Mechanistic investigations of structure-function interplay as causal

结构-功能相互作用作为因果关系的机制研究

• 批准号: 2421745
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2421745
• 关键词: Mechanistic; investigations; structure; function; interplay

BackgroundHypertrophic cardiomyopathy (HCM) is one of the most common genetic heart diseases and a leading cause of sudden cardiac death in the young. Acute myocardial ischaemia, where there is a sudden shortage of blood supply to the heart muscle, is widely acknowledged as a contributor to lethal arrhythmias in HCM, yet the assessment of ischaemia remains absent from clinical guidelines. This is in part because the interactions that ischaemia has with other disease features in HCM are poorly understood, which limits attempts to characterise arrhythmic risk, affects the diagnosis of clinically significant ischaemia on electrocardiography (ECG), and constrains the development of novel antiarrhythmic pharmacologic therapies.Aims and ObjectivesThe research aims to investigate the role of myocardial ischaemia in HCM using multiscale cardiac electrophysiology modelling and simulation, to inform risk stratification, ECG diagnosis and antiarrhythmic therapy. The objectives are to:(i) investigate the mechanisms by which ischaemia interacts with other disease features in HCM (ionic remodelling and fibrosis) to modulate arrhythmic risk(ii) investigate how ischaemia manifests on the ECG in HCM in comparison to normal changes that occur with exercise, to improve the diagnosis of ischaemia on stress ECG(iii) investigate the effects of ranolazine (an antianginal drug) on arrhythmic risk in HCM, to identify patient subgroups likely to benefit from treatmentNovelty of Research MethodologyThe research includes ischaemia as a novel factor in simulations of HCM ventricles. Ischaemia, as a dynamic process, has variable severity at a cellular level and spatial extent. Accounting for this complexity, alongside existing variability in the severity of ionic remodelling and fibrosis in HCM, and intrinsic population electrophysiological variability, imposes significant scientific computing challenges. These challenges are addressed using a novel GPU cardiac electrophysiology solver. Additionally, the research uses novel methods to combine patch-clamp, perfusion and ECG data to inform and validate the computational models, constraining the investigations to clinically relevant cases. This paves the way for more accurate 'digital twin' simulations, which with the application of drug therapy to the HCM population of models, moves towards in silico clinical trials for antiarrhythmic drug development.Alignment with EPSRC strategiesThe proposed research extends the current portfolio of EPSRC funded research in the areas of Mathematical Biology and Non-linear Systems. It aligns closely with Healthcare Technologies Grand Challenges for Optimising Treatment ('technologies for timely and accurate diagnosis, stratification, predictive modelling, and real-time, evidence-based decision making') and the Cross-Cutting Capabilities on Novel Computational and Mathematical Sciences ('in silico modelling and simulation').CollaboratorsCollaborations are established with Prof. Betty Raman (Oxford Centre for Clinical Magnetic Resonance Research) for access to perfusion imaging data, Prof. Raffaele Coppini (University of Florence) for unique access to human HCM cellular measurements, Prof. Rafael Sachetto (Federal University of São João del-Rei) for technical expertise, and Prof. Hugh Watkins (Radcliffe Department of Medicine) and Prof. Iacopo Olivotto (Careggi University Hospital) for clinical HCM expertise.

肥厚性心肌病(HCM)是最常见的遗传性心脏病之一，也是导致年轻人心脏性猝死的主要原因。急性心肌缺血是指心肌的血液供应突然不足，被广泛认为是导致肥厚性心肌病致死性心律失常的因素之一，然而临床指南中仍然缺乏对缺血的评估。这在一定程度上是因为心肌缺血与心肌梗死其他疾病特征的相互作用尚不清楚，这限制了表征心律失常风险的尝试，影响了临床上有意义的心肌缺血的心电图诊断，并限制了新的抗心律失常药物治疗的发展。目的和目的本研究旨在利用多尺度心脏电生理学建模和模拟来研究心肌缺血在心肌梗死中的作用，为风险分层、心电图诊断和抗心律失常治疗提供信息。其目的是：(1)探讨缺血与肥厚性心肌病其他疾病特征(离子重塑和纤维化)相互作用以调节心律失常风险的机制(2)与运动中发生的正常变化相比，肥厚性心肌病如何在心电图上表现缺血，提高应激性心电图上缺血的诊断；(3)研究雷诺嗪(一种抗心绞痛药物)对肥厚性心肌病心律失常风险的影响，以确定可能从治疗中受益的患者亚群。缺血，作为一个动态过程，在细胞水平和空间范围具有不同的严重程度。考虑到这种复杂性，以及肥厚性心肌病离子重塑和纤维化严重程度的现有变异性，以及固有的群体电生理变异性，施加了重大的科学计算挑战。使用一种新型的GPU心脏电生理学解算器来解决这些挑战。此外，该研究使用新的方法结合膜片钳、灌流和心电数据来通知和验证计算模型，将研究限制在临床相关病例。这为更准确的数字双胞胎模拟铺平了道路，随着药物治疗应用于HCM模型人群，走向抗心律失常药物开发的电子临床试验。与EPSRC策略结盟建议的研究扩展了EPSRC资助的数学生物学和非线性系统领域的研究组合。它与医疗保健技术在优化治疗方面面临的重大挑战(“及时和准确的诊断、分层、预测建模和实时、基于证据的决策的技术”)以及新的计算和数学科学的交叉能力(“计算机建模和模拟”)密切相关。与贝蒂·拉曼教授(牛津临床磁共振研究中心)建立了合作伙伴，以访问血流成像数据，拉斐尔·科皮尼教授(佛罗伦萨大学)，以独特的方式访问人类HCM细胞测量，拉斐尔·萨切托教授(S联邦大学若昂·德尔雷)建立了技术专长，Hugh Watkins教授(拉德克利夫医学系)和Iacopo Olivotto教授(Careggi大学医院)提供临床HCM专业知识。