Electrophysiological and Contractile Effects of Disopyramide in Patients With Obstructive Hypertrophic Cardiomyopathy

Coppini, Raffaele; Ferrantini, Cecilia; Pioner, Josè Manuel; Santini, Lorenzo; Wang, Zhinuo Jenny; Palandri, Chiara; Scardigli, Marina; Vitale, Giulia; Sacconi, Leonardo; Stefàno, Pierluigi; Flink, Laura; Riedy, Katherine; Pavone, Francesco S.; Cerbai, Elisabetta; Poggesi, Corrado; Mugelli, Alessandro; Bueno‐Orovio, Alfonso; Olivotto, Iacopo; Sherrid, Mark V.

doi:10.1016/j.jacbts.2019.06.004

Cited by 45 publications

(65 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Technical advancement and availability of human tissue have fostered the collection of human-specific datasets, characterising different aspects of ventricular electro-mechanics. These include excitation-contraction coupling and calcium dynamics ( Lou et al., 2011 ; O’Hara et al., 2011 ; Coppini et al., 2013 ), as well as contractile ( Mulieri et al., 1992 ; Pieske et al., 1996 ; Rossman, 2004 ; Land et al., 2017 ; Coppini et al., 2019 ) and passive material properties ( Demer and Yin, 1983 ; Yin et al., 1987 ; Holzapfel and Ogden, 2009 ). Experimental data at different scales from subcellular to whole-organ dynamics have then been integrated into multiscale computer models of human physiology ( Augustin et al., 2016 ; Land et al., 2017 ; Prakosa et al., 2018 ; Levrero-Florencio et al., 2020 ).…”

Section: Introductionmentioning

confidence: 99%

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Margara

Wang

Levrero-Florencio

et al. 2021

Progress in Biophysics and Molecular Biology

Self Cite

View full text Add to dashboard Cite

Human-based computational modelling and simulation are powerful tools to accelerate the mechanistic understanding of cardiac patho-physiology, and to develop and evaluate therapeutic interventions. The aim of this study is to calibrate and evaluate human ventricular electro-mechanical models for investigations on the effect of the electro-mechanical coupling and pharmacological action on human ventricular electrophysiology, calcium dynamics, and active contraction. The most recent models of human ventricular electrophysiology, excitation-contraction coupling, and active contraction were integrated, and the coupled models were calibrated using human experimental data. Simulations were then conducted using the coupled models to quantify the effects of electro-mechanical coupling and drug exposure on electrophysiology and force generation in virtual human ventricular cardiomyocytes and tissue. The resulting calibrated human electro-mechanical models yielded active tension, action potential, and calcium transient metrics that are in agreement with experiments for endocardial, epicardial, and mid-myocardial human samples. Simulation results correctly predicted the inotropic response of different multichannel action reference compounds and demonstrated that the electro-mechanical coupling improves the robustness of repolarisation under drug exposure compared to electrophysiology-only models. They also generated additional evidence to explain the partial mismatch between in-silico and in-vitro experiments on drug-induced electrophysiology changes. The human calibrated and evaluated modelling and simulation framework constructed in this study opens new avenues for future investigations into the complex interplay between the electrical and mechanical cardiac substrates, its modulation by pharmacological action, and its translation to tissue and organ models of cardiac patho-physiology.

show abstract

Section: Introductionmentioning

confidence: 99%

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Margara

Wang

Levrero-Florencio

et al. 2021

Progress in Biophysics and Molecular Biology

Self Cite

View full text Add to dashboard Cite

show abstract

“…B : Rate dependency of simulated biomarkers: measurements of voltage- ( i,ii ) and Ca 2+ -related ( iii-vi ) biomarkers as a function of the BCL tested. Insets show representative and summary data for CaT characteristics measured in myocytes from patients with cardiac hypertrophy paced at a BCL of 2,000 ms unless noted otherwise (reproduced with permission from Fischer et al 2016, 28 Coppini et al 2013, 29 Ferrantini et al 2018, 30 and Coppini et al 2019 31 ).…”

Section: Resultsmentioning

confidence: 99%

“…Accounting for sex-specific TdP risk is critical for pro-arrhythmic risk evaluation during drug development and can contribute to safer therapeutics. 28 Coppini et al 2013, 29 Ferrantini et al 2018, 30 and Coppini et al 2019 31 ). Uncertainty of the feature weights is measured using LOO-CV (mean + SD).…”

Section: How Might This Change Clinical Pharmacology or Translationalmentioning

confidence: 99%

Sex-specific classification of drug-induced Torsade de Pointes susceptibility using cardiac simulations and machine learning

Iseppe¹,

Ni²,

Zhu³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a potential cardiac side effect of drugs. To assess TdP risk, safety regulatory guidelines require to quantify the effects of new therapeutic compounds on hERG channel block in vitro and QT interval prolongation in vivo. Unfortunately, these have proven to be poor predictors of torsadogenic risk, and are likely to have prevented safe compounds from reaching the clinical phase. While this has stimulated numerous efforts to define new paradigms for cardiac safety, none of the recently developed strategies accounts for patient conditions. In particular, despite being a well-established independent risk factor for TdP, female sex is vastly underrepresented in both basic research and clinical studies, and thus current TdP metrics are likely biased toward the male sex. Here, we apply statistical learning to synthetic data, generated by simulating drug effects on cardiac myocyte models capturing male and female electrophysiology, to develop new sex-specific classification frameworks for TdP risk. We show that 1) TdP classifiers require different features in females vs. males; 2) male-based classifiers perform more poorly when applied to female data; 3) female-based classifier performances are largely unaffected by acute effects of hormones (i.e., during various phases of the menstrual cycle). Notably, when predicting TdP risk of intermediate drugs on female simulated data, male-biased predictive models consistently underestimate TdP risk in women. Therefore, we conclude that pipelines for preclinical cardiotoxicity risk assessment should consider sex as a key variable to avoid potentially life-threatening consequences for the female population.

show abstract

“…Emerging technologies will allow in the future an increasingly precise understanding of the pathophysiology of CVDs and consequent therapeutic advancements. Arrhythmogenic Cardiomyopathy Pathogenic mechanism [8] BMCs Arrhythmogenic Cardiomyopathy Pathogenic mechanism [10] Heart failure - [11] CMs Heart failure Pathogenic mechanism [14] Hypertrophic Cardiomyopathy Drug discovery [16,17] C-MSCs Myocardial ischemia Pathogenic mechanism [24] Arrhythmogenic Cardiomyopathy Pathogenic mechanism/Involvement in disease pathogenesis [25] c-kit + C-MSCs Atrial Fibrillation Pathogenic mechanism [31] FAPs Arrhythmogenic Cardiomyopathy Involvement in disease pathogenesis [35] ECs Hypertension Pathogenic mechanism [39,43] Atherosclerosis Pathogenic mechanism/Involvement in disease pathogenesis [41] Pathogenic mechanism [42] VSMCs Hypertension Involvement in disease pathogenesis [48] Pathogenic mechanism [49] Atherosclerosis Differentiation phenotypes [46] Pathogenic mechanism/Drug discovery [47] AC 16 Hypertrophic Cardiomyopathy Drug discovery [51] Myocardial ischemia Pathogenic mechanism [52] hESC-CMs Hypertrophic Cardiomyopathy Pathogenic mechanism [64,65] hiPSC-CMs Atrial Fibrillation Pathogenic mechanism [76] Hypertrophic Cardiomyopathy Drug discovery [78] Long QT Syndrome Pathogenic mechanism/Drug discovery [79] hiPSC-ECs Hypertension Drug discovery [81] Moyamoya disease Pathogenic mechanism [82] hiPSC-SMCs Supravalvular aortic stenosis syndrome Pathogenic mechanism [83] Bicuspid Aortic Valve-related Thoracic Aortic Aneurysm Pathogenic mechanism/Drug discovery [84] VSMCs and CD14 + cells co-culture Atherosclerosis Pathogenic mechanism [88] [89] ECs and VSMCs co-culture Atherosclerosis Pathogenic mechanism [90]...…”

Section: Discussionmentioning

confidence: 99%

“…This molecule is a potent negative inotrope administered to decrease left ventricular outflow tract obstruction in subjects with obstructive HCM. Results showed that disopyramide inhibited ryanodine receptor (RyR), Na + , Ca ++ , and K + currents, decreased action potential duration and frequency of arrhythmic afterdepolarization, suggesting an additional antiarrhythmic action [ 16 , 17 ].…”

Section: Cardiovascular Cellsmentioning

confidence: 99%

Human Cell Modeling for Cardiovascular Diseases

Lippi

Stadiotti

Pompilio

et al. 2020

IJMS

View full text Add to dashboard Cite

The availability of appropriate and reliable in vitro cell models recapitulating human cardiovascular diseases has been the aim of numerous researchers, in order to retrace pathologic phenotypes, elucidate molecular mechanisms, and discover therapies using simple and reproducible techniques. In the past years, several human cell types have been utilized for these goals, including heterologous systems, cardiovascular and non-cardiovascular primary cells, and embryonic stem cells. The introduction of induced pluripotent stem cells and their differentiation potential brought new prospects for large-scale cardiovascular experiments, bypassing ethical concerns of embryonic stem cells and providing an advanced tool for disease modeling, diagnosis, and therapy. Each model has its advantages and disadvantages in terms of accessibility, maintenance, throughput, physiological relevance, recapitulation of the disease. A higher level of complexity in diseases modeling has been achieved with multicellular co-cultures. Furthermore, the important progresses reached by bioengineering during the last years, together with the opportunities given by pluripotent stem cells, have allowed the generation of increasingly advanced in vitro three-dimensional tissue-like constructs mimicking in vivo physiology. This review provides an overview of the main cell models used in cardiovascular research, highlighting the pros and cons of each, and describing examples of practical applications in disease modeling.

show abstract

Electrophysiological and Contractile Effects of Disopyramide in Patients With Obstructive Hypertrophic Cardiomyopathy

Cited by 45 publications

References 47 publications

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Sex-specific classification of drug-induced Torsade de Pointes susceptibility using cardiac simulations and machine learning

Human Cell Modeling for Cardiovascular Diseases

Contact Info

Product

Resources

About