Abstract

Atrial fibrillation (AF) is a common arrhythmia with a well-recognized inherited component. Until now, AF genetic studies mainly focused on the genes involved in electrical remodelling, rather than left atrial muscle remodelling. To identify rare variants involved in atrial myopathy using mutational screening. A high-throughput next-generation sequencing (NGS) workflow was developed based on a custom AmpliSeq™ panel of 55 genes potentially involved in atrial myopathy. This workflow was applied to a cohort of 94 patients with AF, 66 with atrial dilatation and 28 without. Patients with variants in the selected genes underwent further screening for pathogenic mutations in prevalent arrhythmia-causing genes. Bioinformatic analyses used a pipeline based on NextGENe ® software and in silico tools for variant interpretation. The AmpliSeq™ custom-made panel efficiently explored 96.58% of the targeted sequences. Based on in silico analysis, 11 potentially pathogenic missense variants were identified that were not previously associated with AF. These variants were located in genes involved in atrial tissue structural remodelling. Three patients were also carriers of potential variants in prevalent arrhythmia-causing genes, usually associated with AF. Most of the variants were found in patients with atrial dilatation ( n = 9, 82%). This NGS approach was a sensitive and specific method that identified 11 potentially pathogenic variants, which are likely to play roles in the predisposition to left atrial myopathy. Functional studies are needed to confirm their pathogenicity.

Highlights

  • Atrial fibrillation (AF) is the most frequent arrhythmia, affecting 30 million individuals worldwide [1]

  • Paroxysmal AF was the most common type and 80.8% of patients with AF presented with left atrial dilatation

  • Nine variants were found in patients with AF and left atrial dilatation and two in patients without atrial myopathy

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Summary

Introduction

Atrial fibrillation (AF) is the most frequent arrhythmia, affecting 30 million individuals worldwide [1]. Ion-channel, neural, and structural remodeling of the LA muscle has been widely documented [4] and numerous studies have found a genetic predisposition and a highly heritable component associated with AF risk [5]. In the past 20 years, the genetic basis for AF was established through studies evaluating familial AF [6, 7], linkage [8, 9], candidate genes [10, 11], and genome-wide association studies (GWAS) [12,13,14] that reported common and rare variants in genes encoding ion-channels, gap junction proteins, and signaling molecules. Next-generation sequencing (NGS) technologies have advanced in terms of sensibility, specificity, practicability, and the cost to rapidly screen large numbers of genes. Sequencing candidate genes might be the best approach to reveal variations in AF-associated genes [16,17,18]

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