Basic/Translational Science -> Computer Modeling/Simulation D-AB02 - Machine Learning and Computational Modeling: A Step Towards Precision Medicine? (ID 16) Abstract Plus

D-AB02-06 - Usefulness Of Combination Of Mathematical Modeling And Cell Engineering Using Induced Pluripotent Stem Cells For Revealing Complex Disease Mechanism Of Inherited Channelopathy (ID 725)


Background: A missense mutation, CACNA1C-E1115K, located in the cardiac L-type calcium channel (LTCC), was recently reported to be associated with diverse arrhythmias. Several studies reported in-vivo and in-vitro modeling of this mutation, but actual mechanism and target drug of this disease has not been clarified due to its complex ion-mechanisms.
Objective: To reveal the mechanism of this diverse arrhythmogenic phenotype using combination of in-vitro and in-silico model.
Methods: We generated induced pluripotent stem cells (iPSCs) from a patient carrying heterozygous CACNA1C-E1115K and also newly developed ICaL-mutation mathematical model, fitted into experimental data, including its impaired ion selectivity. Furthermore, we installed this mathematical model into hiPSC-CM simulation model. We analyzed complementary ion channel functions and made a suggestion for drugs suitable for medication tests.
Results: Mutant in-silico model showed APD prolongation and frequent early afterdepolarization (EAD), which are same as in-vitro model. In-silico model revealed this EAD was mostly related to robust late-mode of sodium current occurred by Na+ overload and suggested that mexiletine is capable of reducing arrhythmia. Afterward, we applicated mexiletine onto hiPSC-CMs mutant model and found mexiletine suppress EADs.
Conclusion: Precise in-silico disease model can contribute predicting result of drug-testing for in-vitro model of complex inherited channelopathy.