Loading...

Preprints

Gradient-based parameter optimization to determine membrane ionic current composition of human induced pluripotent stem cell-derived cardiomyocytes

Kohjitani H, Koda S, Himeno Y, Makiyama T, Yamamoto Y, Yoshinaga D, Wuriyanghai Y, Kashiwa A, Toyoda F, Zhang Y, Amano A, Noma A, Kimura T.
Preprint from
bioRxiv
18 May 2022
PPR
PPR494443
Abstract
1. Premature cardiac myocytes derived from human-induced pluripotent stem cells (hiPSC-CMs) show heterogeneous action potentials (APs), most probably because of different expression patterns of membrane ionic currents. We aim to develop a method of determining expression patterns of functional channels in terms of the whole-cell ionic conductances ( G x ) using individual spontaneous AP configurations. However, it has been suggested that apparently identical AP configurations were obtained by different sets of ionic currents in a mathematical model of cardiac membrane excitation. If so, the inverse problem of G x estimation might not be solved. We computationally tested the feasibility of the gradient-based optimization method. For realistic examination, conventional ‘cell-specific models’ were prepared by superimposing the model output of AP on each experimental AP record by the conventional manual adjustment of G x s of the baseline model. Then, G x s of 4 ~ 6 major ionic currents of the ‘cell-specific models’ were randomized within a range of ±5 ~ 15% and were used as initial parameter sets for the gradient-based automatic G x s recovery by decreasing the mean square error (MSE) between the target and model output. When plotted all data points of MSE - G x relation during the optimization, we found that the randomized population of G x s progressively converged to the original value of the cell-specific model with decreasing MSE. To confirm the absence of any other local minimum in the global search space, we mapped the MSE by randomizing G x s over a range of 0.1 ~ 10 times the control. No additional local minimum of MSE was obvious in the whole parameter space besides the global minimum of MSE at the default model parameter.