Dataset Information

Markov models of use-dependence and reverse use-dependence during the mouse cardiac action potential.

ABSTRACT: The fast component of the cardiac transient outward current, I(Ktof), is blocked by a number of drugs. The major molecular bases of I(Ktof) are Kv4.2/Kv4.3 voltage-gated potassium channels. Drugs with similar potencies but different blocking mechanisms have differing effects on action potential duration (APD). We used in silico analysis to determine the effect of I(Ktof)-blocking drugs with different blocking mechanisms on mouse ventricular myocytes. We used our existing mouse model of the action potential, and developed 4 new Markov formulations for I(Ktof), I(Ktos), I(Kur), I(Ks). We compared effects of theoretical I(Ktof)-specific channel blockers: (1) a closed state, and (2) an open channel blocker. At concentrations lower or close to IC(50), the drug which bound to the open state always had a much greater effect on APD than the drug which bound to the closed state. At concentrations much higher than IC(50), both mechanisms had similar effects at very low pacing rates. However, an open state binding drug had a greater effect on APD at faster pacing rates, particularly around 10 Hz. In summary, our data indicate that drug effects on APD are strongly dependent not only on IC(50), but also on the drug binding state.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC3412869 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Markov models of use-dependence and reverse use-dependence during the mouse cardiac action potential.

Zhou Qinlian Q Bett Glenna C L GC Rasmusson Randall L RL

PloS one 20120806 8

The fast component of the cardiac transient outward current, I(Ktof), is blocked by a number of drugs. The major molecular bases of I(Ktof) are Kv4.2/Kv4.3 voltage-gated potassium channels. Drugs with similar potencies but different blocking mechanisms have differing effects on action potential duration (APD). We used in silico analysis to determine the effect of I(Ktof)-blocking drugs with different blocking mechanisms on mouse ventricular myocytes. We used our existing mouse model of the actio ...[more]

PMID: 22879935

Similar Datasets

Project description:Recent efforts to ensure the reliability of computational model-based predictions in healthcare, such as the ASME V&V40 Standard, emphasize the importance of uncertainty quantification (UQ) and sensitivity analysis (SA) when evaluating computational models. UQ involves empirically determining the uncertainty in model inputs-typically resulting from natural variability or measurement error-and then calculating the resultant uncertainty in model outputs. SA involves calculating how uncertainty in model outputs can be apportioned to input uncertainty. Rigorous comprehensive UQ/SA provides confidence that model-based decisions are robust to underlying uncertainties. However, comprehensive UQ/SA is not currently feasible for whole heart models, due to numerous factors including model complexity and difficulty in measuring variability in the many parameters. Here, we present a significant step to developing a framework to overcome these limitations. We: (i) developed a novel action potential (AP) model of moderate complexity (six currents, seven variables, 36 parameters); (ii) prescribed input variability for all parameters (not empirically derived); (iii) used a single "hyper-parameter" to study increasing levels of parameter uncertainty; (iv) performed UQ and SA for a range of model-derived quantities with physiological relevance; and (v) present quantitative and qualitative ways to analyze different behaviors that occur under parameter uncertainty, including "model failure". This is the first time uncertainty in every parameter (including conductances, steady-state parameters, and time constant parameters) of every ionic current in a cardiac model has been studied. This approach allowed us to demonstrate that, for this model, the simulated AP is fully robust to low levels of parameter uncertainty - to our knowledge the first time this has been shown of any cardiac model. A range of dynamics was observed at larger parameter uncertainty (e.g., oscillatory dynamics); analysis revealed that five parameters were highly influential in these dynamics. Overall, we demonstrate feasibility of performing comprehensive UQ/SA for cardiac cell models and demonstrate how to assess robustness and overcome model failure when performing cardiac UQ analyses. The approach presented here represents an important and significant step toward the development of model-based clinical tools which are demonstrably robust to all underlying uncertainties and therefore more reliable in safety-critical decision-making.

Project description:BackgroundEarly afterdepolarizations (EADs) are pathological voltage oscillations during the repolarization phase of cardiac action potentials (APs). EADs are caused by drugs, oxidative stress or ion channel disease, and they are considered as potential precursors to cardiac arrhythmias in recent attempts to redefine the cardiac drug safety paradigm. The irregular behaviour of EADs observed in experiments has been previously attributed to chaotic EAD dynamics under periodic pacing, made possible by a homoclinic bifurcation in the fast subsystem of the deterministic AP system of differential equations.ResultsIn this article we demonstrate that a homoclinic bifurcation in the fast subsystem of the action potential model is neither a necessary nor a sufficient condition for the genesis of chaotic EADs. We rather argue that a cascade of period doubling (PD) bifurcations of limit cycles in the full AP system paves the way to chaotic EAD dynamics across a variety of models including a) periodically paced and spontaneously active cardiomyocytes, b) periodically paced and non-active cardiomyocytes as well as c) unpaced and spontaneously active cardiomyocytes. Furthermore, our bifurcation analysis reveals that chaotic EAD dynamics may coexist in a stable manner with fully regular AP dynamics, where only the initial conditions decide which type of dynamics is displayed.ConclusionsEADs are a potential source of cardiac arrhythmias and hence are of relevance both from the viewpoint of drug cardiotoxicity testing and the treatment of cardiomyopathies. The model-independent association of chaotic EADs with period doubling cascades of limit cycles introduced in this article opens novel opportunities to study chaotic EADs by means of bifurcation control theory and inverse bifurcation analysis. Furthermore, our results may shed new light on the synchronization and propagation of chaotic EADs in homogeneous and heterogeneous multicellular and cardiac tissue preparations.

Dataset Information

Markov models of use-dependence and reverse use-dependence during the mouse cardiac action potential.

Publications

Markov models of use-dependence and reverse use-dependence during the mouse cardiac action potential.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets