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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Am J Hypertens. Author manuscript; available in PMC 2010 December 1.
Published in final edited form as:
PMCID: PMC2890255
NIHMSID: NIHMS206228

Association of Genetic Variants in the Apelin-APJ System and ACE2 with Blood Pressure Responses to Potassium Supplementation: the GenSalt Study

Abstract

BACKGROUND

Genetic factors may influence blood pressure (BP) responses to dietary potassium intake. We examined the association of genetic variants in the apelin-APJ system and angiotensin-converting enzyme 2 (ACE2) with BP responses to potassium supplementation.

METHODS

We conducted a 7-day potassium supplementation (60 mmol/day) intervention among 1,906 Chinese adults who participated in the Genetic Epidemiology Network of Salt-Sensitivity (GenSalt) study. Tag single nucleotide polymorphisms (SNPs) based on HapMap data and potential functional SNPs were selected in the APLN, APLNR, and ACE2 genes. Because the ACE2 and APLN genes are located on the X chromosome, men and women were analyzed separately.

RESULTS

In women, SNP rs2235306 in the APLN gene was significantly associated with diastolic BP (DBP) response to potassium supplementation (P=0.0009). The DBP responses [95% confidence interval (CI)] among those with genotypes T/T, T/C, and C/C were −2.22 (−2.74, −1.70), −1.69 (−2.20, −1.19), and −0.81 (−1.54, −0.09) mmHg, respectively. In men, SNP rs4646174 of the ACE2 gene was significantly associated with systolic BP (SBP), DBP, and mean arterial pressure (MAP) responses to potassium supplementation (P=0.0001, P=0.001, and P=3.0×10−6, respectively). The SBP, DBP and MAP responses (95% CI) were −0.79 (−2.27, 0.69) versus −3.53 (−3.94, −3.12), 1.07 (−0.34, 2.49) versus −1.06 (−1.43, −0.69), and 0.44 (−0.60, 1.48) versus −1.89 (−2.22, −1.55) mmHg among men with minor G allele compared to those with major C allele of rs4646174, respectively.

CONCLUSIONS

Our study indicates that genetic variation of APLN and ACE2 may influence BP response to potassium intake.

INTRODUCTION

Observational epidemiologic studies have reported an inverse association between dietary potassium intake and blood pressure (BP).1,2 Randomized clinical trials have documented that potassium supplementation reduced BP in both hypertensive and normotensive participants.1-3 Clinical trials have also reported that the BP lowering effect of potassium supplementation might vary among individuals.3 The Genetic Epidemiology Network of Salt-Sensitivity study (GenSalt) showed that BP response to potassium supplementation varied even in a homogenous Han Chinese population. These findings suggest that ‘potassium sensitivity’ of BP might exist in humans. In addition, genetic factors might play an important role in determining the BP response to potassium intake. A moderate heritability of BP response to potassium supplementation was found in the GenSalt study.4 Identifying the genetic variants underlying BP response to potassium intake will enhance our understanding of biological mechanisms of BP regulation and may help the development of targeted prevention and treatment strategies for hypertension.

Apelin, a peptide which in humans is encoded by the APLN gene, is the endogenous ligand of the human G-protein coupled receptor APJ.5 The APLN gene encodes a 77 amino acid prepropeptide that is then cleaved to shorter mature peptides including apelin-36, apelin-17, and aplin-13, which activate the APJ receptor.6 The apelin–APJ system has wide representation in the central nervous system and a variety of peripheral tissues, such as lung, kidney, heart, and vasculature, and is emerging as an important regulator of cardiovascular homeostasis.6,7 It stimulates contractility without inducing ventricular hypertrophy, has mild diuretic effects, antagonizes the release of vasopressin centrally, and functions as both an arterial and venous dilator.6,7 Apelins are hydrolyzed by angiotensin-converting enzyme 2 (ACE2), an enzyme which is a negative regulator of the renin-angiotensin-aldosterone system (RAAS). This is also the only degradation pathway for apelins.8,9 APJ knock-out mice showed an increased vasopressor response to angiotensin II.10 These facts suggest an interaction between the apelin-APJ system and RAAS. It is well known that the RAAS plays a major role in regulating sodium and potassium balance as well as BP. In this study, we considered ACE2 an important component of the apelin-APJ system and examined the association of this system with BP response to a dietary potassium supplement among a large and homogenous sample of Han Chinese participants who took part in the GenSalt study.

METHODS

Study Population

The GenSalt study was conducted at six study sites located in rural areas of northern China from October 2003 to July 2005. All participants were of Han Chinese ethnicity. A community-based BP screening was conducted among persons aged 18–60 years in the study villages to identify potential probands and their families for the study. Those with mean systolic blood pressure (SBP) between 130–160 mmHg and/or diastolic blood pressure (DBP) between 85–100 mmHg and no use of antihypertensive medications and their siblings, spouses and offspring were recruited for the dietary intervention study. Detailed eligibility criteria for the participants are presented elsewhere.11 Individuals who had stage-2 hypertension, secondary hypertension, a history of clinical cardiovascular disease (CVD), chronic kidney disease or diabetes, used antihypertensive medications, or were pregnant, heavy alcohol users or currently on a low-sodium diet were excluded from the dietary intervention. Among the 1,906 participants eligible for dietary intervention, 1,843 (96.7%) completed the potassium supplement intervention and were included in the current analysis.

Institutional Review Boards at all participating institutes approved the GenSalt study. Written informed consent for the baseline observation and for the intervention program was obtained from each participant.

Potassium Supplementation Intervention

The GenSalt dietary intervention has been described previously.9 The GenSalt study participants were given a high-sodium diet (18 grams of salt or 307.8 mmol of sodium per day) for 7 days followed by a 60 mmol potassium-supplementation while continuing on the high-sodium diet for another 7 days. One potassium pill (20 mmol potassium) was given during breakfast, lunch, and dinner. To ensure compliance to the intervention program, study participants were required to eat their breakfast, lunch and dinner at the study kitchen under supervision of the study staff during the entire study period. The study participants were instructed to avoid consuming any foods that were not provided by the study. In addition, three timed urinary specimens (one 24–hour and two overnight) were collected at baseline and in each phase of intervention (days 5, 6, and 7) to monitor participants' compliance to dietary sodium and potassium intervention. The timed overnight urinary excretions of sodium and potassium were converted to 24-hour values based on a formula developed from data in this study. The results from the 24-hour urinary excretions of sodium and potassium showed excellent compliance with the study diet: the mean (standard deviation) 24-hour urinary excretions of sodium and potassium were 242.4 (66.7) mmol and 36.9 (9.6) mmol at baseline, 244.3 (37.7) and 35.7 (7.5) during the high-sodium intervention, and 251.9 (36.9) and 77.3 (12.6) during the potassium intervention, respectively.

Phenotype Measurement

A standard questionnaire was administered by trained staff at the baseline examination to collect information on family structure, demographic characteristics, personal and family medical history, and lifestyle risk factors. Body weight, height, and waist circumference were measured twice during the baseline examination. Three BP measurements were obtained each morning of the 3-day baseline observation and on days 5, 6 and 7 of each intervention period by the trained and certified observers using a random-zero sphygmomanometer according to a standard protocol.12 BP was measured with the participant in the seated position after resting for 5 minutes. In addition, participants were advised to avoid alcohol, cigarette smoking, coffee/tea, and exercise for at least 30 minutes prior to their measurement.

Mean BP response to the potassium supplement was calculated as the mean of 9 measurements on days 5, 6, and 7 during the potassium supplementation intervention minus the mean of 9 measurements on days 5, 6, and 7 during high sodium intervention.

SNP Selection and Genotyping

Both the apelin coding gene (APLN) and ACE2 are located on the X chromosome, while the APJ coding gene (APLNR) is located on chromosome 11. TagSNPs from these three genes were selected based on empirical patterns of linkage disequilibrium structure in the Chinese Han of Beijing (CHB) HapMap sample using Tagger software. We also included SNPs which were previously reported to be associated with BP or hypertension. SNPs were genotyped using SNPlex assays (Applied Biosystems, Foster City, CA, USA) based on oligonucleotide ligation assay for capillary electrophoresis on ABI 3700 DNA Analyzers (Applied Biosystems, Foster City, CA, USA). To provide better coverage of the candidate genes, we included additional SNPs genotyped on the Affymetrix 6.0 platform (Affymetrix, Santa Clara, CA, USA), which were not captured by the SNPlex SNPs. Functional SNPs from this platform, identified via Washington University's SNPseek website (http://snp.wustl.edu/cgi-bin/SNPseek/index.cgi), were also selected. A total of 19 SNPs (15 SNPlex SNPs and 4 Affymetrix SNPs) were analyzed in the current study (Table 1).

Table 1
Characteristics of all SNPs analyzed in this study

Statistical Analyses

Baseline characteristics and BP response variables of intervention participants were summarized as means and SDs for continuous variables and as percentages for categorical variables. The statistical significance of differences between men and women were examined by t-test or χ2 test.

The Mendelian consistency of the SNP genotype data was assessed by PLINK and PedCheck.13,14 We used Haploview software (version 4.0) to test Hardy-Weinberg Equilibrium (HWE) for each SNP and estimate the extent of pairwise linkage disequilibrium (LD) between SNPs.15 The confidence intervals method implemented in the Haploview software was used to define LD blocks.16 The most likely haplotypes within each block for individuals were inferred using MERLIN.17

Both single-SNP-based and haplotype-based association analyses were conducted using linear mixed models. A sandwich estimator was used to account for the non-independence of family members. This method assumes the same degree of dependency among all family members. Additive genetic models were assumed in both single SNP and haplotype analyses. Multivariable analyses adjusted for covariables including age, gender, BP measurement, room temperature, and study site. A gender-stratified analysis was conducted for those SNPs located on the X-chromosome. The mean effect size and 95% confidence interval (CI) were also calculated for each genotype and haplotype using mixed models. The Benjamini and Hochberg false discovery rate (FDR) method was used to adjust for multiple comparisons.18 The FDR q-value is defined as the expected proportion of the rejected null hypotheses which are erroneously rejected. We used the Proc Multtest procedure, along with its FDR option, in SAS (version 9.1; SAS Institute Inc) to calculate q-values. A q-value of 0.05 was used as the threshold for statistical significance in our study.

RESULTS

Table 2 shows the baseline characteristics of study participants and BP responses to the potassium supplementation, as well as the BP levels before and during potassium supplementation which were used to calculate the BP responses. Male participants were significantly older, had lower BMI and higher SBP, DBP and MAP compared to their female counterparts. BP levels were reduced in reponse to the potassium supplement for both men and women. Women had a larger mean DBP response to the potassium supplement than men (−1.7 mmHg vs. −1.2 mmHg, P = 0.02), whereas SBP and MAP responses were not significantly different between genders.

Table 2
Baseline characteristics and BP response to potassium supplementation of participants

No SNP deviated from HWE after adjustment for multiple comparisons using the FDR method (all q-values > 0.05). SNPs which were significantly associated with BP responses are shown in Table 3. Among women, SNP rs2235306 of the APLN gene was significantly associated with DBP response to the potassium supplement (P =0.0009). Each additional copy of the minor C allele was associated with a decreased DBP response to the potassium intervention. DBP responses (95% CI) among women with genotypes T/T, C/T, and C/C were −2.22 (−2.74, −1.70), −1.69 (−2.20, −1.19), and −0.81 (−1.54, −0.09) mmHg, respectively. None of the SNPs in the APLN gene was significantly associated with BP responses in men. However, we found that SNP rs4646174 of the ACE2 gene was significantly associated with BP responses to the potassium supplement in men (P=0.0001, P=0.001, and P=3.0×10−6 for SBP, DBP, and MAP responses, respectively). Compared to men with the major C allele, those with the minor G allele had decreased BP reductions due to the potassium supplement. Rs879922 and rs4646140 were also significantly associated with SBP and MAP responses. We did not observe any association between the analyzed SNPs in the APLNR gene and BP responses to the potassium supplement.

Table 3
SNPs significantly associated with BP responses to potassium supplementation

We also performed haplotype analysis of the three genes based on their LD block structure, as defined by Haploview software (Figure 1). A total of 4 LD blocks and 12 common haplotypes with frequencies greater than 0.05 was found in these genes. In women, haplotypes T-T and C-G within LD block 2 (rs2235306-rs3761581) of the APLN gene were significantly associated with DBP and MAP responses (Table 4). In addition, haplotype C-C of LD block 1 (rs2074192-rs714205) in the ACE2 gene was significantly associated with the DBP and MAP responses to the potassium supplement in men. However, none of the haplotypes remained significant after correction for multiple comparisons.

Figure 1
The gene structures of APLN (a), APLNR (b), and ACE2 (c) and the position of single nucleotide polymorphisms. The black boxes in each gene represent exons. Solid lines show introns and dashed lines show gene flanking regions. Pairwise linkage disequilibrium ...
Table 4
Association analysis of haplotypes with BP responses to potassium supplementation

DISSCUSSION

In this study, we present novel findings of an association between genetic variants in the APLN and ACE2 genes and BP responses to potassium supplementation. These findings not only indicate the existence of a genetic component underlying BP response to potassium supplementation, but also provide further clues for the mechanisms of the apelin-APJ system in BP regulation.

Our study is the first investigation to examine the genetic component underlying BP response to potassium supplementation. Although it is already known that BP response to potassium supplementation could be influenced by age, gender, race, sodium intake, and genetic factors,3,4 no study has been conducted to investigate the candidate genes for potassium-sensitivity of BP. In addition, our study has several other strengths. First, BP response to potassium supplementation was measured under a controlled dietary salt intake, which should minimize the confounding caused by the BP effect of sodium. Second, the large and homogenous Han population should increase study power and internal validity. Finally, the application of complementary SNP selection strategies, tagSNP and potentially functional SNPs, enabled a comprehensive analysis of the genetic variants of these candidate genes.

The potential mechanisms of the apelin-APJ system on BP regulation are not fully understood. Previous studies have suggested that apelin can activate endothelial nitric oxide synthase and cause nitric oxide-mediated arterial vasodilatation.19 On the other hand, apelin can directly activate APJ receptors on vascular smooth muscle cells leading to vasoconstriction, although this effect is outweighed by stimulation of local nitric oxide production.19 Furthermore, apelin in the rostral ventrolateral medulla can increase sympathetic nerve activity and BP.20 Apelin acts as a potent diuretic neuropeptide counteracting arginine vasopressin (AVP) actions through inhibition of AVP neuron activity and AVP release.21 Apelin regulates body adiposity, stimulates glucose utilization, and increases insulin sensitivity.22 The apelin-APJ system interacts with the RAAS, which has been well known to be an important regulator of BP as well as fluid and electrolyte balance. Potassium has been involved in most of these biologic mechanisms of BP regulation.23,24

ACE2, an important member of the RAAS, is a type I transmembrane metallopeptidase and cleaves a single C-terminal residue from a distinct range of substrates. One such substrate is angiotensin II, which is hydrolyzed by ACE2 to peptide angiotensin 1-7. Angiotensin 1-7 is a potentially important peptide for its vasodilatory, antifibrotic and natriuretic effects.25 Studies also showed that intrarenal angiotensin 1-7 might be involved in the regulation of salt and water excretion.26,27 Interestingly, ACE2 is also the only known degradation pathway of apelin peptides. This further highlights the interaction between the apelin-APJ system and the RAAS.

In this study, we identified an intronic SNP of the APLN gene, rs2235306, which was significantly associated with DBP response to the potassium supplement in women. Although not statistically significant, a similar trend in the association with SBP response was also observed. The previous studies have reported that the associations of genetic variants with SBP and DBP were not entirely consistent and suggested that the shared as well as separated mechanisms might be involved in SBP and DBP regulation.28 Compared to single marker results, the haplotype containing rs2235306 was not as strongly associated with BP responses. We've considered three potential reasons for the lack of a haplotype-phenotype association. First, it is possible that the FDR method used for correction of multiple comparisons may be too conservative for haplotype analysis. Secondly, lack of haplotype-phenotype association is possible when the association between markers and a phenotype is truly driven by a single SNP.29 Finally, the imprecise nature of haplotype inference may decrease the power to detect haplotype-phenotype association. We also found three intronic SNPs in the ACE2 gene, rs4646174, rs879922, and rs4646140, that were significantly associated with BP responses in single marker analyses. These intronic SNPs could be in LD with the actual risk variants which were not tested in our study. However, there is evidence supporting the functional importance of intronic polymorphisms in the cause of complex disorders.30,31 Reference of the SNPseek database suggests that rs2235306 and rs4646174 are located in a gene region of regulatory potential, which indicates that these SNPs could influence gene transcription. Since the minor allele frequencies of these three SNPs are relatively low, between 1% and 5%, independent replication of these results is warranted.

Neither individual SNPs nor haplotypes of APLNR showed significant associations with BP responses to potassium supplementation. There are few association studies that have examined the association between the APLNR gene and human diseases. Recently, Li et al. reported that rs7119375 was significantly associated with hypertension after correcting for age and gender in Han Chinese.32 Two other studies found genetic variants of APLNR to be associated with stroke and heart failure progression in idiopathic dilated cardiomyopathy patients, respectively.33,34 However, the association between APLNR and BP responses to potassium supplementation has never been studied. Further studies of this gene and BP or hypertension are warranted.

In this study, the ACE2 and APLN genes were related to BP response to potassium in a gender-specific manner. Genetic variants of ACE2 had a significant effect on BP response in men, not in women. For the APLN gene, conversely, the effect on BP response was significant in women but not in men. It is possible that these two genes have different effects on men and women because they are both located on the X chromosome. Other genetic studies have reported the gender-specific effect of ACE2 in human diseases. For example, Yang and colleagues conducted a case-control study and reported that in women, genetic variants of the ACE2 gene were associated with myocardial infarction.35 It was also reported that the ACE2 gene was associated with parameters of left ventricular hypertrophy only in men.36 In addition, the mechanisms underlying BP response to potassium may be different between men and women. It is already known that the biochemical changes in the RAAS related to estrogen status can explain some of the differences in the cardiovascular systems of men and women.37 Estrogen has been reported to contribute to a gender difference in plasma potassium concentrations.38 This difference between genders may also be the result of different genes or different effect sizes of single genes involved in BP response to potassium supplementation for men and women. Our findings warrant future research into gender differences in the genetic mechanisms of BP responses to potassium supplementation.

In summary, the current study indicated that genetic variants in the APLN and ACE2 genes were associated with BP responses to potassium supplementation in a Han Chinese population. These findings may have important clinical and public health implications, but further work is needed. Although these genes have been associated with BP in previous studies, independent replication of their association with potassium sensitivity of BP is necessary. In addition, future studies of these candidate genes are warranted to identify specific causal variants and their functions.

Acknowledgments

The Genetic Epidemiology Network of Salt Sensitivity (GenSalt) is supported by research grants (U01HL072507, R01HL087263, and R01HL090682) from the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland. Upsher-Smith Laboratories, Maple Grove, MN has provided Klor-Con M20 potassium tablets for the GenSalt study.

Appendix

GenSalt Collaborative Research Group

Tulane University Health Sciences Center, New Orleans, LA, USA: Jiang He (PI), Lydia A. Bazzano, Chung-Shiuan Chen, Jing Chen, Hao Mei, L. Lee Hamm, Tanika N. Kelly, Paul Muntner, Kristi Reynolds, Paul K. Whelton, Wenjie Yang, and Qi Zhao.

Washington University School of Medicine, St Louis, MO, USA: Dabeeru C. Rao (PI), Matthew Brown, Charles Gu, Hongyan Huang, Treva Rice, Karen Schwander, and Shiping Wang.

University of Texas Health Sciences Center at Houston, Houston, TX, USA: James E. Hixson (PI) and Lawrence C. Shimmin.

National Heart, Lung, and Blood Institute, Bethesda, MD, USA: Cashell E. Jaquish.

Chinese Academy of Medical Sciences, Beijing, China Dongfeng Gu (PI), Jie Cao, Jichun Chen, Jingping Chen, Zhenhan Du, Jianfeng Huang, Hongwen Jiang, Jianxin Li, Xiaohua Liang, Depei Liu, Xiangfeng Lu, Donghua Liu, Qunxia Mao, Dongling Sun, Hongwei Wang, Qianqian Wang, Xigui Wu, Ying Yang, and Dahai Yu.

Shandong Academy of Medical Sciences, Shandong, China: Fanghong Lu (PI), Zhendong Liu, Shikuan Jin, Yingxin Zhao, Shangwen Sun, Shujian Wang, Qengjie Meng, Baojin Liu, Zhaodong Yang, and Chuanrui Wei.

Shandong Center for Diseases Control and Prevention, Shandong, China: Jixiang Ma (PI), Jiyu Zhang, and Junli Tang.

Zhengzhou University, Henan, China: Dongsheng Hu (PI), Hongwei Wen, Chongjian Wang, Minghui Shen, Jingjing Pan, and Liming Yang.

Xinle Traditional Chinese Medicine Hospital, Hebei, China: Xu Ji (PI), Rongyan Li, Haijun Zu, and Junwei Song.

Ganyu Center for Disease Control and Prevention, Jiangsu, China: Delin Wu (PI), Xushan Wang, and Xiaofeng Zhang.

Xi'an Jiaotong University, Shaanxi, China: Jianjun Mu (PI), Enrang Chen, Fuqiang Liu, and Guanji Wu.

Chinese National Human Genome Center at Beijing, Beijing, China: Zhi-Jian Yao (PI), Shufeng Chen, Dongfeng Gu, Hongfan Li, Laiyuan Wang, and Penghua Zhang.

Footnotes

Conflict of Interest: none.

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