Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiomyopathy and the leading cause of sudden cardiac death (SCD) in the young. Myocardial ischemia plays a central role in HCM, as characterised by numerous imaging studies, which demonstrate that microvessel disease and perfusion defects occur in most HCM patients. The risk of intense exercise in HCM, which may further promote ischemia, is understudied and existing SCD risk models fail to account for this. Despite this, the electrophysiological mechanisms linking SCD and ischemia in HCM remain largely unexplored. A refined understanding of ischemia-related mechanisms in HCM is expected to improve risk stratification or yield novel therapies for SCD prevention in these patients.
Using the ToR-ORd ventricular cardiomyocyte model, populations of experimentally calibrated action potential models for control and HCM cardiomyocytes were created. The populations were subjected to acidosis, hyperkalemia and hypoxia separately and in combined cases of ischemia.
HCM cardiomyocytes exhibited increased sensitivity to ischemia. Effective refractory periods, which increased by 14±45 ms in control models during hyperkalemia, instead decreased by 153±57 ms in HCM models. The response of refractory periods to hypoxia was enhanced in HCM models at all levels of K-ATP channel activation. Selective removal of HCM ionic remodelling demonstrated that remodelling of the late sodium and rapidly delayed rectifier channels caused this enhanced sensitivity to ischemia. Late sodium current inhibitors such as ranolazine and disopyramide may prove beneficial in mitigating the ischemic response in HCM.
More broadly, our results highlight the potential of computational modelling to investigate the multifactorial nature of arrhythmic risk in human heart disease, such as the concomitant role of stress-precursors of arrhythmias in inherited cardiomyopathies, as well as to investigate novel mechanisms of drug action to tailor pharmacological therapy – a step toward the realisation of the digital twin in clinical decision making.