Re-evaluating the efficacy of β-adrenergic agonists and antagonists in long QT-3 syndrome through computational modelling
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Journal title
Cardiovascular ResearchDate Published
2009-03-05Publication Volume
82Publication Issue
3Publication Begin page
439Publication End page
447
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Aims: Long QT syndrome (LQTS) is a heterogeneous collection of inherited cardiac ion channelopathies characterized by a prolonged electrocardiogram QT interval and increased risk of sudden cardiac death. Beta-adrenergic blockers are the mainstay of treatment for LQTS. While their efficacy has been demonstrated in LQTS patients harbouring potassium channel mutations, studies of beta-blockers in subtype 3 (LQT3), which is caused by sodium channel mutations, have produced ambiguous results. In this modelling study, we explore the effects of beta-adrenergic drugs on the LQT3 phenotype. Methods and results: In order to investigate the effects of beta-adrenergic activity and to identify sources of ambiguity in earlier studies, we developed a computational model incorporating the effects of beta-agonists and beta-blockers into an LQT3 mutant guinea pig ventricular myocyte model. Beta-activation suppressed two arrhythmogenic phenomena, transmural dispersion of repolarization and early after depolarizations, in a dose-dependent manner. However, the ability of beta-activation to prevent cardiac conduction block was pacing-rate-dependent. Low-dose beta-blockade by propranolol reversed the beneficial effects of beta-activation, while high dose (which has off-target sodium channel effects) decreased arrhythmia susceptibility. Conclusion: These results demonstrate that beta-activation may be protective in LQT3 and help to reconcile seemingly conflicting results from different experimental models. They also highlight the need for well-controlled clinical investigations re-evaluating the use of beta-blockers in LQT3 patients.Citation
Ahrens-Nicklas RC, Clancy CE, Christini DJ. Re-evaluating the efficacy of beta-adrenergic agonists and antagonists in long QT-3 syndrome through computational modelling. Cardiovasc Res. 2009 Jun 1;82(3):439-47. doi: 10.1093/cvr/cvp083. Epub 2009 Mar 5. PMID: 19264765; PMCID: PMC2682617.DOI
10.1093/cvr/cvp083ae974a485f413a2113503eed53cd6c53
10.1093/cvr/cvp083
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