Multiscale modeling of inherited cardiomyopathies and therapeutic interventions

遗传性心肌病的多尺度建模和治疗干预

• 批准号: 10448074
• 负责人: Kenneth S Campbell
• 金额: $ 0.34万
• 依托单位: UNIVERSITY OF KENTUCKY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-03 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10448074
• 关键词: Acute; Affect; Algorithms; American; Biological Assay; Biology; Cardiac; Cardiac Death; Cardiomyopathies; Cardiovascular Diseases; Cells; Chronic; Computer Models; Computer Simulation; Computer software; Coupled; DNA Sequence Alteration; Data; Data Analyses; Development; Drug usage; Elements; Engineering; Fiber; Future; Genetic; Geometry; Goals; Growth; Heart; Heart Abnormalities; Heart Diseases; Heart Hypertrophy; Heart failure; Histology; Hypertrophy; Inherited; Intervention; Kinetics; Laws; Magnetic Resonance Imaging; Mathematics; Measurement; Measures; Modeling; Molecular; Motor; Mutation; Myocardial; Myosin ATPase; Myosin Regulatory Light Chains; Organ; Patients; Pattern; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacotherapy; Proteins; Records; Research; Research Personnel; Sarcomeres; Scientist; Structure; Techniques; Testing; Therapeutic Intervention; Time; Tissues; Transgenic Animals; Transgenic Mice; Treatment Failure; Validation; Ventricular; Ventricular Remodeling; Wild Type Mouse; Work; cell motility; drug testing; experience; experimental study; genetic regulatory protein; heart function; improved; in silico; inherited cardiomyopathy; innovation; interest; kinetic model; mathematical model; model development; molecular scale; multi-scale modeling; novel therapeutics; personalized medicine; predictive modeling; response; simulation; skills; software development; treatment optimization; treatment planning

ABSTRACT The goal of this research is to develop a predictive multiscale model that will improve understanding of familial cardiomyopathies and that can be used to help screen potential new therapies for cardiac disease. Familial cardiomyopathies are the most frequently inherited heart defect and affect about 700,000 Americans. Most of the genetic mutations affect myosin or regulatory proteins that modulate myosin function. The majority of these mutations also induce abnormal cardiac growth termed hypertrophy. This project will develop, calibrate, and validate an innovative multiscale model that uses data quantifying myosin-level function to predict how hearts hypertrophy over time. This is a critical step on the path to developing patient-specific computer models that can be used to optimize treatments for heart failure and to predict the effects of different types of pharmaceutical intervention. In the future, one could envision clinicians testing drug treatments in silico and selecting the intervention that produces the greatest long-term benefit for their patient. The research team consists of two physiologists/biophysicists (Campbell & Yengo) and two engineers (Wenk & Lee) who share a common interest in cardiac biology. Together, their research skills span from structure-function analysis of myosin molecules to computer simulations of hearts that grow and remodel over time. The research plan integrates state-of-the-art hierarchically-coupled mathematical models with validation experiments that range from stopped-flow molecular kinetic assays to magnetic resonance imaging of myocardial strain patterns. The model will be tested using molecular to organ-level experimental data obtained from wild-type mice and from transgenic animals that develop cardiac hypertrophy because of a K104E mutation in myosin regulatory light chain. Additional tests will be performed using drugs that enhance (omecamtiv mecarbil) and inhibit (MYK-461) myosin-level contractile function. There are three specific aims. Aim 1: Integrate a multistate kinetic model of myosin into an organ-level finite framework to predict the effects of genetic and/or pharmaceutical modulation of myosin function. Aim 2: Develop growth and remodeling algorithms to predict chronic changes in ventricular structure and function resulting from genetic and/or pharmaceutical modulation of myosin function. Aim 3: Calibrate and validate the model using experimental data quantifying different spatial and temporal scales.

抽象的 这项研究的目标是开发一个预测性多尺度模型，以增进对家庭的理解 心肌病，可用于帮助筛选潜在的心脏病新疗法。家族式 心肌病是最常见的遗传性心脏缺陷，影响约 70 万美国人。大部分 基因突变影响肌球蛋白或调节肌球蛋白功能的调节蛋白。其中大多数 突变还会引起心脏异常生长，称为肥大。该项目将开发、校准和 验证一种创新的多尺度模型，该模型使用量化肌球蛋白水平功能的数据来预测心脏如何 随着时间的推移肥大。这是开发患者特定计算机模型的关键一步，该模型可以 用于优化心力衰竭的治疗并预测不同类型药物的效果 干涉。未来，人们可以设想临床医生在计算机上测试药物治疗并选择 为患者带来最大长期利益的干预措施。 研究团队由两名生理学家/生物物理学家（Campbell & Yengo）和两名工程师（Wenk & Lee），他们对心脏生物学有着共同的兴趣。他们的研究技能涵盖从结构到功能 从肌球蛋白分子分析到心脏随时间生长和重塑的计算机模拟。研究 计划将最先进的分层耦合数学模型与验证实验相结合 范围从停流分子动力学测定到心肌应变模式的磁共振成像。 该模型将使用从野生型小鼠和从小鼠获得的分子到器官水平的实验数据进行测试 由于肌球蛋白调节光中的 K104E 突变而导致心脏肥大的转基因动物 链。将使用增强 (omecamtiv mecarbil) 和抑制 (MYK-461) 的药物进行其他测试 肌球蛋白水平的收缩功能。 具体目标有三个。 目标 1：将肌球蛋白的多态动力学模型整合到器官级有限框架中，以预测肌球蛋白的影响 肌球蛋白功能的遗传和/或药物调节。 目标 2：开发生长和重塑算法来预测心室结构和功能的慢性变化 由肌球蛋白功能的遗传和/或药物调节引起。 目标 3：使用量化不同空间和时间尺度的实验数据来校准和验证模型。

项目成果

The effects of pH and Pi on tension and Ca2+ sensitivity of ventricular myofilaments from the anoxia-tolerant painted turtle.

pH和Pi对耐缺氧锦龟心室肌丝张力和Ca2+敏感性的影响。

• 发表时间: 2017-11-15
• 作者: Fanter, Cornelia E;Campbell, Kenneth S;Warren, Daniel E
• 通讯作者: Warren, Daniel E

Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients.

肥厚型心肌病患者心室力学的计算分析。

• 发表时间: 2023-01-18
• 影响因子: 4.6
• 作者: Mojumder, Joy;Fan, Lei;Nguyen, Thuy;Campbell, Kenneth S;Wenk, Jonathan F;Guccione, Julius M;Abraham, Theodore;Lee, Lik Chuan
• 通讯作者: Lee, Lik Chuan

Overview of mathematical modeling of myocardial blood flow regulation.

心肌血流调节数学模型概述。

• 发表时间: 2020
• 作者: Namani, Ravi;Lanir, Yoram;Lee, Lik Chuan;Kassab, Ghassan S
• 通讯作者: Kassab, Ghassan S

Regional end-systolic circumferential strain demonstrates compensatory segmental contractile function in patients with ST-segment elevation myocardial infarction.

局部收缩末期周向应变显示 ST 段抬高型心肌梗死患者的代偿性节段收缩功能。

• DOI: 10.1016/j.jbiomech.2021.110794
• 发表时间: 2021-12-02
• 期刊: Journal of biomechanics
• 影响因子: 2.4
• 作者: Leung SW;Ratajczak TM;Abo-Aly M;Shokri E;Abdel-Latif A;Wenk JF
• 通讯作者: Wenk JF

Impact of regulatory light chain mutation K104E on the ATPase and motor properties of cardiac myosin.

调节轻链突变 K104E 对心肌肌球蛋白 ATP 酶和运动特性的影响。

• 发表时间: 2021
• 作者: Rasicci, David V;Kirkland, Orville;Moonschi, Faruk H;Wood, Neil B;Szczesna;Previs, Michael J;Wenk, Jonathan F;Campbell, Kenneth S;Yengo, Christopher M
• 通讯作者: Yengo, Christopher M