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Personalizing Class I anti-Arrhythmic Drug Therapy

个性化 I 类抗心律失常药物治疗

基本信息

批准号：
10133139
负责人：
JONATHAN R SILVA
金额：
$ 67.05万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10133139
关键词：
Adrenergic Agents Affect Amiodarone Anti-Arrhythmia Agents Arrhythmia Biophysics Blinded Cardiac Cardiac Myocytes Cardiomyopathies Clinical Clinical Research Clinical Trials Computer Models Data Defibrillators Diagnosis Disease Dose Drug Interactions Drug Modelings Drug Prescriptions Drug Regulations Genetic Genetic Variation Genotype Guidelines Implant Macromolecular Complexes Maps Mass Spectrum Analysis Measures Methods Mexiletine Modeling Molecular Molecular Conformation Movement Mutation Outcome Outcome Measure Pain Patients Peripheral Blood Mononuclear Cell Pharmaceutical Preparations Pharmacology Pharmacotherapy Phosphorylation Phosphorylation Site Physicians Precision therapeutics Process Protocols documentation Regimen Registries Regulation Reporting Shock Sodium Channel Structure Syndrome Testing Toxic effect Variant Ventricular Ventricular Arrhythmia Ventricular Fibrillation Ventricular Tachycardia base biophysical properties cohort cost design drug efficacy experimental study genetic information genetic variant genomic data heart rate variability heart rhythm implantable device improved improved outcome induced pluripotent stem cell insight novel outcome prediction patient registry patient response patient subsets personalized medicine predicting response predictive modeling prevent prospective response side effect simulation stem cell differentiation stem cell model therapy outcome translational approach treatment strategy voltage wearable device

项目摘要

Summary We want to improve arrhythmia therapy outcomes by predicting an optimal anti-arrhythmic drug regimen for ventricular arrhythmia patients using genomic data and heart rhythm reports from wearable and implanted devices. Today, amiodarone is commonly prescribed to prevent painful shocks from defibrillators that are implanted in patients who suffer from ventricular arrhythmia. Nevertheless, amiodarone is toxic for many patients when it is used over a period of years. In contrast, the class 1b molecule, mexiletine has many fewer side effects, but is effective in fewer patients. We have shown that cardiac Na+ channel variants in patients with Long QT Type 3 Syndrome can significantly affect key biophysical gating parameters that determine whether patients respond to mexiletine therapy. We propose to apply a similar approach to determine how common genetic variants and β-adrenergic tone regulate mexiletine response in patients with ventricular arrhythmias. The project aims have been developed to 1) gain novel insight into the molecular mechanisms of β-adrenergic and variant regulation of the drug response, 2) create a predictive model by mapping parameters associated with these mechanisms to patient response in a clinical study, and 3) improve the model by gaining insight from an optimized induced pluripotent stem cell based model of the drug response. If the aims of the proposal are successful, we will set the stage for a prospective clinical trial that uses a predictive model to identify ventricular arrhythmia patients who will respond to mexiletine based on data that is becoming readily available to physicians.

总结我们希望通过预测最佳抗心律失常药物来改善心律失常治疗的结果使用基因组数据和心律报告的室性心律失常患者的方案可穿戴和植入设备。今天，胺碘酮通常用于预防疼痛植入室性心律失常患者体内的起搏器所产生的电击。然而，胺碘酮在使用多年后对许多患者是有毒的。在相比之下，1b类分子，美沙芬的副作用要少得多，但在更少的患者我们已经证明，长QT 3型患者的心脏Na+通道变异综合征可以显著影响决定是否患者对美西律治疗有反应。我们建议采用类似的方法来确定常见遗传变异和β-肾上腺素能紧张度如何调节患者的Mexilavine反应室性心律失常该项目的目标是：1）获得新的见解，药物反应的β-肾上腺素能和变体调节的分子机制，2）通过将与这些机制相关的参数映射到患者，临床研究中的反应，以及3）通过从优化的基于诱导多能干细胞的药物反应模型。如果提案的目的是如果成功，我们将为使用预测模型的前瞻性临床试验奠定基础，根据以下数据确定对美西律有反应的室性心律失常患者：变得容易被医生利用。