Slower Calcium Handling Balances Faster Cross-Bridge Cycling in Human MYBPC3 HCM

BACKGROUND

The pathogenesis of MYBPC3-associated hypertrophic cardiomyopathy (HCM) is still unresolved. In our HCM patient cohort, a large and well-characterized population carrying the MYBPC3:c772G>A variant (p.Glu258Lys, E258K) provides the unique opportunity to study the basic mechanisms of MYBPC3-HCM with a comprehensive translational approach.

METHODS

We collected clinical and genetic data from 93 HCM patients carrying the MYBPC3:c772G>A variant. Functional perturbations were investigated using different biophysical techniques in left ventricular samples from 4 patients who underwent myectomy for refractory outflow obstruction, compared with samples from non-failing non-hypertrophic surgical patients and healthy donors. Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes and engineered heart tissues (EHTs) were also investigated.

RESULTS

Haplotype analysis revealed MYBPC3:c772G>A as a founder mutation in Tuscany. In ventricular myocardium, the mutation leads to reduced cMyBP-C (cardiac myosin binding protein-C) expression, supporting haploinsufficiency as the main primary disease mechanism. Mechanical studies in single myofibrils and permeabilized muscle strips highlighted faster cross-bridge cycling, and higher energy cost of tension generation. A novel approach based on tissue clearing and advanced optical microscopy supported the idea that the sarcomere energetics dysfunction is intrinsically related with the reduction in cMyBP-C. Studies in single cardiomyocytes (native and hiPSC-derived), intact trabeculae and hiPSC-EHTs revealed prolonged action potentials, slower Ca2+ transients and preserved twitch duration, suggesting that the slower excitation-contraction coupling counterbalanced the faster sarcomere kinetics. This conclusion was strengthened by in silico simulations.

CONCLUSIONS

HCM-related MYBPC3:c772G>A mutation invariably impairs sarcomere energetics and cross-bridge cycling. Compensatory electrophysiological changes (eg, reduced potassium channel expression) appear to preserve twitch contraction parameters, but may expose patients to greater arrhythmic propensity and disease progression. Therapeutic approaches correcting the primary sarcomeric defects may prevent secondary cardiomyocyte remodeling.

Modelling and in silico simulation of human induced pluripotent stem cell derived cardiomyocyte electro-mechanical properties

Funding Acknowledgements

Type of funding sources: Foundation. Main funding source(s): BHF

Background

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) enable accessible human data-based cardiology studies. However, a caveat in hiPSC-CM-based studies is their immature electrophysiological and contractile phenotype. One of the modifications occurring during hiPSC-CM maturation is the change in myofilament calcium sensitivity, an important indicator of cardiac muscle function [1, 2]. In silico hiPSC-CM investigations could help improve understanding of the hiPSC-CM-specific contractile behaviour and its changes during maturation. Considering the growing use of hiPSC-CM, it is vital to enable investigations of hiPSC-CM-specific contractile features.

Purpose

To address the need of hiPSC-CM model with integrated contractile element, our goal is to develop an electromechanical human data-based iPSC-CM computer model. We aim to use the model to investigate the effects of the changes in myofilament calcium sensitivity on hiPSC-CM electrophysiology and contractility.

Methods

We coupled a published hiPSC-CM electrophysiological model [3] with a model of the human adult cardiomyocyte contractile machinery [4] by linking intracellular calcium and calcium-bound troponin dynamics. The established electromechanical hiPSC-CM model was calibrated using experimental hiPSC-CM active tension data and its simulated electromechanical biomarkers were also evaluated against experimental action potential and calcium transient data. We conducted a sensitivity analysis to investigate the effects of changes in myofilament calcium sensitivity on the electrophysiology and contractility of the cell.

Results

First, we demonstrated that the model successfully reproduces the hiPSC-CM contractile phenotype. Simulations showed a peak twitch tension of 0.44 kPa which takes 201 ms to peak and 164 ms to achieve 50% relaxation, which all agree with the experimental hiPSC-CM values. Simulated calcium transient and action potential biomarkers remain within the experimentally established ranges after electromechanical coupling. The sensitivity analysis of the hiPSC-CM model focused on the myofilament calcium sensitivity effects showed an increase in active tension amplitude with a decrease in calcium transient peaks upon increased myofilament calcium sensitivity. Large increases in myofilament calcium sensitivity result in depolarization failure with low amplitude fluctuations of membrane voltage, calcium transient and active tension. Altogether simulation results demonstrate the usability of the model for simulating and exploring not only physiological, but also pathological cardiac conditions.

Conclusions

We present a new electromechanical hiPSC-CM model for in silico hiPSC-CM-based studies. The model has been evaluated against experimental data and has demonstrated the capacity to generate key electrophysiological currents, active tension as well as myofilament calcium sensitivity-induced electromechanical abnormalities.

Abstract 402: Defining Diverse Disease Pathomechanisms Across Thick And Thin Filament Hypertrophic Cardiomyopathy Variants

Hypertrophic cardiomyopathy (HCM) affects as many as ~1 in 500 individuals, and is often typified by hyperdynamic contraction and poor cellular relaxation. HCM can be caused by mutations in a variety of key contractile proteins of the sarcomere. A large proportion of these variants are found in MYBPC3, MYH7, TNNT2, and TNNI3. These genes encode proteins that control cardiac muscle contraction at the thick (MYBPC3 and MYH7) and thin filaments (TNNT2 and TNNI3) of the sarcomere. In this study we use human induced pluripotent stem cell derived cardiomyocytes to model HCM across all of these genes. We do this to define key mechanistic differences between thick and thin filament HCM. We define sarcomeric contractility (SarcTrack) calcium transients (CalTrack) and myosin states using the mant-ATP assay. We use the parametric data from these experimental studies in iPSC-CMs to model possible disease mechanisms in silico. Our experimental analysis highlights that both thick and thin filament HCM variants cause cellular hypercontractility, with slowed cellular relaxation. We find that thick filament HCM variants drive cellular HCM phenotypes by destabilising the myosin interacting heads motif (IHM), showing a marked reduction in the super relaxed state of myosin. Counterintuitively thin filament based HCM variants show a reduction in DRX myosin. When applying Mavacamten the allosteric myosin ATPase inhibitor to our thin and thick filament HCM variant iPSC-CMs we find a dichotomy of cellular responses. The thick filament variants studied all show a clear resolution of cellular HCM. However, not all cellular phenotypes of thin filament HCM are corrected by Mavacamten treatment, although there is benefit. We conclude that causal mechanisms of thick filament HCM are well corrected at the molecular and cellular level by Mavacamten, but these causal mechanisms in thin filament based HCM are not suitably corrected. We highlight key mechanistic pharmacological targets for thin filament variants that could add cellular benefit to HCM phenotype resolution.

CalTrack: High-Throughput Automated Calcium Transient Analysis in Cardiomyocytes

[Figure: see text].

Human-based computational and experimental investigation of disease mechanisms in mutation-specific hypertrophic cardiomyopathy

Funding Acknowledgements

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 764738. British Heart Foundation Intermediate Basic Science Fellowship (FS/17/22/32644).

Background

The pathogenic TNNI3R21C/+ variant causes malignant hypertrophic cardiomyopathy (HCM) with high incidence of sudden cardiac death, even in individuals absent of hypertrophy. There is evidence to support a known biophysical defect in the protein, yet the cellular mechanisms that precipitate adverse clinical outcomes remain unclear.

Purpose

We aim to computationally model and map the TNNI3R21C/+ cellular phenotype observed in induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) to human disease, thereby explaining the key mechanisms driving HCM in TNNI3R21C/+ variant carriers. 

Methods

Wild-type (WT) and TNNI3R21C/+ iPSC-CMs were characterised by calcium transient analysis and direct sarcomere tracking to assess cellular contraction and relaxation. In-vitro data was used to inform the in-silico modelling of human cardiomyocytes. We constructed an in-silico population of WT adult cardiomyocytes and used it to transform the in-vitro data into corresponding adult phenotypes by means of a novel iPSC-to-adult data mapping. We tested the hypothesis that the abnormal TNNI3R21C/+ phenotype observed in iPSC-CMs would be explained by alterations in calcium affinity of troponin and increased myofilament calcium sensitivity. 

Results

Analysis of in-vitro iPSC-CM data showed that TNNI3R21C/+ cells exhibit increased contractility with slowed relaxation when compared to WT. They also exhibited a faster rise in the calcium transient with a slowed calcium decay in comparison to WT. The in-silico adult TNNI3R21C/+ phenotype from the iPSC-to-adult mapping replicated the abnormalities observed in iPSC-CMs. The WT in-silico population accurately covered the ranges of electromechanical biomarkers providing a representative cohort of physiological variability. The TNNI3R21C/+ calcium phenotype could be recovered by our in-silico mutant models. Simulation results suggest that calcium abnormalities in TNNI3R21C/+ are a direct consequence of abnormal calcium buffering by thin filaments, mediated by increases in calcium affinity of troponin and myofilament calcium sensitivity. The TNNI3R21C/+ phenotype could not be recovered if these two factors were considered in isolation. Corresponding contractility analyses of in-silico models showed that the calcium level changes caused by the TNNI3R21C/+ phenotype are associated with hypercontractility and diastolic dysfunction, well-known hallmarks of HCM, which were also observed in the iPSC-CM model of disease.

Conclusions

This study showcases human-based computational and experimental methodologies that unearth direct mechanistic explanations of phenotypes driven by the TNNI3R21C/+ HCM variant. We show that the TNNI3R21C/+ HCM-causing mutation exhibits multifactorial remodelling of troponin calcium affinity and myofilament calcium sensitivity. Unearthing mechanistic pathways in mutation-specific HCM will be key to develop effective pharmacological interventions for a wide variety of understudied variants.

Human biventricular electromechanical simulations on the progression of electrocardiographic and mechanical abnormalities in post-myocardial infarction

AIMS

Develop, calibrate and evaluate with clinical data a human electromechanical modelling and simulation framework for multiscale, mechanistic investigations in healthy and post-myocardial infarction (MI) conditions, from ionic to clinical biomarkers.

METHODS AND RESULTS

Human healthy and post-MI electromechanical simulations were conducted with a novel biventricular model, calibrated and evaluated with experimental and clinical data, including torso/biventricular anatomy from clinical magnetic resonance, state-of-the-art human-based membrane kinetics, excitation-contraction and active tension models, and orthotropic electromechanical coupling. Electromechanical remodelling of the infarct/ischaemic region and the border zone were simulated for ischaemic, acute, and chronic states in a fully transmural anterior infarct and a subendocardial anterior infarct. The results were compared with clinical electrocardiogram and left ventricular ejection fraction (LVEF) data at similar states. Healthy model simulations show LVEF 63%, with 11% peak systolic wall thickening, QRS duration and QT interval of 100 ms and 330 ms. LVEF in ischaemic, acute, and chronic post-MI states were 56%, 51%, and 52%, respectively. In linking the three post-MI simulations, it was apparent that elevated resting potential due to hyperkalaemia in the infarcted region led to ST-segment elevation, while a large repolarization gradient corresponded to T-wave inversion. Mechanically, the chronic stiffening of the infarct region had the benefit of improving systolic function by reducing infarct bulging at the expense of reducing diastolic function by inhibiting inflation.

CONCLUSION

Our human-based multiscale modelling and simulation framework enables mechanistic investigations into patho-physiological electrophysiological and mechanical behaviour and can serve as testbed to guide the optimization of pharmacological and electrical therapies.

The 'Digital Twin' to enable the vision of precision cardiology

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.

Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers

The human heart beats as a result of multiscale nonlinear dynamics coupling subcellular to whole organ processes, achieving electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation software. In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation-contraction and active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200% - 1000% variations in key parameters result in changes in clinically-relevant mechanical biomarkers ranging from diseased to healthy values in clinical studies. Furthermore mechanical biomarkers are primarily affected by only one or two parameters. Specifically, ejection fraction is dominated by the scaling parameter of the active tension model and its scaling parameter in the normal direction ( k ort 2 ); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered ( P ej ) and the compliance of the Windkessel fluid model ( C ); and the longitudinal fractional shortening is dominated by the fibre angle ( ϕ ) and k ort 2 . The wall thickening does not seem to be clearly dominated by any of the considered input parameters. In summary, this study presents in detail the description and implementation of a human-based coupled electromechanical modelling and simulation framework, and a high performance computing study on the sensitivity of mechanical biomarkers to key model parameters. The tools and knowledge generated enable future investigations into disease and drug action on human ventricles.