Mechanistic investigations of structure-function interplay as causal

背景肥厚性心肌病（HCM）是最常见的遗传性心脏病之一，也是导致年轻人心源性猝死的主要原因。急性心肌缺血，即心肌血液供应突然短缺，被广泛认为是HCM致死性心律失常的一个因素，但临床指南中仍缺乏对缺血的评估。这在一定程度上是因为HCM中缺血与其他疾病特征的相互作用知之甚少，这限制了表征心律失常风险的尝试，影响了心电图（ECG）临床显著缺血的诊断，并限制了新型抗心律失常药物治疗的发展。目的和目的本研究旨在通过多尺度心脏电生理建模和模拟，探讨心肌缺血在HCM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。目的是：(1)研究缺血与HCM其他疾病特征（离子重塑和纤维化）相互作用的机制，以调节心律失常风险；(2)研究与运动引起的正常变化相比，HCM患者的心电图上的缺血表现如何；(3)研究雷诺嗪（一种抗心绞痛药物）对HCM患者心律失常风险的影响。确定可能从治疗中受益的患者亚组研究方法的新颖性研究将缺血作为HCM心室模拟的新因素。缺血是一个动态过程，在细胞水平和空间范围上具有不同的严重程度。考虑到这种复杂性，以及HCM中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，给科学计算带来了重大挑战。这些挑战是通过一种新颖的GPU心脏电生理求解器来解决的。此外，该研究采用新颖的方法将膜片钳、灌注和心电图数据结合起来，为计算模型提供信息和验证，将研究限制在临床相关病例上。这为更准确的“数字双胞胎”模拟铺平了道路，随着药物治疗在HCM模型人群中的应用，将朝着抗心律失常药物开发的计算机临床试验迈进。与EPSRC战略一致拟议的研究扩展了EPSRC资助的数学生物学和非线性系统领域的研究组合。它与医疗技术优化治疗的重大挑战（“及时准确的诊断、分层、预测建模和实时、循证决策的技术”）和新型计算和数学科学的跨领域能力（“计算机建模和仿真”）密切相关。合作伙伴Betty Raman教授（牛津临床磁共振研究中心）获得灌注成像数据，Raffaele Coppini教授（佛罗伦萨大学）获得人类HCM细胞测量的独特途径，Rafael Sachetto教授（<s:1> o jo<e:1> o del-Rei联邦大学）获得技术专业知识，Hugh Watkins教授（拉德克利夫医学院）和Iacopo Olivotto教授（Careggi大学医院）获得临床HCM专业知识。

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.