Polymorphisms of Renin-Angiotensin-Aldosterone System Gene in Chinese Han Patients with Nonfamilial Atrial Fibrillation

Background Atrial fibrillation(AF) is the most common arrhythmia in the adult population. The activated renin-angiotensin-aldosterone system (RAS) has been reported to play an important role in the pathogenesis of atrial fibrillation. The aim of this study was to investigate the association between nonfamilial AF and polymorphisms in RAS gene. Methods A total of 931 patients with nonfamilial AF, 663 non-AF heart disease patients and 727 healthy subjects were selected. 10 tagSNPs (tSNPs) (ACE gene rs8066114, AGT gene rs7539020, rs3789678, rs2478544, rs11568023, rs2478523, rs4762, rs699 and CYP11B2 rs3802230, rs3097) were chosen and genotyped in our study. Single-locus analysis and haplotype analysis were used in this study. Results In single-locus analysis, we found rs11568023 and rs3789678 in AGT gene were associated with nonfamilial AF in Chinese Han population. AF risk was associated with rs3789678 between the AF group and control groups. Under dominant model, the significant AF risk was observed in rs3789678 between the AF group and non AF heart control group; And the protective effect was found in rs11568023, compared with the non-AF heart disease control group. In multilocus haplotype analysis, the association between frequencies of the haplotypes and AF risk was showed in AGT gene (rs7539020-rs3789678), compared ‘TT’ haplotype with the common ‘TC’ haplotype, adjusted for age, gender, LVEF, LVEDD, LAD and frequency of hypertension and diabetes. The diplotype with ‘TC’, carrying rs3789678-C-allele, was associated with reduced risk of AF between the AF group and the healthy control group. The diplotype with ‘TT’ haplotype in the same block, carrying rs3789678-T-allele, was associated with increased risk of AF. Conclusions Via a large-scale case-control study, we found that rs3789678 site was potential susceptible locus of AF whereas rs11568023 was protective factor.


Results
In single-locus analysis, we found rs11568023 and rs3789678 in AGT gene were associated with nonfamilial AF in Chinese Han population. AF risk was associated with rs3789678 between the AF group and control groups. Under dominant model, the significant AF risk was observed in rs3789678 between the AF group and non AF heart control group; And the protective effect was found in rs11568023, compared with the non-AF heart disease control group. In multilocus haplotype analysis, the association between frequencies of the haplotypes and AF risk was showed in AGT gene (rs7539020-rs3789678), compared 'TT' haplotype with the common 'TC' haplotype, adjusted for age, gender, LVEF, LVEDD, LAD and frequency of hypertension and diabetes. The diplotype with 'TC', carrying rs3789678-C-allele, was associated with reduced risk of AF between the AF group and the healthy control Introduction Atrial fibrillation is the most common arrhythmia in the adult population. However, the underlying mechanisms of AF remain unknown. So far a lot of evidence is in support of a role for renin-angiotensin-aldosterone system (RAS) activation as an important factor in paroxysmal and persistent AF. Genetic variations of RAS affect plasma and tissue RAS activity, and ACE and angiotensin II levels. Hiroshi Watanabe [1] demonstrated for the first time that the ACE I/D polymorphism is associated with atrial and atrioventricular conduction in patients with lone AF. Polymorphisms in the angiotensinogen gene were also associated with AF as they might cause higher angiotensinogen gene transcription activity and a higher tissue angiotensin II concentration in the atrium under the stimulation of high atrial pressure [2,3]. However, Yamashita et al. [4] examined an Asian cohort with lone AF and found no significant association between the DD genotype and AF. The results of a meta-analysis indicated that there was insufficient evidence to draw clear conclusions on the potential association between the ACE I/D polymorphism and AF risk [5].
Some studies suggest that polymorphisms in the renin-angiotensin-aldosterone system alter activation of the renin-angiotensin-aldosterone system and increase the likelihood of atrial fibrillation. However, they are far from being definitive. The majority of studies about commonly occurring SNPs have not been replicated in independent populations or in different ethnic groups and have been substantially underpowered. Case-control studies are useful in identifying gene polymorphisms that are associated with disease. If the polymorphism itself is functional, or an allele polymorphism is in linkage disequilibrium with a disease susceptibility allele, we will find functional mutation and discover the mechanism of atrial fibrillation. Based upon the aforementioned studies on RAS genes and AF, we hypothesized that RAS genes may be the susceptible genes of non-familial AF, and we can find the association between the RAS gene variantsandnon-familial AF in a matched case-control study. Therefore, we investigated the association of tSNPs in RAS gene (ACE gene rs8066114, AGT gene rs7539020, rs3789678, rs2478544, rs11568023, rs2478523, rs4762, rs699 and CYP11B2 rs3802230, rs3097) and atrial fibrillation in a Chinese Han sample.

Study population
This study was approved by the Institutional Review Board of Shanghai First People's Hospital affiliated to Shanghai Jiao Tong University. All patients provided written informed consent. We enrolled 931AF subjects as AF group (529 men and 402 women; mean age, 64.63± 10.83 years) and 663 non-AF heart disease subjects as control group 1 (363 men and 300 women; mean age, 64.96±7.90 years), admitted to department of Cardiology from July 2012 to August 2013. We also enrolled 727 healthy subjects as control group 2 (378 men and 349 women; mean age, 61.81±8.38 years) from our medical examination center in 2012 (Table 1, 2). All of three groups came from Shanghai First People's Hospital affiliated to Shanghai Jiao Tong University. AF was diagnosed by electrocardiogram (ECG) or Holter. Exclusion criteria for case group included one of the following: familial AF, recent MI (six months or less), cardiac surgery (30 days or less), New York Heart Association class III or IV, severe valve disease, thyroid dysfunction, renal or lung dysfunction, and AF due to trauma, surgery, or acute medical illness. For every case patient, a matched control group1 without a history of AF was selected from the same ward. Case and control group1 patients were individually matched with regard to their gender, age (difference less than 5 years), New York Heart Association class, valvular heart disease, acute medical illness, hypertension and diabetes. All subjects in the case group and control groups were less than 80 years old. We elected healthy control group without AF history from our hospital's medical examination center. Their electrocardiogram (ECG) and Holter showed sinus rhythm.
Transthoracic echocardiography was performed to measure the left atrial and left ventricular dimensions and to detect significant valvular disease (defined as moderate to severe valvular regurgitation or stenosis, normal left atrial dimension 19-40 mm, normal left ventricular endsystolic dimension 20-40 mm, left ventricular end-diastolic dimension 35-55 mm).
Three groups were comparable with regard to ethnicity, sex, and residence area. However, the factors of age, left atrium dimension, left ventricular end diastolic dimension and left ventricular ejection fraction showed significant differences between the AF group and control groups ( Table 1, 2) Extraction of genomic DNA A 2-mL volume of venous blood samples from each participant was taken in citrate-anticoagulated glass tubes, and was frozen at -40°C. Total genomicDNA of the leucocyte was extracted from 1 ml of peripheral blood using the Whole Blood DNA Extraction Kit (QIAamp DNA Blood Mini Kit), according to the manufacturer's instructions. Genomic DNA extracted was dissolved in 0.1×TE buffer (10 mMTris-1 mM EDTA, pH8.0) and stored at -20°C.

TagSNP selection
Some tSNPs of RAS system gene were selected by using genotype data obtained from the International HapMap Project (http://hapmap.ncbi.nlm.nih.gov) data (released # 27/PhaseII+III Feb 09). To identify common tagging SNPs, these eligible SNPs were entered into the Tagger program implemented in Haploview 4.2 program (http://www.broad.mit.edu/haploview/ haploview-downloads). We defined the common variants as those with minor allele frequency (MAF) of more than 5% and set the threshold of 0.8 for LD measure r 2 . In the end, a total of 10 tSNPs (ACE gene rs8066114, AGT gene rs7539020, rs3789678, rs2478544, rs11568023, rs2478523, rs4762, rs699 and CYP11B2 rs3802230, rs3097) were chosen in our study.

SNP genotyping assays
SNPs were typed using iPLEX chemistry on a matrix-assisted laser desorption/ionization timeof-flight mass spectrometer (MALDI-TOF-MS, named as MassARRAY system, manufactured by Sequenom, Inc.). In brief, (1) multiplex PCR amplification: PCR reactions were carried out in standard 384-well plates in 5 μL per reaction with 10 ng of genomic DNA, 0.5 units of Taq polymerase (HotStarTaq, Qiagen), 500 μmol of each deoxynucleotidetriphosphate (dNTP), and 100 nmol of each PCR primer. PCR thermal cycling was carried out in an ABI-9700 instrument for 15 min at 94°C, followed by 45 cycles of 20s at 94°C, 30s at 56°C, and 60s at 72°C. PCR products were electrophoresed on 2.0% agarose. (2) Removing residual primers and dNTPs: after PCR reaction, 2 μL containing 0.3 units of Shrimp Alkaline Phosphatase was added, and the reaction was incubated at 37°C for 20 min followed by inactivation for 5 min at 85°C. (3) PCR with single base extension: After adjusting the concentrations of extension primers to equilibrate signal-to-noise ratios, the post-PCR primer extension reaction of the iPLEX Gold Kits (Sequenom, Inc.) assay was done in a final 9 μL volume extension reaction containing 0.2 μL (100 μmol) of termination mix, 0.04 μL containing 0.05 units of DNA polymerase (Sequenom, Inc.), and 625 to 1,250 nmol/L extension primers. A 200-short-cycle program was used for the iPLEX reaction: initial denaturation was for 30s at 94°C followed by 5s at 94°C and five cycles of 5s at 52°C and 5s at 80°C. An additional 40 annealing and extension cycles were then looped back to 5s at 94°C, five cycles of 5s at 52°C and 5s at 80°C. The final extension was carried out at 72°C for 3 min and the sample was cooled to 4°C. (4) Analyses of purified extension reaction products by MALDI-TOF-MS: The samples were then manually desalted by using 6 mg of clean resin and a dimple plate and subsequently transferred to a 384-well Spectro-CHIP (Sequenom, Inc.) using a nanodispenser. Mass spectrum was acquired by Compact Mass Spectrometer and analyzed by MassARRAYTyper 4.0 Software (Sequenom, Inc.). The PCR assay was arrayed with two no-template controls and four duplicated samples in each 384-well format as quality controls. All genotyping results were generated and checked by laboratory staff unaware of patient status.

Statistical analyses
The statistical analyses were performed with the Stata statistical package (version 10.0; Stata-Corp LP, College Station, TX, USA). The quantitative variables were presented as the mean ± SD, which are normally distributed. Measured variables were compared in patients with and without AF and the healthy group by an unpaired Student's t-test. Hardy-Weinberg Equilibrium (HWE) was tested in the healthy group by the chi-square test. The allele frequency, genotype, haplotype as well as dihaplotype between the groups were examined by unconditional logistic regression analysis with adjustment for age, gender, LVEF, LVEDD, LAD and frequency of hypertension and diabetes. P < 0.05 was considered statistically significant. The pairwise linkage disequilibrium (LD) among the SNPs was examined using Lewontin's standardized coefficient D' and LD coefficient r 2 [6], and haplotype blocks were defined by the method of Gabriel et al. [7] in Haploview 4.2 with default settings (the CI for a strong LD was minimal for upper 0.98 and low 0.7 and maximal for a strong recombination of 0.9, and a fraction of strong LD in informative comparisons was at least 0.95). In addition, PHASE 2.1 Bayesian algorithm [8] was used to estimate the haplotype frequencies. The HAPLO.STATS package developed by Schaidet al. [9] (http://www.mayo.edu/hsr/Sfunc.html) in the software language R was used for the haplotype analysis. Haplotypes with a frequency of less than 0.03 were pooled into a combined group. Diplotype (haplotype dosage, an estimate of the number of copies of the haplotype) was the most probable haplotype pair for each individual. Unconditional logistic regression analyses were conducted to estimate ORs and 95% CIs for participants carrying one to two copies versus zero copy of each common haplotype for the dichotomized diplotypes.

Individual SNP association analysis
There was no deviation from the Hardy-Weinberg equilibrium in the healthy group. After Bonferroni correction (the results were corrected for SNP number and the number of statistical analyses), the allele frequencies of AGT gene SNP5 rs11568023 was significantly different between the AF group and non-AF heart disease control group (P = 0.0003). And the allele frequencies of AGT gene SNP7 rs3789678 was significantly different between the AF group and the healthy control group (P = 0.043) ( Table 3).

LD Analysis and Haplotype Block Structure
The plots of the pairwise LD (D') values for the tSNPs and LD structures of each gene are displayed in Figs. 1B, 2B. The LD plot indicates that compared with the non-AF heart disease control and the healthy control group, for AGT gene, block 1 (SNPs 2-3: size 1598bp) with high LD were identified, encompassing the downstream intron 1 and the former exon 2 (Figs. 1B, 2B); And compared with the healthy control group, block 2 (SNPs 6-7: size 292bp) with high LD were identified, encompassing the intron region (Fig. 2B). For CYP11B2 gene, compared with the healthy control group, we identified the following regions of strong LD: SNPs 1-2 (size 451bp) covering the 3' UTR. The calculation of pairwise LD (r 2 ) values for these tSNPs is illustrated in Figs. 1A, 2A.

Discussion
Previous studies only focused on a few variants in RAS system genes, which may be insufficient to capture the full effects of susceptibility genes. This study targeted these main genes of RAS system (ACE, AGT, and CYP11B2 genes) and tested the hypothesis that genetic predisposition may be underlying the prevalence of nonfamilial AF by observing the association of tSNPs in RAS system gene with AF in a large pair-matched case control study.  Some studies reported that the polymorphisms of rs699 (M235T), rs5050 (A-20C), rs11568020 (G-152A), rs5051 (G-6A), rs4762 (T174M) and rs5049 (G-217A) were related to AF [2,3,10]. In the study, we found rs3789678 and rs11568023 of AGT gene exhibited statistically significant association with AF in Chinese Han population. Both of two sites had not been previously reported by other AF research groups. Rs11568023 and rs3789678 are in intron of the AGT gene. They showed no linkage disequilibrium (r 2 < 0.8) with the published six variants in Han Chinese population. However, rs3789678 was in strong LD (r 2 > 0.8) with four promoter SNPs (rs2071404, rs5046, rs11122580, rs2071405). Rs11568023 is localized in intronic region of AGT gene. It may be strongly linked with a potential functional locus or exerts molecular influence with AGT gene transcription. However, in HapMap database, the Han Chinese Beijing (HCB) sample size (about 90 healthy persons) is too small to show the virtual linked polymorphism of rs11568023. In addition, rs11568023 was only 1303bp away from rs3789678, but the function of these two polymorphisms was inverse. Consistently, in the haplotype and diplotype analysis "T" mutation of AGT gene rs3789678 was found associated with AF risk. Therefore, we demonstrated that the rs3789678 T allele in intron of the AGT gene and the corresponding haplotypes were associated with AF. A specific haplotype may be associated with higher AGT gene transcription activity. This higher transcription may cause a higher tissue angiotensin II concentration in the atrium, which subsequently causes atrial fibrosis, conduction heterogeneity and decreased atrial effective refractory period and provides the substrates for the development of AF.
In previous studies, rs699 proved to be associated with atrial fibrillation in Chinese Taiwan and Turkish population [2,11], but it did not exhibit association in our sample set. However, it showed association as haplotype form. There are some reasons as follows: Chinese Taiwan population is the Gaoshan nationality, whereas the population living in Shanghai belongs to Han nationality. In addition to territory and population stratification, another possible reason is that sample size is still not big enough. Although the sample size of our study was larger than the studies in Chinese Taiwan and Turkish population, we still need to verify the result in a more large-scale population. Other studies revealed that-344C/T (rs1799998) of CYP11B2 was associated with AF risk [12,13,14]. In our study, the single "A" mutation of CYP11B2 rs3802230 in the diplotype analysis, which was no genetic linkage with reported polymorphisms, showed reduced risk of AF. The main physiological determinants of serum aldosterone concentration are volume status, potassium levels, and activity of the renin-angiotensin-aldosterone system [15]. Genetic variation, such as rs3802230 of CYP11B2 gene, might modulate the expression of the enzyme [16], and therefore contribute to the inherited variability of aldosterone levels.
Control subjects in our study consisted of both healthy individuals and patients with heart diseases. The only difference between the AF group and the control group consisting of patients with heart diseases was the presence or absence of AF. Although the groups were similar in respect of age, hypertension, diabetes, and heart disease. AF patients had a significantly larger left atrium, higher LVEDD, and low LVEF. These findings may imply that stretching of the atria is responsible for the development of AF. In the Framingham study, it was found that left atrial dilation and reduced left ventricular fractional shortening increased the risk of AF [17]. Because gender, left atrial size, LVEDD, and LVEF were not balanced in the AF group and the two control groups, we reanalyzed the associations between AF and RAS polymorphisms with adjustmentfor these parameters. Hypertension and diabetes are known phenotypes associated with polymorphisms in RAS genes [18]. In our study, the case and the healthy group were not matched with regard to these frequencies of hypertension and diabetes. Thus, we analyzedthe associations between AF and RAS polymorphisms between the case and the healthy group, adjusted for the frequency of hypertension and diabetes. Some limitations are inherent in this study and must be noted. Although we used a statistical correction to adjust for multiple testing for a given gene, current epidemiologic and statistical literature is not unanimously clear on when and how to make such corrections. Although frequently used, both Bonferroni correction and Bayesian techniques [19] are problematic in correcting multiple comparisons. However, some authors believe that corrections were not needed when different associations in a study are of interest on a purely one-at-a-time basis [20,21]. In addition, although our study suggested that RAS system gene was involved in the prevalence of nonfamilial AF, the tSNPs selected for this study were not sufficient in capturing all the geneticvariation in Chinese Hans. Therefore, we were not able to exclude the potential association between rare alleles and nonfamilial AF in Chinese Hans.

Conclusion
Activation of the RAS may be an important risk factor for the occurrence and development of AF. In our study, we found that new polymorphisms/haplotypes in AGT gene were associated with nonfamilial AF in Chinese Han population. Therefore, genetic variation in the RAS system may influence effect of renin-angiotensin system blockers on atrial fibrillation. More importantly, this study shows the complexities of a multifactorial and multigenic disease like AF, and the necessity to continue studying it with a more comprehensive approach.
Supporting Information S1 Table. Associations of common haplotypes of AGT gene with AF risk between AF group and non-AF heartdisease control group. (DOCX) S2 Table. Diplotype analysis of AGT gene polymorphisms with AF risk between AF group and non-AF heart disease control group. (DOCX)