Korean Atrial Fibrillation (AF) Network: Genetic Variants for AF Do Not Predict Ablation Success
Genomewide association studies have identified several loci associated with atrial fibrillation (
Methods and Results
We determined the association between 4
Atrial fibrillation (AF) is the most commonly found sustained arrhythmia, with a lifetime risk of 25%.1 Risk factors include advancing age, hypertension, structural heart disease, and congestive heart failure, yet a subset of younger persons develop AF in the absence of established risk factors. Genetic factors play an important role in the pathogenesis of AF. Parental history of AF increases risk of AF by 1.4 to 1.9 times.2, 3 Familial cases of AF underscore a genetic basis for disease,4 and research has implicated mutations and polymorphisms in the development of AF.5
Recently, several common genetic variants have been shown to be associated with AF in genomewide association studies performed in populations of European ancestry6, 7, 8, 9, 10; however, ethnic differences exist in the frequency of AF‐related single nucleotide polymorphisms (SNPs) between European and Asian populations,11, 12 and thus the relationship between these SNPs and AF in non‐European populations remains unclear. Furthermore, despite the identification of these AF‐associated loci, data regarding the association between variants at these loci and clinical outcomes remain limited. Some reports suggested that these variants were associated with an increased risk of AF recurrence after a radiofrequency catheter ablation (RFCA),13, 14, 15 a common therapy in symptomatic patients with lone AF. These reports, however, were conducted in patients of European ancestry, and the associations between genetic variants and responses to RFCA in other ancestral groups remain unclear.
The goal of the current study was 2‐fold. First, we sought to determine whether the top 4 AF SNPs identified in European patients were also associated with AF in Korean patients. These SNPs reside on chromosomes 4q25 (PITX2 locus), 16q22 (ZFHX3 locus), and 1q21 (KCNN3 locus). Second, we examined whether these AF SNPs were associated with AF recurrence after RFCA.
The study protocol was approved by the institutional review board of Severance Cardiovascular Hospital, Yonsei University Health System, and adhered to the Declaration of Helsinki. This study is registered at ClinicalTrials.gov (identifier NCT02138695). All 2136 subjects (1068 with AF patients and 1068 with age‐ and sex‐matched control subjects) provided written informed consent. All AF patients who underwent RFCA were included in the Yonsei AF Ablation Cohort registry. The exclusion criteria of this study were as follows: (1) permanent AF refractory to electrical cardioversion, (2) AF with valvular disease, (3) structural heart disease other than left ventricular hypertrophy, and (4) prior AF ablation. Age‐ and sex‐matched control DNA was obtained from the Korea Centers for Disease Control and Prevention, National Biobank of Korea (KOBB‐2012‐00).16, 17 All control subjects had a 12‐lead electrocardiogram to exclude the presence of AF.
SNP Selection and Genotyping
We evaluated selected SNPs from the top 3 AF‐associated genetic loci in European patients from the meta‐analysis of genomewide association studies reported by Ellinor and colleagues in 2012 and in other previous papers.6, 10, 18 Specifically, we selected the top variant or a proxy SNP at each locus. For the locus at PITX2, the top SNP reported was rs6817105,6 and the SNP rs2200733 is a perfect proxy for this SNP (r2=1.0). Because SNP rs6843082 has also been reported to be strongly associated with AF10 and is in only modest linkage disequilibrium with rs6817105, we included this SNP in our analyses (r2=0.434). For the locus at ZFHX3 on chromosome 16q22, the top SNP selected was rs2106261. At the KCNN3 locus on chromosome 1q21, the top SNP reported was rs6666258,6 and we selected a perfect proxy for genotyping: SNP rs13376333 (r2=1.0).
We used whole blood samples for DNA extraction and genetic analyses. The SNPs were genotyped using validated TaqMan assays (Applied Biosystems, Life Technologies). Polymerase chain reaction product was amplified using 0.9 μm each of the forward and reverse primers, 0.2 μm each of the fluoresce in amidite and VIC minor groove binder sequence–specific probes, 3 ng DNA, 5.0 mmol/L MgCl2, and 1× TaqMan Universal PCR Master Mix containing AmpliTaq gold DNA polymerase in a 5.5‐μL reaction volume. All SNPs had a call rate of >99%.
Radiofrequency Catheter Ablation
During the procedure, intracardiac electrograms were recorded using a Prucka CardioLab electrophysiology system (General Electric Health Care System Inc). Ablation was guided by 3‐dimensional electroanatomical mapping (NavX system; St. Jude Medical Inc). An open irrigation 3.5‐mm‐tip deflectable catheter (Celsius, Johnson & Johnson Inc; Cool Flex, St. Jude Medical Inc; 30 to 35 W; 47°C) was used for RFCA (Stockert generator; Biosense Webster Inc). All patients initially underwent circumferential pulmonary vein (PV) isolation and cavotricuspid isthmus ablation. For patients with persistent AF, we added a roof line, posterior inferior line, and anterior line19 as a standard lesion set. At the operator's discretion, additional ablations were delivered to the superior vena cava, non‐PV foci, or regions of complex fractionated electrograms. We confirmed the PV isolation by both entrance and exit block and rechecked it under an isoproterenol infusion before finishing the procedure. In addition, we attempted to reinduce AF by isoproterenol infusion with rapid atrial pacing before finishing the procedure. The end point of our procedure was defined as no immediate recurrence of AF after cardioversion while receiving an isoproterenol infusion (5 to 10 μg/min). If there was immediate recurrence of AF after cardioversion, we then ablated these non‐PV foci.
Postablation Management and Follow‐up
Patients were seen in the outpatient clinic at 1, 3, 6, and 12 months and then every 6 months thereafter or whenever symptoms occurred after RFCA. An electrocardiogram was performed on every visit. A 24‐ or 48‐hour Holter recording and/or event recorder was obtained at the 3‐ and 6‐month visits as well as every 6 months afterward in accordance with the 2012 Heart Rhythm Society, European Heart Rhythm Association, and European Cardiac Arrhythmia Society expert consensus statement guidelines.20 Whenever patients reported symptoms of palpitations, Holter monitor or event monitor recordings were obtained and evaluated for possible arrhythmia recurrences. We defined recurrence of AF as any episode of AF or atrial tachycardia of at least 30 seconds in duration.21 Early recurrence was defined as having a documented AF electrocardiogram within 3 months after ablation. Clinical recurrence was defined as (1) any documented recurrence of AF after 3 months21 or (2) the initiation of an antiarrhythmic medication for AF.
Odds ratios (ORs) were calculated using logistic regression with an additive genetic model. In case‐only analysis, multiple parameters including clinical features and echocardiography parameters were compared depending on genotype distribution. Univariate analysis was performed for continuous variables using the t test and for nominal variables using the chi‐square test. The log‐rank test with Bonferroni correction for multiplicity of comparisons was applied to control the type 1 error. Multivariable Cox regression analyses were conducted to evaluate the associations between genetic variants and AF recurrence, with adjustment for age, sex, left atrium size, AF subtype (persistent AF), and early recurrence (≤3 months). Cases and controls were matched using the variables age and sex to reduce confounding effects. Conditional logistic regression models were used to assess the association between each SNP and AF risk to take matching situation into account. Potential confounding factors that were statistically significant at P<0.05 in the univariate analysis were included in the final analysis. ORs and 95% CIs were estimated using conditional logistic regression analysis with adjustments for potential confounding factors, body mass index, hypertension, diabetic mellitus, and congestive heart failure. Additional analyses were performed in 4 different subgroups. All statistical analyses were performed using SPSS version 19.0 (IBM Corp).
Baseline characteristics of the study population are summarized in Table 1. We studied 1068 patients who underwent an AF ablation and 1068 controls who were matched on the basis of age and sex. The mean age of our study population was 57.5±11.2 years, and 74.6% of participants were male. As expected, the AF group had a higher prevalence of hypertension, diabetes mellitus, congestive heart failure, stroke, and coronary artery disease than the control group. To exclude the possible confounding effects caused by the imbalance of disease prevalence between cases and controls, we sequentially performed subgroup analyses excluding patients with the following risk factors: (1) hypertension; (2) diabetes mellitus; (3) congestive heart failure; and (4) strokes, coronary artery disease, and congestive heart failure simultaneously. All subgroup analyses were performed by using multivariable logistic regression, adjusting for age, sex, body mass index, hypertension, diabetic mellitus, and congestive heart failure, as appropriate, and the results were consistent (Table S1).
|AF (n=1068)||Controls (n=1068)|
|Male sex, %||74.6||74.6|
|Body mass index, kg/m2b||24.7±3.2||23.6±3.1a|
|Hypertension||510 (47.8)||19 (1.8%)a|
|Diabetes mellitus||139 (13.0)||14 (1.3%)a|
|Congestive heart failure||70 (6.6)||1 (0.1%)a|
|Stroke||106 (9.9)||0 (0%)a|
|Coronary artery disease||136 (12.7)||0 (0%)a|
|LA dimension, mm||41.6±6.5||—|
|LA volume index||35.0±12.3|
|Early recurrence, %||28.5||—|
|Clinical recurrence, %||19.0||—|
PITX2 and ZFHX3 Were Strongly Associated With AF in Korean Patients
We found that 2 of the 3 known AF‐associated loci were strongly associated with AF in Korean patients (Table 2). Two variants at the PITX2 locus and 1 at the ZFHX3 locus were significantly associated with AF (rs6843082_G: OR 3.41, 95% CI 2.55 to 4.55, P=1.32×10−16; rs2200733_T: OR 2.05, 95% CI 1.66 to 2.53, P=2.20×10−11; rs2106261_A: OR 2.33, 95% CI 1.87 to 2.91, P=3.75×10−14) In contrast, genetic variants at the KCNN3 locus were not associated with AF in Korean patients (rs13376333_T: OR 1.74, 95% CI 0.93 to 3.25, P=0.085). Interestingly, the frequency of the AF risk allele at this locus (rs13376333_T) was very low in the Korean population, at only 1.9% compared with 29.5% in European patients.10
|Nearest Gene||SNP||Chr||Position||Minor Allele/Major Allele||MAF||AF Associated Allele||OR||95% CI||P Valuea|
|PITX2||rs6843082||4||111937516||A/G||0.204||G||3.41||2.55 to 4.55||1.32×10−16|
|PITX2||rs2200733||4||111929618||C/T||0.394||T||2.05||1.66 to 2.53||2.20×10−11|
|ZFHX3||rs2106261||16||71609121||A/G||0.395||A||2.33||1.87 to 2.91||3.75×10−14|
|KCNN3||rs13376333||1||153080977||T/C||0.019||T||1.74||0.93 to 3.25||0.085|
Relationship Between AF‐Risk SNPs and Baseline Clinical Characteristics of Patients Undergoing AF Ablation
Next we sought to determine whether any baseline differences existed in an extensive set of clinical and echocardiographic parameters based on AF genotype (Table 3). Among the 1068 AF ablation patients, the only notable difference was that carriers of the AF‐associated risk allele for SNP rs6843082 on chromosome 4q25 were younger (50.8±15.3 versus 59.0±11.1, P=0.005).
|rs6843082 (PITX2)||rs2200733 (PITX2)||rs2106261 (ZFHX3)||rs13376333 (KCNN3)|
|AA (n=17)||GA (n=215)||GG (n=836)||CC (n=84)||CT (n=447)||TT (n=527)||GG (n=297)||GA (n=520)||AA (n=251)||CC (n=1020)||CT (n=48)||TT (n=0)|
|Male sex, %||58.8||71.2||75.8||71.4||72.0||77.2||72.4||75.6||75.3||74.4||79.2||—|
|Body mass index, kg/m2||26.0±3.5||24.6±2.8||24.9±2.8||24.8±2.8||24.7±2.9||25.0±2.7||24.7±2.8||24.8±2.8||24.9±2.6||24.8±2.8||25.5±2.5||—|
|Hypertension||9 (52.9%)||108 (50.2%)||393 (47.0%)||44 (52.4%)||202 (45.2%)||261 (49.5%)||147 (49.5%)||256 (49.2%)||107 (42.6%)||493 (48.3%)||17 (35.4%)||—|
|Diabetes mellitus||0 (0%)||26 (12.1%)||113 (13.5%)||6 (7.1%)||62 (13.9%)||71 (13.5%)||31 (10.4%)||75 (14.4%)||33 (13.1%)||134 (13.1%)||5 (10.4%)||—|
|Congestive heart failure||2 (11.8%)||21 (9.8%)||47 (5.6%)||7 (8.3%)||31 (6.9%)||32 (6.1%)||20 (6.7%)||34 (6.5%)||16 (6.4%)||67 (6.6%)||3 (6.3%)||—|
|Stroke||2 (11.8%)||24 (11.2%)||80 (9.6%)||6 (7.1%)||43 (9.6%)||56 (10.6%)||29 (9.8%)||52 (10.0%)||25 (10.0%)||101 (9.9%)||5 (10.4%)||—|
|Coronary artery disease||1 (5.9%)||28 (13.0%)||107 (12.8%)||8 (9.5%)||67 (15.0%)||60 (11.4%)||35 (11.8%)||69 (13.3%)||32 (12.7%)||130 (12.7%)||6 (12.5%)||—|
|LA dimension, mm||40.2±7.1||41.6±6.5||41.7±6.0||41.1±6.6||41.5±6.1||41.9±6.0||41.4±6.3||41.8±6.4||41.0±5.7||41.7±6.1||41.5±5.8||—|
|LA volume index||38.3±18.9||35.5±13.1||35.0±11.9||34.4±12.5||35.2±12.6||34.9±11.9||35.2±12.4||35.5±12.5||33.7±11.5||35.1±12.3||32.8±10.6|
|Early recurrence, %||0||28.8||28.9||25.0||28.2||29.4||29.6||28.1||27.9||27.6||45.8||—|
Relationship Between AF Genotype and Outcomes After AF Ablation
After ablation, 304 patients (28.5%) had early recurrence during the 3‐month blanking period. We did not observe any significant associations between AF‐risk SNPs and early AF recurrence. During 18.3±13.9 months (range 0 to 55 months) of follow‐up, 203 patients (19.0%) had a clinical recurrence >3 months from RFCA. Figure displays the freedom from AF recurrence for each of the 4 SNPs. None of the 4 SNPs were associated with a long‐term clinical recurrence after RFCA (Table 4).
|HR||95% CI||P Value|
|PITX2/rs6843082_G||0.84||0.61 to 1.15||0.280|
|PITX2/rs2200733_T||1.01||0.80 to 1.26||0.963|
|ZFHX3/rs2106261_A||0.86||0.71 to 1.04||0.128|
|KCNN3/rs13376333_T||0.72||0.38 to 1.36||0.308|
In a well‐characterized cohort of >1000 Korean patients with nonvalvular AF, we observed that 2 of the 3 main AF susceptibility signals discovered in European patients (chromosomes 4q25 [PITX2] and 16q22 [ZFHX3]) were similarly associated with AF, supporting a shared genetic basis for AF that transcends ancestry. Second, and in contrast to prior reports,13, 14 we did not observe any significant associations between these top 4 AF susceptibility loci and AF recurrence following catheter ablation.
Interestingly, the AF risk allele at 1q21 was not associated with AF; however, the frequency of this variant in the Korean population was rare. Large‐scale genomewide association studies showed the association of SNPs in PITX2, ZFHX3, and KCNN3 with AF in patients of European ancestry, and the results were replicated in a Japanese study.6 In Table 5, we summarized the published results of these 4 AF variants in patients of Asian descent. We noted that most published studies were smaller and studied only 1 or 2 of the top AF variants. Although SNPs at PITX2 and ZFHX3 were consistently associated with AF, there was less consistency among the studies at the KCNN3 locus. The lack of replication of the association at the KCNN3 locus may be due to the rarity of this risk allele among those of Asian descent. In Korean patients, the risk allele was quite rare, with a minor allele frequency of only 1.9%. Similarly, in Japanese and Chinese studies, this variant had a minor allele frequency of 1.5% and 4%, respectively. In contrast, European and Taiwanese populations had high prevalence of the AF risk allele (29.6% and 8.6%, respectively). Our findings highlight the variability in this KCNN3 AF risk allele, even among those of Asian descent. Our results also demonstrate the need for large‐scale genetic studies in specific Asian subgroups to identify this and other regions uniquely associated with AF.
|Ethnicity||European6||Japanese6||Hong Kong9||Chinese11||Taiwanese12||Hong Kong22||Chinese23||Chinese24||Korean|
|Total Number (AF Patients)||59 133 (6707)||4193 (843)||3048 (285)||2097 (650)||428 (214)||3169 (333)||1234 (383)||1593 (597)||2136 (1068)|
|95% CI||1.55 to 1.73||1.59 to 2.13||1.16 to 1.73||1.21 to 3.20||2.59 to 3.61|
|95% CI||1.17 to 1.30||0.71 to 0.91||0.87 to 1.26||1.15 to 1.51||1.46 to 2.00||1.79 to 2.31|
|95% CI||1.13 to 1.23||0.85 to 2.51||0.88 to 1.75||1.54 to 6.29||0.89 to 2.14|
The first identification of common genetic variants dates to 2007, yet data on the clinical utility of these variants remains relatively limited.25 Investigators have examined the risk of AF after cardioversion,26 the initiation of antiarrhythmic medication,27 and PV isolation ablation procedures.13, 14 In our study of >1000 Korean patients who underwent PV ablation, we did not observe any significant associations between the AF risk alleles on chromosomes 4q25, 16q22, or 1q21 and recurrent AF after catheter ablation. Our findings are in contrast to the recent observations in 2 studies of patients with Europeans ancestry (Table 6).13, 14 Many potential causes could underlie the discordant results observed between Asian and European populations. First, our results may point to a specific racial difference in the associations between AF genetic data and clinical recurrence after RFCA. It is possible that the genetic variants that we considered in Korean patients are only proxies rather than the truly causative SNPs at these loci. Second, because our study is nearly 3 times larger than the prior studies, it is possible that the findings in European patients reflected a relatively smaller sample size. Finally, the differences may also be due to technical variability of RFCA, surveillance for AF, or the length of the follow‐up period among the studies. Ultimately, further large‐scale multicenter studies will help resolve each of these issues.
|N||Age||Male||PAF||Race||End Point||SNP||Closest Gene||Late Recurrence of AF|
|Early Recurrence of AF||Late Recurrence of AF||HR (95% CI)||P Value|
|Husser14||195||56±12||73%||78%||European||Within 7 days||Between 3 and 6 months||rs10033464_T||PITX2||2.82 (1.29 to 6.15)a||0.009|
|rs2200733_T||PITX2||2.46 (1.06 to 5.69)a||0.036|
|Shoemaker13||311||60 (52 to 66)||72%||47%||European||N/A||After the 3‐month postablation blanking period||rs2200733_T||PITX2||0.76 (0.6 to 0.95)b||0.016|
|Current study||1068||58±11||75%||68%||Asian||Within the 3‐month postablation period||After the 3‐month postablation blanking period||rs6843082_G||PITX2||0.84 (0.61 to 1.15)||0.280|
|rs2200733_T||PITX2||1.01 (0.80 to 1.26)||0.963|
|rs2106261_T||ZFHX3||0.86 (0.71 to 1.04)||0.128|
Strengths of our study include the largest cohort of patients of Asian descent described to date, a well‐characterized ablation population with detailed phenotypic data, and a standardized clinical protocol for follow‐up after ablation. Our study was also subject to a number of potential limitations. First, we excluded patients with significant structural heart disease. Second, because we studied a Korean population, our results may not be generalizable to other races and ethnicities. This observational study included a highly selected group of patients referred for Yonsei AF Ablation Cohort; therefore, the results cannot be generalized to the entire AF population or to other ethnicities. The lack of association of the polymorphism to the recurrence of AF after ablation might be related to the low frequency of the variant in the selected population, a small effect of polymorphisms, heterogeneity of the population with varying underlying substrate, variable ablative techniques used, and follow‐up, despite the relatively consistent protocols for inclusion, ablation, and follow‐up.
Genetic variants at the PITX2 and ZFHX3 loci were strongly associated with AF among Korean patients, whereas there was no association at the KCNN3 locus. The clinical outcomes after a catheter ablation for AF could not be predicted by genetic variants in Korean patients.
We appreciate National Biobank of Korea (KOBB‐2012‐00) for kindly providing control DNA.
Sources of Funding
Dr Pak is supported by a grant (A085136) from the Korea Health 21 R&D Project, Ministry of Health and Welfare, and a grant (7‐2013‐0362) from the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (MSIP). Dr Choi is supported by grant no 2520140060 from the SNUH Research Fund and a Korea National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2014R1A1A2A16055218). Dr Ellinor is supported by grants from the National Institutes of Health (R01HL092577, R01HL104156, K24HL105780, HL065962), the American Heart Association (13EIA14220013), and Fondation Leducq (14CVD01). Dr Lubitz is supported by a grant from the National Institutes of Health (K23HL114724) and a Doris Duke Charitable Foundation Clinical Scientist Development Award (2014105).
Table S1. Subgroup association analyses of 3 known AF loci and atrial fibrillation excluding hypertension (n=558, n=1049); diabetes (n=929, n=1054); congestive heart failure (CHF; n=998, n=1067); and stroke, coronary artery disease, and CHF (n=796, n=1067). N=cases, n=controls.
An accompanying Table S1 is available at http://jaha.ahajournals.org/content/4/8/e002046/suppl/DC1
† Dr Choi and Mr Park contributed equally to this work.
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