Abstract
Short QT (SQT) syndrome is a genetic cardiac disorder characterized by an abbreviated QT interval of the patient’s electrocardiogram. The syndrome is associated with increased risk of arrhythmia and sudden cardiac death and can arise from a number of ion channel mutations. Cardiomyocytes derived from induced pluripotent stem cells generated from SQT patients (SQT hiPSC-CMs) provide promising platforms for testing pharmacological treatments directly in human cardiac cells exhibiting mutations specific for the syndrome. However, a difficulty is posed by the relative immaturity of hiPSC-CMs, with the possibility that drug effects observed in SQT hiPSC-CMs could be very different from the corresponding drug effect in vivo. In this paper, we apply a multistep computational procedure for translating measured drug effects from these cells to human QT response. This process first detects drug effects on individual ion channels based on measurements of SQT hiPSC-CMs and then uses these results to estimate the drug effects on ventricular action potentials and QT intervals of adult SQT patients. We find that the procedure is able to identify IC50 values in line with measured values for the four drugs quinidine, ivabradine, ajmaline and mexiletine. In addition, the predicted effect of quinidine on the adult QT interval is in good agreement with measured effects of quinidine for adult patients. Consequently, the computational procedure appears to be a useful tool for helping predicting adult drug responses from pure in vitro measurements of patient derived cell lines.
Highlights
Short QT (SQT) syndrome is a cardiac channelopathy characterized by an abnormally short duration of the QT interval of the patient’s electrocardiogram (ECG) [1,2,3]
We set up the default human induced pluripotent stem cells (hiPSCs)-CM and adult base models for wild type (WT) and SQT1 based on measurements of WT and SQT1 IKr currents from [14]
We found that the effect of quinidine for adult patients estimated by the computational procedure fitted well with these measured drug responses, indicating that the applied computational procedure shows promise for reliably predicting adult drug responses based on measurements of hiPSC-CMs
Summary
Short QT (SQT) syndrome is a cardiac channelopathy characterized by an abnormally short duration of the QT interval of the patient’s electrocardiogram (ECG) [1,2,3]. The IKr blockers sotalol and ibutilide have been shown to be ineffective for SQT1 patients [12] This may be explained by the fact that these drugs primarily affect the inactivated state of the IKr channels, and the SQT1 mutation impairs the inactivation of the channels [6, 13, 14]. Quinidine, which affects both the open and inactivated states of IKr channels has proven to be more effective for SQT1 patients [15]. These examples demonstrate that investigations into drug effects on specific SQT mutations are needed in order to find appropriate pharmacological treatments
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