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. Author manuscript; available in PMC: 2023 Apr 17.
Published in final edited form as: Curr Opin Cardiol. 2018 May;33(3):304–310. doi: 10.1097/HCO.0000000000000505

Genetics of Atrial Fibrillation – An Update

Hannah M Campbell 1,2,3, Xander HT Wehrens 1,2,4,5,6
PMCID: PMC10108376  NIHMSID: NIHMS1890946  PMID: 29461262

Abstract

Purpose of Review:

Atrial fibrillation is a common cardiac arrhythmia with a high morbidity and mortality affecting 34 million worldwide. Current therapies are inadequate and often fail to directly address molecular mechanisms of the disease. In this review, we will provide an overview of recent advances in our understanding of the genetic underpinnings of atrial fibrillation.

Recent Findings:

Large-scale genetic association studies have more than doubled the number of genetic loci associated with atrial fibrillation during the last year. Studies examining how genes at or near these loci can affect the pathogenesis of atrial fibrillation are ongoing in both cellular, animal, and computational models. Additionally, several recent clinical studies have also demonstrated that variants at these loci can aid in risk stratification of patients.

Summary:

There are now over 30 genetic loci associated with atrial fibrillation. A better understanding of how these loci relate to disease pathogenesis may provide insight into novel therapeutic targets and ultimately lead to improved clinical care.

Keywords: Arrhythmia, atrial fibrillation, electrophysiology, genome-wide association studies, genomics

Introduction

Atrial Fibrillation (AF) is the most common cardiac arrhythmia affecting 34 million worldwide [1]. The disease has a high morbidity and mortality, with an increased risk of both cardio-embolic stroke and heart failure. Current pharmaceutical and procedural treatment methods remain inadequate and fail to target disease-specific mechanisms. Atrial fibrillation has been shown to have a heritable component, as a history of atrial fibrillation in a parent increases the four-year risk of developing AF by two fold [2]. Common and rare variants associated with AF have been identified near or in genes encoding ion channels, transcription factors, as well as structural proteins [3]. A better understanding of the genetic variation contributing to AF may provide novel therapeutic targets as well as play a role in risk-stratification and management of patients. The aim of this review is to provide a summary of the current state of the field of genetics in atrial fibrillation, with a particular emphasis on discoveries within the last year in regard to both familial and common AF. We will also include our vision on the future of the field, including clinical applications.

Genetics of Familial AF

In familial AF, inheritance can occur in a Mendelian fashion with a phenotype of early-onset AF in the absence of other forms of acquired heart disease. Familial AF is usually caused by rare variants in coding regions of ion channels genes, although variants in other genes have been implicated [4]. A list of genes in which rare variants have been identified in AF are summarized in Table 1 [5].

Table 1.

Genes with rare variants implicated in AF

Gene Protein/Function
ABCC9 ATP binding cassette subfamily C member 9; ion channel
C9orf3 Chromosome 9 open reading frame 3; aminopeptidase-O
CAV1 Caveolin1; plasma membrane scaffold
GATA4 GATA binding protein 4; transcription factor: cardiac morphogenesis
GATA5 GATA binding protein 5; transcription factor: cardiac morphogenesis
GATA6 GATA binding protein 6; transcription factor: cardiac morphogenesis
GJA1 Gap junction alpha-1 protein; gap junctions
GJA5 Gap junction alpha-5 protein; gap junctions
HCN4 Potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 4; ion channel
JPH2 Junctophilin-2; transverse-tubule and junctional membrane complex regulator
KCNA5 Potassium voltage-gated channel, shaker-related subfamily, member 5; ion channel
KCND3 Potassium voltage-gated channel subfamily D member 3; ion channel
KCNE1 Potassium voltage-gated channel subfamily E regulatory subunit 1; ion channel
KCNE2 Potassium voltage-gated channel subfamily E regulatory subunit 2; ion channel
KCNE5 Potassium voltage-gated channel subfamily E regulatory subunit 5; ion channel
KCNH2 Potassium voltage-gated channel subfamily H member 2; ion channel
KCNJ2 Potassium voltage-gated channel subfamily J member 2; ion channel
KCNJ8 Potassium voltage-gated channel subfamily D member 3; ion channel
KCNN3 Potassium calcium-activated channel subfamily N member 3; ion channel
KCNQ1 Potassium voltage-gated channel subfamily Q member 1; ion channel
MYH6 Myosin heavy chain 6; sarcomere structure
MYL4 Myosin light chain 4; sarcomere structure
NKX2–5 NK2 homeobox 5; transcription factor: cardiac morphogenesis
NPPA Natriuretic peptide precursor A; blood-volume control signal
NUP155 Nucleoporin 155; nucleoporin structure
PITX2 Paired like homeodomain 2; transcription factor: cardiac morphogenesis
RyR2 Ryanodine receptor type-2; ion channel
SCN10A Sodium voltage-gated channel alpha subunit 10; ion channel
SCN1B Sodium voltage-gated channel beta subunit 1; ion channel
SCN2B Sodium voltage-gated channel beta subunit 2; ion channel
SCN3B Sodium voltage-gated channel beta subunit 3; ion channel
SCN4B Sodium voltage-gated channel beta subunit 4; ion channel
SCN5A Sodium voltage-gated alpha subunit 5; ion channel
SYNE2 Spectin repeat-containing nuclear envelope protein 2; nuclear pore
ZFHX3 Zinc finger homeobox 3; transcription factor: cardiac morphogenesis
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Variant Discovery in Familial AF

The first gene to be associated with AF was identified in 2003 through linkage studies followed by sequencing which revealed a coding variant in KCNQ1 [6]. With recent advances in whole exome and genome sequencing, the number of genes associated with familial AF has continued to grow.

Recently, a rare frameshift deletion in MYL4, a protein important for sarcomere structure, was identified as a cause of familial AF [7*]. This variant was associated with a fully-penetrant atrial myopathy with early-onset atrial fibrillation. This discovery highlights the need to examine the role of structural proteins in the pathogenesis of atrial fibrillation secondary to atrial myopathy. Other recently discovered variants associated with AF include gain-of-function mutations in the GATA6 N-terminal and C-terminal domains [8*]. Previous variants in GATA6 associated with AF have been loss-of-function mutations. Such seems to be a common theme in monogenic AF that gain-of-function and loss-of-function mutations in the same gene can lead to disease pathogenesis.

Typically, rare variants in familial AF are associated with lone AF, defined as AF in the absence of other underlying cardiovascular conditions. However, this is not always the case as rare germline variants were also identified in patients with AF with mitral valve regurgitation, many in genes containing potassium channels [9**]. This would suggest that certain rare variants may not be penetrant independent of interaction with other factors.

Rare Variant Validation

Because of the complex nature of the pathogenesis of common AF, with gross structural, metabolic, and inflammatory conditions contributing to its pathogenesis, cell-based assays are often not ideal for mechanistic studies. However, in the case of familial AF where a single mutation is sufficient for disease pathogenesis, the study of isolated cardiomyocytes may offer important information in regard to disease mechanisms. Human induced pluripotent stem cells (hiPSCs) offer a unique opportunity for studying human disease mutations when combined with the CRISPR/Cas9 system and the use of retinoic acid for the differentiation hiPSCs to atrial-like cardiomyocytes [10]. Such an approach may provide a promising avenue for the study of role of genetic variants in the pathogenesis of AF. A recent study using hiPSCs was able to successfully demonstrate the effects of KCNA5 knock-out in atrial-like cardiomyocytes [11*]. The cells recapitulated the disease phenotype with increased action potential duration (APD) and frequency of early after-depolarizations (EADs). Additionally, an hiPSC cell line of a human mutation associated with familial AF has also been successfully generated [12*].

Animal models, including zebrafish and mice, have also been used to study these variants, although to a lesser extent. Caution needs to be taken when examining animal models, as the phenotype may not recapitulate the human disease phenotype. Recently, a rat knock-out and knock-in models have been used to confirm that MYH4 loss-of-function causes an atrial myopathy, although the knock-in mice did not have any episodes of spontaneous AF, unlike the human patients with the same mutation [13]. However, these investigators did not perform atrial-pacing studies or other alternative experiments to test for arrhythmia inducibility under stress conditions.

In silico methods may also provide useful avenues for variant study due to the impracticality of generating a cell-line for each novel variant, with some only present in a single family or individual. A recent study used three separate 3-D atrial computer models to predict the effect of six rare familial KCNA5 variants on atrial electrophysiology [14*]. Gain-of-function mutations were shown to decrease APD, leading to increased re-entry and initiation, while loss-of-function mutations showed an increased probability of heterogeneously distributed EADs. Another study was also successful in using a virtual atrial model to examine the mechanisms by which patient-specific KCNJ2 mutations drive arrhythmogenicity [15]. Although these models have several limitations, they may provide a tool for more high-throughput screening of disease mutations, with potential applications for the clinical management of patients.

Genetics of Common AF

Most atrial fibrillation cases fall into the category of common AF, with a variety of risk factors such as hypertension, diabetes, age, and valvular heart disease contributing to its pathogenesis. There is also a growing appreciation for how common genetic variants contribute to AF pathogenesis independent of other risk factors.

Variant Discovery in Common AF

Whole exome sequencing of patients with common AF has failed to show common or rare variation in genes implicated in familial AF [16*]. Instead, most variants associated with common AF have been identified by Genome Wide Association Studies (GWAS) and fall in non-coding regions of the genome. Great progress has been made in the discovery of these AF genetic loci, as summarized in Table 2. After one recent study performed by the AFGen Consortium, the number of genetic disease loci associated with atrial fibrillation nearly doubled with the discovery of 12 novel loci [17**]. This feat was accomplished by performing meta-analyses using data from 31 GWAS and 17 Exome-Wide Association Studies. Many of the identified loci were located proximal to genes encoding cardiac ion channels, sarcomere proteins, and transcription factors important for cardiac morphogenesis. Additionally, one Japanese specific rare variant was found in SH3PXD2A, which encodes a protein important for neural crest migration. This finding was replicated a few months later in a GWAS study performed in a Japanese population by Low et. al. This study also identified a significantly associated variant in PPFIA4, a gene encoding a tyrosine phosphatase important for axon guidance [18**].

Table 2.

Genetic Disease Loci Associated with Common AF

Nearest Gene(s) Protein/Function
ANXA4–GMCL1 Unknown-intergenic region
ASAH1–PCM1 Unknown-intergenic region
C9orf3 Chromosome 9 open reading frame 3; aminopeptidase
CAND2 Cullin associated and neddylation dissociated; transcription factor: cardiac morphogenesis
CEP68 Centrosomal protein 68; cytoskeleton
CUX2 Cut like homeobox 2; transcription factor: cardiac morphogenesis
GJA1 Gap junction alpha-1 protein; gap junctions
HAND2 Heart and neural crest derivatives expressed 2; transcription factor: cardiac morphogenesis
HCN4 Potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 4; ion channel
KCND3 Potassium voltage-gated channel subfamily D member 3; ion channel
KCNJ5 Potassium voltage-gated channel subfamily J member 5; ion channel
KCNN2 Potassium calcium-activated channel subfamily N member 2; ion channel
KCNN3 Small conductance calcium-activated potassium (SK) channel 3; ion channel
KLHL3–WNT8A–FAM13B Unknown-intergenic region
LINC01142-METTL11B Unknown-intergenic region
METTL11B–KIFAP3 Unknown-intergenic region
NEBL Nebulette; sarcomere structure
NEURL1 Neuralized E3 ubiquitin protein ligase 1; ubiquitin ligase
PITX2 Paired like homeodomain 2; transcription factor:cardiac morphogenesis
PLEC Plectin; cytoskeleton
PPF1A4 Liprin-beta-1; protein tyrosine-phosphatase: axon guidance
PPRX1 Paired related homoeobox 1; transcription factor: cardiac morphogenesis
SCN10A Sodium voltage-gated channel alpha subunit 10; ion channel
SH3PXD2A SH3 and PX domain-containing protein 2A; transcription factor: neural crest migration
SLC1A4-CEP68 Unknown-intergenic region
SLC35F1–PLN Unknown-intergenic region
SOX5 SRY (sex determining region Y)-Box 5; transcription factor: cardiac morphogenesis
SYNE2 Spectin repeat-containing nuclear envelope Protein 2; nuclear pore
SYNPO2L Synaptopodin 2-like; cytoskeleton
TBX5 T-box transcription factor 5; transcription factor: cardiac morphogenesis
TTN–TTN-AS1 Unknown-intergenic region
ZFHX3 Zinc finger homeobox 3; transcription factor: cardiac morphogenesis
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Low et. al. also variants also identified three other novel AF disease loci, with the most significant being HAND2, encoding a protein import for cardiac morphogenesis [18**]. Five of the six genetic loci were unique to the Japanese population vs. European cohorts, suggesting that genetic background differences among ethnicities may have an impact on AF pathogenesis. Additionally, another GWAS study performed in a Korean population also found SNPs near HAND2 and PPFIA4 to be associated with AF, further validating the previous studies [19].

Finally, another GWAS study performed in an Icelandic population identified two novel variants, one of these in the coding region of PLEC, encoding Plectin, a cytoskeletal protein [20*]. Although this variant is rare in other populations, it will be interesting to study whether regulatory changes in PLEC as well as other structural proteins contribute to initiation and/or remodeling in atrial fibrillation.

The interaction of genetic variants with other AF risk factors

In another hallmark study performed this past year, the AFGen Consortium examined whether an interaction existed between common variants associated with AF and other risk factors including BMI, age, and gender [21**]. A significant interaction with age was observed with SNP rs6817105 at the 4q25 genetic risk loci close to the gene encoding Pitx2. The odds ratio for AF with the risk allele was 1.78 in patients under 65 and 1.40 in patients older than 65. One likely reason that associations with other known AF risk factors were not found to be statistically significant likely lies in the lack of power in these studies. Upon performing power analysis, it was found that an AF cohort of over 100,0000 individuals would be required to obtain 80% power to detect an Odds-ratio of 1.5 for gender and 1.5 for an SNP. Thus, it may not be possible to obtain statistical significance without much larger sample sizes. Such may only be possible when whole genome sequencing and data sharing become common in clinical practice.

Common AF Variant Validation

As more genetic association studies are performed, there is little doubt that more loci will be identified. What is needed to accompany this increasing list of loci is validation and information on the effects of these variants on atrial myocyte function and how such variants may be able to contribute to the pathogenesis of AF. Many studies have been performed examining the 4q25 locus, close to PITX2, as this is the most significantly associated locus across multiple studies [17**]. Experimental evidence supports that disease variants at this locus can indeed affect expression levels of PITX2 leading to downstream changes in protein expression [22, 23*, 24*]. Future studies will likely continue to focus on the mechanisms of PITX2 loss in disease pathogenesis, using animal models and hiPSC lines of PITX2 deficiency. Of note, a PITX2 deficient hiPSC line has been successfully generated that can be used to study general effects of PITX2 on atrial cardiomyocyte gene expression changes[12*, 25*].

Studies are still ongoing to verify causality of other AF associated variants. The Ellinor group was successful in showing that an associated variant in a non-coding region of the locus at 1q24 alters PPRX1 expression levels [26*]. Similar studies will need to be performed for the other loci followed by work to determine how such gene regulation changes may lead to AF pathogenesis further downstream. It will also be important to examine whether any of these variants affect miRNAs or epigenetic regulation, as evidence continues to increase for the significance of these regulatory mechanisms in AF [27–29].

A role for genetics in the clinical management of AF?

Unlike arrhythmia disorders such as long QT syndrome and CPVT where knowledge of the genotype may influence clinical management, genetic testing is not currently recommended for patients with atrial fibrillation. However, recent studies examining the predictive power of common and rare variants in atrial fibrillation may change this in the near future as genetic information is translated into improving clinical care of patients with AF.

Genetics guiding pharmaceutical therapy

Although there have been pre-clinical studies examining how certain genotypes associated with AF in the context of short QT syndrome [30*, 31] respond to targeted medications, with the large variety of genetic loci associated with AF, genotype specific treatments may not be feasible. However, it is possible that treatments developed using monogenic disease models may be effective in the general treatment of AF. Additionally, a better understanding of the mechanism by which the identified disease loci contribute to AF pathogenesis may yield novel drug targets that specifically address some of the electrophysiological or structural changes that occur in disease pathogenesis. Currently, none of the potassium channel-blocking drugs currently used in clinic target any of the potassium channels that have variants associated with AF pathogenesis. The development of drugs tailored to channels with AF associated variants is one example of how genetics may guide the development of novel therapies.

Predicting treatment efficacy using AF genetics

Several studies have been performed examining whether genetic variants can predict recurrence of AF after ablation procedures One of these recent studies reported that examining patients for rare variants failed to predict recurrence [32]; however, the sample size of this study was limited. Most other studies examining the burden of common and rare variants have shown as association with disease-associated genetic variants and recurrence of AF [33–36, 37]. An interesting finding from one of these studies found through pathway analysis that alterations in extracellular matrix-receptor and calcium signaling genes were both associated with left atrial diameter (a marker of atrial remodeling) and recurrence of AF after ablation [37**]. The findings of these studies will need to be validated in larger cohorts. Additionally, these studies have been limited to single ethnic groups and may not be generalizable to the entire population. Future studies examining larger and more diverse populations will be necessary.

Genetic risk scores to predict AF and stroke

Current clinical risk scores in atrial fibrillation that predict development of AF and/or cardio-embolic stroke rely on risk factors such as age, blood pressure, presence of diabetes, and gender. Work to see whether genetics may serve as an additional biomarker for AF risk is ongoing. Several recent studies have shown that a genetic risk score calculated based on the number of disease associated variants can be used to help predict risk of AF development and/or stroke, although only to a limited extent after factoring in other risk factors [38*]. In a Japanese population, a weighted genetic risk score, taking into account prevalence of each variant, was able to identify patients with a 7-fold increased risk of AF[18**] This finding still needs to be independently validated. It was also found in another study in a Japanese population that the burden of AF associated variants had an impact on the age of onset of disease [39*]. Not only is there evidence that variants from multiple loci can lead to higher incidence of AF, but there is also evidence of multiple variants in the TBX5 locus having a synergistic effect in increasing susceptibility to AF [40*]. However, as of yet, significant gene-gene interactions between AF associated loci have not been identified[41].

Additionally, it was recently found that a genetic screen for AF associated variants may be useful in elucidating whether a patient who has suffered a stroke has potentially undiagnosed AF [42*]. As of this date, genetic testing for AF patients is not currently recommended. However, the use of genetics to predict risk of AF may not be too far distant as methods for genetic risk score generation continue to be improved upon.

Conclusion

Tremendous progress in the field of genetics in atrial fibrillation has been made this past year with the number of identified genetic loci more than doubled. However, the rate at which we are able to determine causality and mechanisms of these variants is far behind our rate of discovery. Future work will need to focus on validation of these variants and how to ultimately translate these findings into the clinical management of patients with atrial fibrillation.

Key Points.

  • Over 30 genetic loci have been identified as significantly associated with AF.

  • There is a need for verification of causality and studies to understand the mechanisms by which these genetic loci increase arrhythmia susceptibility.

  • Mechanistic studies of these variants may provide novel therapeutic targets for the treatment of patients.

  • AF genetics may serve as useful biomarkers with utility in risk stratification and treatment of patients.

Acknowledgements

American Heart Association (17CPRE33660059 to HMC; EIA14560061 to XHTW), National Institute of Health/National Heart Lung Blood Institute (HL089598, HL117641, HL091947, HL118761, HL134824 to XHTW).

Funding Sources:

American Heart Association, National Institute of Health.

Footnotes

Conflict of interest

XHTW is a founding partner of Elex Biotech, a start-up company that developed drug molecules that target ryanodine receptors for the treatment of cardiac arrhythmia disorders.

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