Abstract
Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K+, inward rectifying K+, L-type Ca2+, and Na+/K+ pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.
Highlights
Variability is perhaps an essential component of physiological systems
The first was created by Shannon et al [39] and the second was an updated version of that model by Mahajan et al [40], which includes updates to the L-type Ca2+ current, intracellular Ca2+ cycling, Na+- Ca2+ exchanger, and channel distributions updated to better replicate AP and Ca2+-handling dynamics at rapid stimulation rates
By using the values derived from the literature to describe physiological ranges for APD50 and APD90 (Table 1), it was possible to constrain the combinations of current conductances to those producing experimentally measured variability at each cycle length (CL)
Summary
Variability is perhaps an essential component of physiological systems. It is observed at all levels of spatial and temporal organisation, from sub-cellular processes to the whole-organism, and over time scales spanning from nanoseconds to years. Its importance in health and disease, where it may explain the spectrum of responses often seen between individuals, is largely unknown It has long been ignored in experimental and computational research. Computational models are generated based on reported mean values, creating representations of the ‘typical’ case that fail to account for underlying variability [1]. This approach results in a loss of information, but in an inability of models to explain physiological observations that may depend on the presence of variability. At all levels of integration, variability in cardiac activity exists, whether it is across the heart, between individual cells, or within ion-channels
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