INTRODUCTION

Atrial fibrillation (AF) is the most common arrhythmia that requires treatment and is associated with increased morbidity and mortality.1 The prevalence of AF increases with age, and affects 1–2% of the general population, a proportion that is likely to increase in the next 50 years.2, 3 Cardiac risk factors such as hypertension and ischemic or other structural heart disease are known as risk factors for AF.1, 4, 5 However, a subgroup of patients diagnosed with AF is younger than 60 years of age and lacks these well-established risk factors. This condition is called ‘lone’ AF and accounts for 10–20% of the total number of patients with AF.6, 7

Brugada Syndrome (BrS) is characterized by ST-segment elevations in the right precordial leads and an increased risk of ventricular arrhythmias and sudden cardiac death.8

There is a significant overlap between genes associated with AF and BrS.8, 9 Accordingly, several rare variants in genes encoding cardiac sodium and potassium channels have been found both in patients with AF and in patients with BrS. This is the case for the variants in SCN5A (c. 647C>T (p.(Ser216Leu)), rs201002736,10, 11 c. 1127G>A (p.(Arg376His)), rs199473101,10, 12 c. 3157G>A (p.(Glu1053Lys)), rs137854617,10, 13 and c. 6010T>C (p.(Phe2004Leu)), rs4131111714, 15), SCN1Bb (c. 641G>A (p.(Arg214Gln)), rs6687687616, 17), SCN3B (c. 29T>C (p.(Leu10Pro)), rs12191828218, 19), MOG1 (c. 181G>T (p.(Glu61Xaa20, 21)), rs140704891, and KCNJ8 (c. 1265C>T (p.(Ser422Leu)), rs7255407122, 23). Furthermore, several studies have showed that the common AF-associated variant c. 1673A>G (p.(His558Arg)), rs1805124, in SCN5A may have a protective role against BrS in patients with other Brugada-associated SCN5A variants.11, 24, 25, 26 Since some mutations can result in different phenotypes,18, 19 the presence of additional single-nucleotide polymorphisms (SNPs) might have a disease-modifying effect. Of note, a recent genome-wide association study (GWAS) identified three loci (rs9388451; T>C, rs10428132; T>G, and rs11708996; G>C), to be associated with BrS. Patients carrying more than four risk alleles had an odds ratio (OR) of 21.5 for BrS, compared with patients carrying less than two risk alleles.27 All three GWAS-identified loci are presumed to affect the sodium current.

Since ∼20% of Brugada patients also develop supraventricular arrhythmias including AF,28 we hypothesized that SNPs previously associated with BrS in GWAS27 may also modify the risk of AF.

MATERIALS AND METHODS

Study population

A total of 358 patients with lone AF (ie, the absence of clinical or echocardiographic findings indicating other cardiovascular diseases, metabolic, or pulmonary diseases) and onset of disease before the age of 50 (ranging from 16 to 49 years of age) were included from Copenhagen, Denmark and from Oslo and Vestre Viken, Norway, as described previously.29 In addition, 299 ‘non-lone’ AF patients were included.

An ethnically matched control population was recruited from the same geographic area as the cases. This control population comprised (1) 208 healthy blood donors <48 years of age and free of cardiac diseases19 and (2) 533 men and women aged 55–75 years without history of AF or other cardiovascular diseases or stroke, despite a high prevalence of risk factors for AF30 (control group I). The latter control group was considered as highly relevant, because of their high AF resistance. To add power to our data, we added summarized data from the recently published BrS GWAS27 (control group II).

Written informed consent was obtained from all participants. The study conforms to the principles outlined in the Declaration of Helsinki, and was approved by the Scientific Ethics Committee of Copenhagen and Frederiksberg (Protocol reference number: H-KF-01313322) and the Regional Ethics Committee in Norway (Protocol reference number: 2009/2224-5).

SNP genotyping

Genotyping was performed as previously described.31 In brief, the DNA was extracted from whole blood that had been stored at −20 °C using the QIAamp DNA Blood Mini and Maxi kits (Qiagen, Hilden, Germany). SNP genotypes for rs9388451, rs10428132, and rs11708996 were determined using fluorescence-based real-time PCR (ABI PRISM 7900 Sequence Detection System; Applied Biosystems, Foster City, CA, USA) and pre-developed TaqMan assays (Applied Biosystems). An allelic discrimination run was performed allowing for discrimination between the allele compositions of each sample.

SNP genotypes for rs9388451, rs10428132, and rs11708996 have been submitted to ResearchGate, URL: https://www.researchgate.net/publication/259990810_Brugada_syndrome_risk_loci_seem_protective_against_atrial_fibrillation?ev=prf_pub.

Statistical analyses

The proportion of risk alleles (risk allele frequencies) was compared between AF cases and controls in two-by-two tables. Analyses were performed separately for the three investigated SNPs using either (1) in-house controls (control group I) or (2) both the in-house controls and summarized data on controls from the recently published BrS GWAS27 (control group I and control group II). The latter meta-analysis was done to add power to our analysis.

To assess the additive effect of the three SNPs, logistic regression models were performed including AF patients and control group I. Individuals were categorized into having 0–1, 2–3, or 4–6 risk alleles. The additive effect of carrying multiple BrS-risk alleles was assessed in four different models including (1) all three alleles, (2) the two loci that were statistically significant associated with AF, (3) all three alleles but without the non-lone AF patients, and finally (4) only the two statistically significant loci and without the non-lone AF patients. A two-tailed P-value of <0.05 was considered as statistically significant. Analyses were performed with the Stata 11.0 software package (StataCorp LP, College Station, TX, USA).

RESULTS

Clinical characteristics of the two AF groups and the control group are shown in Table 1. The lone and non-lone AF groups are combined in one case group throughout all analyses, unless otherwise stated.

Table 1 Clinical data of patient and control populations
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The results of the genotyping are summarized in Tables 2 and 3. One of three variants, rs10428132 in SCN10A, showed a statistically significant decreased risk of AF (OR=0.77, P=0.001) when comparing AF cases with control group I. Combining control groups I and II, both rs10428132 in SCN10A and rs11708996 intronic to SCN5A showed a statistically significant decreased risk of AF (rs10428132: OR=0.73, P=5.7 × 10−6, rs11708996: OR=0.80, P=0.02) (Table 3).

Table 2 Effect size of BrS-risk alleles in AF population vs control I
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Table 3 Effect size of BrS-risk alleles in AF population vs controls I+II
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In a pooled analysis of all three SNPs, we found that the risk of AF decreased consistently with increasing numbers of BrS-risk alleles (Figure 1a). Carrying four or more risk alleles was associated with an OR of 0.50 (95% CI: 0.33–0.76, P=0.001) for AF compared with individuals carrying less than two risk alleles. A subgroup analysis of the lone AF patient group showed a similar association (OR=0.41, 95% CI: 0.23–0.74, P=0.003) (Figure 1b). Similar pooled analyses were carried out for the two variants shown to be significantly associated with a decreased risk of AF. Again, AF risk decreased consistently with increasing numbers of BrS-risk alleles that an individual carried (Figure 1c and d). The distribution of risk alleles in patients and controls (control group I) is shown in Figure 2. The risk of AF decreases consistently with increasing numbers of BrS-risk alleles, indicated by the right-shifted patient population.

Figure 1
figure 1

ORs calculated according to the number of risk alleles in the in-house controls. Each dot represents the log(OR) value and each bar the 95% confidence interval (vertical). (a) Pooled analysis of all three loci in the lone AF and the non-lone AF patients vs the in-house controls. (b) Pooled analysis of all three loci in the lone AF patients vs the in-house controls. (c) Pooled analysis of the two loci significantly associated with AF (rs10428132 in SCN10A and rs11708996 intronic to SCN5A) in the lone AF and the non-lone AF patients vs the in-house controls. (d) Pooled analysis of the two loci significantly associated with AF in the lone AF population vs the in-house controls.

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Figure 2
figure 2

Distribution of risk alleles among individuals with AF (red bars) and among the in-house controls (blue bars).

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DISCUSSION

We investigated the prevalence of three SNPs recently shown to be associated with BrS, in a group of AF patients and in controls, and found that the additive effect of the three loci decreased the risk of AF in a dose-response manner (OR=0.50, 95% CI: 0.33–0.76, P=0.001 in the presence of ≥4 risk alleles vs ≤1).

The finding that the same group of SNPs known to be associated with BrS, with ORs of >20, at the same time possess a protective effect against AF is fascinating. The reported SNPs are either within or close to genes underlying or regulating the cardiac sodium current (INa). rs10428132 resides in the gene SCN10A encoding NaV1.8, rs11708996 is intronic to SCN5A encoding NaV1.5, and rs9388451 resides near the HEY2 locus. The loci at SCN10A and SCN5A are also associated with both PR interval and QRS duration.32, 33

From an evolutionary perspective, our results may suggest that these common variants known to increase the risk of a rare, but potentially lethal syndrome such as BrS seem to have a dualistic effect, protecting against a much more common disease such as AF.

Noteworthy, the SCN10A SNP, rs10428132, is in high linkage (0.98 r2) with rs6795970, also located in SCN10A. rs6795970 has, in a recent GWAS,34 been shown to protect against AF and atrial flutter (OR=0.85, P=8.45 × 10−4), along with arterial embolism and thrombosis (OR=0.69, P=3.20 × 10−3). This SNP leads to the substitution of valine to alanine at amino-acid position 1073 (c. 3218T>C (p.(Val1073Ala))) in the sodium channel isoform Nav1.8, resulting in this channel displaying both increased peak and late sodium current in functional studies.35 The NaV1.8 channel protein seems to be expressed in working myocardium and the cardiac conduction system,36 although it has also been found in intracardiac neurons.37 Its contribution to the total cardiac sodium current in the atria remains elusive. In addition, rs10428132 is in complete linkage with the PR-prolonging allele of rs6800541 which Pfeufer et al32 also noted to have a protective effect on AF risk. Finally, rs10428132 is in almost complete linkage with rs6801957 (r2=0.97), which has been reported to affect the binding of the TBX3 transcription factor and thereby the regulation of SCN5A/SCN10A expression.38

The majority of the cardiac sodium current is conducted by NaV1.5, and several studies including knock-out mouse models suggest a central role of SCN5A/NaV1.5 in the pathogenesis of AF. Heterozygote knock-out mice display compromised conduction velocity, impaired AV conduction, and QRS prolongation.39 An altered SCN5A/SCN10A expression could affect the conduction velocity and thereby the risk for BrS. Of note, both the SCN5A SNP rs11708996 and the SCN10A SNP rs10428132 have previously been associated with PR interval duration in a GWAS,32 supporting a protective role in AF. Pazoki et al40 replicated the association between the SCN5A SNP and PR duration, showing a trend for association between the rs11708996 C allele and a PR interval of ≥200 ms (OR=2.39, P=0.004).

rs9388451 is located in close proximity to the HEY2 gene, encoding a transcriptional repressor important in the development of the cardiovascular system.41, 42, 43, 44 Bezzina et al27 found homozygous HEY2 knock-out embryos to have increased NaV1.5 expression and a flattened transmural expression gradient of the channel in the cardiac ventricles. In HEY2+/− knock-out mice, the conduction velocity was increased in the right ventricle outflow tract (RVOT), and the action potential upstroke velocity was increased, indicating an increase in sodium channel peak current. This is in line with the characteristic ST-segment elevation in the right precordial leads of BrS ECGs, and proposes the RVOT as an origin of ventricular arrhythmias in BrS. Assuming that the variant also gives rise to an increased conduction velocity in the atria it may protect against other genetic variants, or age- and sport-induced decreases in conduction velocity caused by fibrosis, and thereby protect against AF. Furthermore, HEY2-deficient embryos displayed a change in the expression patterns of GJA5, NPPA, and TBX5.43, 45, 46 These genes have all previously been associated with AF.47, 48, 49, 50

Thus, several studies support our finding that BrS-associated genetic variants protect against AF. Further mechanistic studies might help decipher how cellular electrophysiological changes induced by each of these variants (separately and additively) result in protection against AF. The elucidation of the mechanism(s) might provide keys to a more detailed understanding of the pathophysiology of AF and BrS. From a clinical point of view, our result highlights the complexity of personalized medicine as the AF patients with BrS-risk alleles, known to increase the sodium peak current, on one hand might benefit from a sodium peak current blocker such as flecainide, but on the other hand, flecainide treatment might increase the risk of sudden cardiac death in these patients, since they are predisposed for BrS by the same BrS-risk alleles.

Study limitations

Our study population was highly selected and relatively small. As a consequence, the power to detect associations was reduced. The study only included cases of Scandinavian ancestry, and the generalizability of the results to other ethnicities might be limited.

CONCLUSIONS

We found the risk of AF to decrease consistently with increasing numbers of BrS-risk alleles carried, suggesting that these variants have a protective role against developing AF.