Genome-wide association studies of atrial fibrillation: Finding meaning in the life of risk loci

AF, while the CTCF pathwaywas randomly distributed with low enrichGenome-wide association studies (GWAS) have identified potential pathogenic variants associated with several complex traits/phenotypes in multi-ethnic populations (Fig. 1A), which has helped redesign therapeutic strategies for those particular diseases [1]. For example, the association of genetic variants in PCSK9, identified in classical genetic studies and GWAS, with LDL cholesterol levels and coronary artery disease has led to new therapeutic options [1]. Similarly, in type-2 diabetes mellitus, GWAShave been employed to identify novel risk loci [2],while in rheumatoid arthritis, GWAS have detected the genetic overlap with other immunologic diseases, such as human primary immunodeficiency and hematological cancer, suggesting the potential benefit of repurposing drugs targeting those diseases [3]. GWAS have also been applied to study several electrocardiographic traits, including PR, RR and QT intervals, as well as complex arrhythmias, such as atrial fibrillation (AF) and sudden cardiac death [4]. AF is a progressive arrhythmia with multifactorial etiologies and pathogenesis, and a significant impact on morbidity and mortality [5]. Since rhythm control with catheter ablation or cardiac surgery can be performed in only a limited number of AF patients [6], antiarrhythmic drugs [7] along with anticoagulation for stroke prevention [8] remain the cornerstone of AF management. Several pathological mechanisms, including electrical remodeling, structural remodeling, autonomic imbalance and calcium-handling abnormalities, contribute to the initiation, maintenance and progression of AF (Fig. 1B) [5]. AF shows a significant heritability, highlighting a genetic predisposition, particularly in the case of lone AF (i.e., AF in the apparent absence of overt cardiovascular disease or atrial pathology). To date, GWAS have identified more than 100 susceptibility loci associated with AF and pathway analyses have revealed the association with cardiac developmental, structural and electrophysiological pathways [9,10], although the magnitude of their contribution and the precisemechanistic role remain largely unknown [11]. In the current issue of the Journal, Ebana et al. [12] employed metaanalysis gene-set enrichment of variant associations (MAGENTA), a computational tool that tests for enrichment of genetic associations in specific biological processes or gene sets, to identify the biological pathways linked to AF-associated loci previously identified in a GWAS of a