Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm

Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm

Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia

Reduced blood flow in the coronary arteries can lead to damaged heart tissue (myocardial ischaemia). Although one method for detecting myocardial ischaemia involves changes in the ST segment of the electrocardiogram, the relationship between these changes and subendocardial ischaemia is not fully understood. In this study, we modelled ST-segment epicardial potentials in a slab model of cardiac ventricular tissue, with a central ischaemic region, using the bidomain model, which considers conduction longitudinal, transverse and normal to the cardiac fibres. We systematically quantified the effect of uncertainty on the input parameters, fibre rotation angle, ischaemic depth, blood conductivity and six bidomain conductivities, on outputs that characterise the epicardial potential distribution. We found that three typical types of epicardial potential distributions (one minimum over the central ischaemic region, a tripole of minima, and two minima flanking a central maximum) could all occur for a wide range of ischaemic depths. In addition, the positions of the minima were affected by both the fibre rotation angle and the ischaemic depth, but not by changes in the conductivity values. We also showed that the magnitude of ST depression is affected only by changes in the longitudinal and normal conductivities, but not by the transverse conductivities

Multi-scale modelling and simulations into the mechanisms linking neuronal nitric oxide synthase and atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Its incidence is projected to rise due to population ageing and increasing prevalence of associated risk factors. AF alters, or remodels, the affected atrial tissue, promoting future occurrences of itself and increasing resistance to treatment. Mechanisms underlying AF initiation and remodelling are not well understood. Recent experimental evidence indicates that decreased levels of the neuronal isoform of Nitric Oxide Synthase (nNOS) may be related to AF onset and precede remodelling. However, the potential mechanisms cannot be easily elucidated with experiments alone. Furthermore, experiments are complicated by inter-subject variability, which is particularly important in human studies due to the wide heterogeneity of the human population. In this thesis, I use multi-scale modelling and simulations in synergy with experimental information to investigate mechanistic links between nNOS and AF at the level of ionic currents/cellular action potential/whole atria in human. First, I construct populations of models spanning experimentally-observed variability in human atrial myocytes under control conditions. Second, I use those populations of control models to identify key ionic mechanisms underpinning nNOS-mediated regulation of the cellular action potential in human atrial myocytes. I show that two of those currents – IKur and IK1 – play a key role in explaining the phenotypic shortening of the action potential observed under nNOS inhibition conditions and preceding AF-induced tissue remodelling. Finally, I build models of human whole atria and establish that this action potential shortening leads to the establishment of a vulnerable substrate, and hence is the main mechanism of pro-arrhythmia at this level. Overall, I provide a picture of nNOS-mediated mechanisms related to AF onset from ionic currents to the whole organ level. </p

Constructing human atrial electrophysiological models mimicking a patient-specific cell group

Patient-specific modelling aims to produce computational models of human physiology tailored to a specific patient. In line with this, we construct multiple human atrial electrophysiological models mimicking the behaviour of single atrial myocytes extracted from a homogeneous patient group. We study cells with the action potential duration being 2-3 times lower than in human atrial electrophysiological models. Assuming such a difference can be rationalized by altering the values of ionic conductances, we generated 15000 models by simultaneously varying conductance values of the most important currents affecting the action potential (AP). We paced the models at different frequencies and conditions, probing the importance of ion concentrations and stimulus strength, and kept the models producing AP biomarkers consistent with experiments. We discovered that both the ionic conductances and external factors play a critical role in producing biomarker values consistent with experiments. By mimicking experimental conditions, we generated 604 models fully covering the experimental range of AP biomarkers. In conclusion, both the ionic conductances and external factors are vital in tailoring single-cell electrophysiological models to a narrow patient group. This has implications in understanding the propensity of subgroups of the total population to disease conditions

Constructing human atrial electrophysiological models mimicking a patient-specific cell group

Patient-specific modelling aims to produce computational models of human physiology tailored to a specific patient. In line with this, we construct multiple human atrial electrophysiological models mimicking the behaviour of single atrial myocytes extracted from a homogeneous patient group. We study cells with the action potential duration being 2-3 times lower than in human atrial electrophysiological models. Assuming such a difference can be rationalized by altering the values of ionic conductances, we generated 15000 models by simultaneously varying conductance values of the most important currents affecting the action potential (AP). We paced the models at different frequencies and conditions, probing the importance of ion concentrations and stimulus strength, and kept the models producing AP biomarkers consistent with experiments. We discovered that both the ionic conductances and external factors play a critical role in producing biomarker values consistent with experiments. By mimicking experimental conditions, we generated 604 models fully covering the experimental range of AP biomarkers. In conclusion, both the ionic conductances and external factors are vital in tailoring single-cell electrophysiological models to a narrow patient group. This has implications in understanding the propensity of subgroups of the total population to disease conditions

From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study

Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and sub-cellular ionic densities on calcium transient dynamics. Results show that: (1) Variability in APs and ionic densities is large, even within an apparently homogenous patient cohort, and translates into ±100% variation in ionic conductances; (2) Experimentally-calibrated populations of models with wide variations in ionic densities yield APs overlapping with those obtained experimentally, even if AP characteristics of the original generic model differed significantly from experimental AP’s; (3) Model calibration with AP recordings restricts the variability in ionic densities affecting upstroke and resting potential, but redundancy in repolarisation currents admits substantial variability in ionic densities; (4) Model populations constrained with experimental APs and ionic densities exhibit three calcium transient phenotypes, differing in intracellular Ca2+ handling and Na+/Ca2+ membrane extrusion. These findings advance our understanding of the impact of variability in human atrial electrophysiology

From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study

Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and sub-cellular ionic densities on calcium transient dynamics. Results show that: (1) Variability in APs and ionic densities is large, even within an apparently homogenous patient cohort, and translates into ±100% variation in ionic conductances; (2) Experimentally-calibrated populations of models with wide variations in ionic densities yield APs overlapping with those obtained experimentally, even if AP characteristics of the original generic model differed significantly from experimental AP’s; (3) Model calibration with AP recordings restricts the variability in ionic densities affecting upstroke and resting potential, but redundancy in repolarisation currents admits substantial variability in ionic densities; (4) Model populations constrained with experimental APs and ionic densities exhibit three calcium transient phenotypes, differing in intracellular Ca2+ handling and Na+/Ca2+ membrane extrusion. These findings advance our understanding of the impact of variability in human atrial electrophysiology