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Article Abstract
With the demonstration that AF is highly hereditable and strongly associated with over 100 genetic loci, one step towards personalized treatment of AF is the potential use of genetic testing to predict response to therapy. Although various clinical models have been developed to predict recurrence, none have shown a consistent ability to predict treatment outcomes. This highlights a need for additional patient information to increase predictive value. Here, we review the use of genetic data for prediction of AF recurrence after interventions such as ablation, cardioversion, or drug therapy. We explore the use of other downstream predictors, such as mRNA and protein, as other possible predictive tools. Finally, we assess how this genetic data can further our mechanistc understanding of AF pathogenesis and recurrence.
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| http://dx.doi.org/10.1016/j.pcad.2025.06.008 | DOI Listing |
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