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Atrial fibrillation (AF) management has significantly improved during the career of professor Crijns. Research was implemented into guidelines and clinical practice. However, despite advances in AF management, large differences between individual treatment responses still exist and the mechanisms underlying initiation and perpetuation of AF are not completely understood. International collaborations have revealed the genetic contribution to AF and steps towards improving AF management are being made. In this short review, the most important paradigms shifts in the field of AF genetics are recognized and the future role of genetics in personalized management of AF is discussed. [ABSTRACT FROM AUTHOR]

Aims: Atrial fibrillation (AF) may present variously in time, and AF may progress from self-terminating to non-self-terminating AF, and is associated with impaired prognosis. However, predictors of AF types are largely unexplored. We investigate the clinical, biomarker, and genetic predictors of development of specific types of AF in a community-based cohort.Methods: We included 8042 individuals (319 with incident AF) of the PREVEND study. Types of AF were compared, and multivariate multinomial regression analysis determined associations with specific types of AF.Results: Mean age was 48.5 ± 12.4 years and 50% were men. The types of incident AF were ascertained based on electrocardiograms; 103(32%) were classified as AF without 2-year recurrence, 158(50%) as self-terminating AF, and 58(18%) as non-self-terminating AF. With multivariate multinomial logistic regression analysis, advancing age (P< 0.001 for all three types) was associated with all AF types, male sex was associated with AF without 2-year recurrence and self-terminating AF (P= 0.031 and P= 0.008, respectively). Increasing body mass index and MR-proANP were associated with both self-terminating (P= 0.009 and P< 0.001) and non-self-terminating AF (P= 0.003 and P< 0.001). The only predictor associated with solely self-terminating AF is prescribed anti-hypertensive treatment (P= 0.019). The following predictors were associated with non-self-terminating AF; lower heart rate (P= 0.018), lipid-lowering treatment prescribed (P= 0.009), and eGFR <60 mL/min/1.73 m2 (P= 0.006). Three known AF-genetic variants (rs6666258, rs6817105, and rs10821415) were associated with self-terminating AF.Conclusions: We found clinical, biomarker and genetic predictors of specific types of incident AF in a community-based cohort. The genetic background seems to play a more important role than modifiable risk factors in self-terminating AF. [ABSTRACT FROM AUTHOR]