的反应。我们将使用以下方法来告知我们的机械生物学驱动的多尺度模型 来自 RNA 测序、定量组织学和双轴生物力学（被动和 活动）数据。重要的是，这种基于数据的模型将使我们能够首次探索潜在的 细胞信号拓扑中促进或阻止有效稳态的适应性与适应不良变化， 因此代表了理解某些血管疾病以及如何最好治疗的方式的范式转变 他们。例如，高血压在这个国家很猖獗，是多种心血管疾病的关键危险因素， 神经血管和肾血管疾病。这项工作具有重要的生物学意义，因为它有可能提供新的 insight into this insidious risk factor.然而，更一般地说，组织稳态对于许多人来说是基础 不同的组织和器官，我们的通用计算方法有望普遍适用。 最后，这项工作具有高度创新性，因为它将确定一个用于整合信息的新计算框架 从差异表达基因到组织水平表现的各个尺度，它将能够描述 对不同基因突变或小分子的潜在稳态反应与非稳态反应 干预措施，可以指导治疗干预。该提案是通过 R03 机制提交的 其重点是“研究方法的发展”和“现有数据的二次分析”，具体来说， 从偶然发现的小鼠模型获得的独特的多尺度数据集。还将支持培训 一位有前途的年轻女性生物数学家转向血管研究的故事。