Atrial resting membrane potential confers sodium current sensitivity to propafenone, flecainide and dronedarone

Holmes, Andrew P.; Saxena, Priyanka; Kabir, S. Nashitha; O’Shea, Christopher; Kuhlmann, Susanne D.; Gupta, Suranjana; Fobian, Dannie; Apicella, Clara; O’Reilly, Molly; Syeda, Fahima; Reyat, Jasmeet S.; Smith, Godfrey L.; Workman, Antony J.; Pavlović, Davor; Fabritz, Larissa; Kirchhof, Paulus

doi:10.1016/j.hrthm.2021.03.016

Cited by 16 publications

(13 citation statements)

References 31 publications

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“…Further function analysis showed that cardiomyocytes of the left atria displayed a depolarized resting membrane potential and a smaller action potential amplitude than those from control mice [ 57 ]. However, an increase [ 60 ] and no change [ 56 , 62 ] in Scn5a expression were also observed in other studies. In addition to I Na and I K1 , remodelled I Ks and I CaL were associated with PITX2c overexpression in right atrial myocytes [ 59 ].…”

Section: The Role Of Pitx2 In Cardiogenesis and Arrhythmogenesissupporting

confidence: 53%

Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models

Bai

Zhu

et al. 2021

IJMS

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Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including genetic predispositions to AF development. Genome-wide association studies have identified a number of genetic variants in association with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research is insufficient for understanding the functional impacts of PITX2 variants on AF. Linking PITX2 properties to ion channels, cells, tissues, atriums and the whole heart, computational models provide a supplementary tool for achieving a quantitative understanding of the functional role of PITX2 in remodelling atrial structure and function to predispose to AF. It is hoped that computational approaches incorporating all we know about PITX2-related structural and electrical remodelling would provide better understanding into its proarrhythmic effects leading to development of improved anti-AF therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives.

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Section: The Role Of Pitx2 In Cardiogenesis and Arrhythmogenesissupporting

confidence: 53%

Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models

Bai

Zhu

et al. 2021

IJMS

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“…Further function analysis showed that cardiomyocytes of the left atria displayed a depolarized resting membrane potential and a smaller action potential amplitude than those from control mice [20]. However, an increase [21] and no change [79,83] in Scn5a expression were also observed in other studies. In addition to INa and IK1, remodelled IKs and ICaL were associated with PITX2c overexpression in right atrial myocytes [23].…”

Section: Membrane Effector Genes Regulated By Pitx2mentioning

confidence: 51%

Understanding PITX2-dependent Atrial Fibrillation Mechanisms through Computational Models

Bai¹,

Lu²,

Zhu³

et al. 2021

Preprint

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Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including a genetic predisposition to develop AF. Genome-wide association studies have identified genetic variants associated with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene coding for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research on PITX2-dependent AF is not sufficient for understanding atrial functional proprieties. Linking PITX2 to ion channels, cells, tissues, atria and the whole heart, computational models are necessary for achieving a quantitative understanding of atrial structure and function in PITX2-dependent AF. Computational approaches are used to capture all that we know about PITX2-dependent AF and to develop improved therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives.

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“…Bai et al and Syeda et al reported that the class I AAD flecainide was more effective in suppressing atrial arrhythmias in PITX2 v ariants than in the wild type ( 13 , 17 ). In contrast, Holmes et al reported that the class III AAD dronedarone offered a more prominent anti-AF effect than flecainide or propafenone in a murine PITX2 +/− heart model than in the wild type ( 10 ). In this study, we confirmed that class I AAD was more effective in PITX2 variants, consistent with the previous studies by Bai or Syeda ( 13 , 17 ).…”

Section: Discussionmentioning

confidence: 93%

Ablation and antiarrhythmic drug effects on PITX2+/− deficient atrial fibrillation: A computational modeling study

Jin

Hwang

Lim

et al. 2022

Front. Cardiovasc. Med.

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IntroductionAtrial fibrillation (AF) is a heritable disease, and the paired-like homeodomain transcription factor 2 (PITX2) gene is highly associated with AF. We explored the differences in the circumferential pulmonary vein isolation (CPVI), which is the cornerstone procedure for AF catheter ablation, additional high dominant frequency (DF) site ablation, and antiarrhythmic drug (AAD) effects according to the patient genotype (wild-type and PITX2+/− deficient) using computational modeling.MethodsWe included 25 patients with AF (68% men, 59.8 ± 9.8 years of age, 32% paroxysmal AF) who underwent AF catheter ablation to develop a realistic computational AF model. The ion currents for baseline AF and the amiodarone, dronedarone, and flecainide AADs according to the patient genotype (wild type and PITX2+/− deficient) were defined by relevant publications. We tested the virtual CPVI (V-CPVI) with and without DF ablation (±DFA) and three virtual AADs (V-AADs, amiodarone, dronedarone, and flecainide) and evaluated the AF defragmentation rates (AF termination or changes to regular atrial tachycardia (AT), DF, and maximal slope of the action potential duration restitution curves (Smax), which indicates the vulnerability of wave-breaks.ResultsAt the baseline AF, mean DF (p = 0.003), and Smax (p < 0.001) were significantly lower in PITX2+/− deficient patients than wild-type patients. In the overall AF episodes, V-CPVI (±DFA) resulted in a higher AF defragmentation relative to V-AADs (65 vs. 42%, p < 0.001) without changing the DF or Smax. Although a PITX2+/− deficiency did not affect the AF defragmentation rate after the V-CPVI (±DFA), V-AADs had a higher AF defragmentation rate (p = 0.014), lower DF (p < 0.001), and lower Smax (p = 0.001) in PITX2+/− deficient AF than in wild-type patients. In the clinical setting, the PITX2+/− genetic risk score did not affect the AF ablation rhythm outcome (Log-rank p = 0.273).ConclusionConsistent with previous clinical studies, the V-CPVI had effective anti-AF effects regardless of the PITX2 genotype, whereas V-AADs exhibited more significant defragmentation or wave-dynamic change in the PITX2+/− deficient patients.

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Atrial resting membrane potential confers sodium current sensitivity to propafenone, flecainide and dronedarone

Cited by 16 publications

References 31 publications

Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models

Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models

Understanding PITX2-dependent Atrial Fibrillation Mechanisms through Computational Models

Ablation and antiarrhythmic drug effects on PITX2+/− deficient atrial fibrillation: A computational modeling study

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