Abstract:

BACKGROUND AND PURPOSE: Atomoxetine is a selective noradrenaline reuptake inhibitor, recently approved for the treatment of attention-deficit/hyperactivity disorder. So far, atomoxetine has been shown to be well tolerated, and cardiovascular effects were found to be negligible. However, two independent cases of QT interval prolongation, associated with atomoxetine overdose, have been reported recently. We therefore analysed acute and subacute effects of atomoxetine on cloned human Ether-a-Go-Go-Related Gene (hERG) channels. EXPERIMENTAL APPROACH: hERG channels were heterologously expressed in Xenopus oocytes and in a human embryonic kidney cell line and hERG currents were measured using voltage clamp and patch clamp techniques. Action potential recordings were made in isolated guinea-pig cardiomyocytes. Gene expression and channel surface expression were analysed using quantitative reverse transcriptase polymerase chain reaction, Western blot and the patch clamp techniques. KEY RESULTS: In human embryonic kidney cells, atomoxetine inhibited hERG current with an IC(50) of 6.3 micromol.L(-1). Development of block and washout were fast. Channel activation and inactivation were not affected. Inhibition was state-dependent, suggesting an open channel block. No use-dependence was observed. Inhibitory effects of atomoxetine were attenuated in the pore mutants Y652A and F656A. In guinea-pig cardiomyocytes, atomoxetine lengthened action potential duration without inducing action potential triangulation. Overnight incubation with high atomoxetine concentrations resulted in a decrease of channel surface expression. CONCLUSIONS AND IMPLICATIONS: Whereas subacute effects of atomoxetine seem negligible under therapeutically relevant concentrations, hERG channel block should be considered in cases of atomoxetine overdose and when administering atomoxetine to patients at increased risk for the development of acquired long-QT syndrome.

Abstract:

The anticholinergic antiparkinson drug orphenadrine is an antagonist at central and peripheral muscarinic receptors. Orphenadrine intake has recently been linked to QT prolongation and Torsade-de-Pointes tachycardia. So far, inhibitory effects on I Kr or cloned HERG channels have not been examined. HERG channels were heterologously expressed in a HEK 293 cell line and in Xenopus oocytes and HERG current was measured using the whole cell patch clamp and the double electrode voltage clamp technique. Orphenadrine inhibits cloned HERG channels in a concentration dependent manner, yielding an IC50 of 0.85 μM in HEK cells. Onset of block is fast and reversible upon washout. Orphenadrine does not alter the half-maximal activation voltage of HERG channels. There is no shift of the half-maximal steady-state-inactivation voltage. Time constants of direct channel inactivation are not altered significantly and there is no use-dependence of block. HERG blockade is attenuated significantly in mutant channels lacking either of the aromatic pore residues Y652 and F656. In conclusion, we show that the anticholinergic agent orphenadrine is an antagonist at HERG channels. These results provide a novel molecular basis for the reported proarrhythmic side effects of orphenadrine

Abstract:

With ECG imaging it is possible to reconstruct cardiac electrical activity noninvasively from measurements of the electrocardiogram (ECG). To facilitate the recon- struction, an MRI- or CT- based model of the body is re- quired, which is represented as a volume conductor. A mathematically ill-posed problem is solved to reconstruct the cardiac sources from potentials collected on the body surface. To obtain a body surface potential map (BSPM) electrodes are ideally placed allover the entire thorax. In practical applications, however, the number of electrodes is limited and the placing is subject to constraints. We in- vestigate the effect of different electrode setups on the ill- posedness of the inverse problem. In particular, electrode setups are chosen to comply with constraints for female pa- tients in the catheter lab.

Abstract:

Congenital Long-QT Syndrome (LQTS) is a genetic dis- order affecting the repolarization of the heart. The most prevalent subtypes of LQTS are LQT1-3. In this work, we aim to evaluate the differences in the T-waves of simu- lated LQT1-3 in order to identify markers in the ECG that might help to classify patients solely based on ECG mea- surements. For LQT1, mutation S277L was used to char- acterize IKs and mutation S818L in IKr for LQT2. Volt- age clamp data were used to parametrize the ion channel equations of the ten Tusscher and Panfilov model of hu- man ventricular electrophysiology. LQT3 was integrated using an existing mutant INa model. The monodomain model was used in a transmural and apico-basal heteroge- neous model of the ventricles to calculate ventricular exci- tation propagation. The forward calculation on a torso model was performed to determine body surface ECGs. Compared to the physiological case with a QT-time of 375 ms, this interval was prolonged in all LQTS (LQT1 423 ms; LQT2 394 ms; LQT3 405 ms). The T-wave ampli- tude was changed (Einthoven lead II: LQT1 108%; LQT2 91%; LQT3 103%). Also, the width of the T-wave was en- larged (full width at half maximum: LQT1 111%; LQT2 125%; LQT3 109%). At the current state of modeling and data analysis, the three LQTS have not been distinguish- able solely by ECG data.

Abstract:

Generally, models of cardiac electrophysiology describe physiologic conditions in detail. However, other conditions, such as drug interactions or mutations of ion channels are of interest for research. Therefore, the simulated ion currents have to be fitted to measured voltage or patch clamp data. In this work, three different methods for the model parametrization were compared: one based on Powells algorithm implemented in a modular C++ framework and two optimization techniques realized in Matlab. The latter two approaches differed in solving the ordinary differential equations describing the channel gating. They can either be approximated numerically or solved analytically, since the transmembrane voltage is a piecewise constant function during the applied clamp protocol. All three methods were compared regarding computing time and quality of the fit using least squares. The modular C++ framework was slower than the numerical Matlab method, which took longer than the analytical one. The quality of the fit was similar for almost all analyzed methods. Therefore, the analytical method grants a fast and reliable solution for the calibration of ion current models for applications with constant membrane voltage, as e.g. in case of voltage or patch clamp data.

Abstract:

Atrial fibrillation is the most common type of cardiac dysrhythmia. A catheter based ablation of abnormal heart tissue has become a popular method to treat and possibly terminate this arrhythmia. For better treatment, it is important to improve the automated analysis and preprocessing of these signals. In this work, two sets of clinical data of a patient recorded during atrial fibrillation were analyzed to characterize, differentiate, and detect signals showing properties of clinical interest. Therefore, the information of unipolar as well as bipolar electrograms were taken into account. According to questions of clinical interest, a workflow using different methods was implemented.A useful analysis of the electrograms was enabled by the detection of segments with a constant catheter position. Therefore, the x-, y-, and z-coordinates of all 20 mapping electrodes were analyzed. In so doing, 9 segments with a mean length of 4.78 seconds of a 60 second signal respectively 4 segments with a mean length of 4 seconds of a 30 second signal were each detected as being stable. A distinction between signal segments containing clear activation waves and segments with a greater degree of fractionation could be made by the analysis of the signal activity. Therefore, active segments were detected using a wavelet-based approach. Non-fractionated signal segments were labeled as segments with an activity ratio less or equal than 20 %. Drivers of atrial fibrillation are supposed to be identifiable by the detection of highly organized areas. For this purpose, the similarity of activation waves was analyzed and similar activation waves (metric less or equal than 0.6) were then color-coded and highlighted in the signal. Knowledge about the excitation patterns can guide the ablation therapy. Therefore, local activation times of adjacent unipolar signals were detected and assigned to each other to determine spatio- temporal wavefronts. Complex dynamics of cardiac fibrillation can be understood by mapping the spatial distribution of the reconstructed phase. The phase was reconstructed correctly, if unipolar signals containing clear activation waves were recomposed with a sum of sinusoidal wavelets. Since bipolar electrograms originate from the difference of two unipolar measurements, another interesting analysis was the fractionation of associated unipolar signals.