Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2 ^+/−-deficient AF conditions by realistic in silico AF modeling.

Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2 ^+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.

Results: We compared the wild-type and PITX2 ^+/− deficiency in terms of the action potential duration (APD ₉₀), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2 ^+/−-deficient model exhibited a shorter APD ₉₀ ( p < 0.001), a lower Smax ( p < 0.001), mean DF ( p = 0.012), PS number ( p < 0.001), and a longer AF cycle length (AFCL, p = 0.011). Five V-AADs changed the electrophysiology in a dose-dependent manner. AAD-induced AFCL lengthening ( p < 0.001) and reductions in the CV ( p = 0.033), peak DF ( p < 0.001), and PS number ( p < 0.001) were more significant in PITX2 ^+/−-deficient than wild-type AF. PITX2 ^+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF ( p = 0.018).

Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.