Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) has a poor prognosis, with approximately 40% of patients dying within 10 years of diagnosis. There is an urgent need for improved treatment for the children and young adults that are predominantly affected by this disease. Currently, the most common treatment is the use of beta-blockers. However, they can be ineffective during high sympathetic activity, when delayed after depolarizations and sudden cardiac death can occur. Therefore, improved treatments that account for the dynamics of the sympathetic nervous system are needed.
We have developed a computational model of the postganglionic sympathetic neuron that can simulate drug effects, allowing extremely high efficiency analysis of potential drug treatments that can then be further investigated experimentally. This computational model was calibrated to patch-clamp data from human induced pluripotent stem cells (iPSCs) that were differentiated from CPVT patient cells. Therefore, the calibrated model replicates the CPVT patient phenotype. Bayesian calibration techniques were used to provide uncertainties in the prediction response that account for experimental error, model error, and calibration uncertainty.
We validated the simulated response to changes in extracellular concentrations, different input current, and potassium channel up-regulators to demonstrate the accurate response to drug effects. We accurately predicted firing frequency, resting membrane potential, and peak membrane potential for all experiments. This demonstrates that the model can be used for investigating drug effects, and once coupled with cardiac electrophysiology models has the potential to be used for in-silico trials that account for sympathetic activity.
The model predicts norepinephrine release at the neuro-cardiac junction and, in future work, will be coupled to cardiomyocyte models for predicting cardiac electrophysiological response. This sympathetic neuron model forms the foundation for a coupled sympathetic neuron – cardiac electrophysiology model that will be used to predict the response to CPVT treatments.