Genome-Wide Association Study Identifies 8 Novel Loci Associated With Blood Pressure Responses to Interventions in Han Chinese
Background—Blood pressure (BP) responses to dietary sodium and potassium intervention and cold pressor test vary considerably among individuals. We aimed to identify novel genetic variants influencing individuals’ BP responses to dietary intervention and cold pressor test.
Methods and Results—We conducted a genome-wide association study of BP responses in 1881 Han Chinese and de novo genotyped top findings in 698 Han Chinese. Diet-feeding study included a 7-day low-sodium (51.3 mmol/d), a 7-day high-sodium (307.8 mmol/d), and a 7-day high-sodium plus potassium supplementation (60 mmol/d). Nine BP measurements were obtained during baseline observation and each intervention period. The meta-analyses identified 8 novel loci for BP phenotypes, which physically mapped in or near PRMT6 (P=7.29×10–9), CDCA7 (P=3.57×10–8), PIBF1 (P=1.78×10–9), ARL4C (P=1.86×10–8), IRAK1BP1 (P=1.44×10−10), SALL1 (P=7.01×10–13), TRPM8 (P=2.68×10–8), and FBXL13 (P=3.74×10–9). There was a strong dose–response relationship between the number of risk alleles of these independent single-nucleotide polymorphisms and the risk of developing hypertension during the 7.5-year follow-up in the study participants. Compared with those in the lowest quartile of risk alleles, odds ratios (95% confidence intervals) for those in the second, third, and fourth quartiles were 1.39 (0.97, 1.99), 1.72 (1.19, 2.47), and 1.84 (1.29, 2.62), respectively (P=0.0003 for trend).
Conclusions—Our study identified 8 novel loci for BP responses to dietary sodium and potassium intervention and cold pressor test. The effect size of these novel loci on BP phenotypes is much larger than those reported by the previously published studies. Furthermore, these variants predict the risk of developing hypertension among individuals with normal BP at baseline.
High blood pressure (BP) is a global public-health challenge because of its high prevalence and related risk of cardiovascular disease and premature death.1,2 BP is influenced by multiple environmental and genetic determinants, as well as their interactions. Among environmental factors, dietary sodium and potassium intake is the most common and important risk factor for high BP.3 However, BP responses to dietary sodium and potassium intake vary considerably among individuals, and genetic factors might play an important role in BP salt sensitivity.4,5
Clinical Perspective on p 607
BP response to cold pressor test (CPT), a phenotype that characterizes sympathetic function, has been documented to predict the future risk of hypertension in normotensive persons.6 BP response to CPT has also been associated with salt sensitivity of BP.7 Twin and pedigree studies have suggested that BP response to CPT has strong genetic determinants.8
The recent meta-analyses of genome-wide association studies (GWASs) have identified multiple novel loci influencing usual BP levels and risk of hypertension.9–13 In general, the effect sizes of these common genetic variants on BP are small and explain only a small proportion of BP variation. The GWASs of intermediate BP phenotypes may identify novel genetic variants with larger effect sizes and reveal new biological pathways of BP regulation. We report top findings from GWASs of BP responses to dietary sodium and potassium interventions and CPT in the Genetic Epidemiology of Salt Sensitivity (GenSalt) study and findings from the meta-analysis of the GenSalt and GenSalt-replication studies.
The GenSalt study was conducted in a Han Chinese population in rural North China from 2003 to 2005.14 Details of the study participants and methods are summarized in the online-only Data Supplement. In brief, 1906 participants were recruited for the GenSalt dietary intervention, and 1881 of them had GWAS data. Among those with GWAS data, 1850 (98.4%), 1840 (97.8%), and 1836 (97.6%) completed the low-sodium, high-sodium, and potassium-supplementation interventions, respectively. The GenSalt-replication study was conducted in rural North China in 2010 using the identical eligibility criteria, intervention protocol, and data-collection methods. Among the 698 eligible participants, 666 (95.4%), 659 (94.4%), and 654 (93.7%) completed the low-sodium, high-sodium, and potassium-supplementation interventions, respectively.15
Institutional review boards or ethics committees at all participating institutes approved the study protocol. Written informed consent was obtained from each participant for the screening visit and for the main study (data collection and intervention).
The GenSalt and GenSalt-replication study participants received a consecutive 3-week dietary intervention, which included a 7-day low-sodium diet (3 g salt or 51.3 mmol sodium/d), a 7-day high-sodium diet (18 g salt or 307.8 mmol sodium/d), and a 7-day high-sodium diet plus potassium supplementation (60 mmol potassium/d). The results from 3 timed urinary specimens at baseline and during the last 3 days of each intervention showed excellent compliance with the study diet. The mean (SD) values of 24-hour urinary excretions of sodium and potassium were 242.4 (66.7) mmol and 36.9 (9.6) mmol at baseline, 47.5 (16.0) and 31.4 (7.7) during low-sodium intervention, 244.3 (37.7) and 35.7 (7.5) during high-sodium intervention, and 251.9 (36.9) and 77.3 (12.6) during high-sodium plus potassium supplementation intervention.
CPT was conducted at baseline examination. After the participant had remained seated for 20 minutes, 3 BP measurements were obtained using a standard mercury sphygmomanometer. Then the participant immersed the left hand in the ice water bath (3–5°C) to just above the wrist for 1 minute. BP measurements at 0, 60, 120, and 240 seconds after the left hand had been removed from the ice water bath were obtained on the right arm.
Three morning BP measurements were obtained according to a standard protocol during each of the 3 days of baseline observation and on days 5, 6, and 7 of each intervention period. All BP readings were measured by trained and certified observers using a random-zero sphygmomanometer after 5 minutes of rest with the participant in the sitting position and the arm placed at the level of the heart. The BP levels at baseline and during the intervention were calculated as the mean of 9 measurements from 3 clinical visits during the 3-day baseline observation or on days 5, 6, and 7 of each intervention phase. Responses were defined as follows: BP response to low sodium=BP on low-sodium diet–BP at baseline, BP response to high sodium=BP on high-sodium diet–BP on low-sodium diet, and BP response to potassium supplement=BP on high-sodium diet with potassium supplementation–BP on high-sodium diet. BP response to CPT at time 0=BP at time 0–BP at baseline during the CPT.
The GenSalt study participants were re-examined from 2008 to 2009 and 2011 to 2012 in the GenSalt follow-up study. Information on the history of hypertension and use of antihypertension medications was obtained using a standard questionnaire. Three BP measurements were obtained in the morning during each of 3 days of follow-up visits according to the same protocol used in the GenSalt study. Hypertension was defined as systolic BP (SBP) ≥140 mm Hg or diastolic BP (DBP) ≥90 mm Hg or the use of antihypertensive medications among 1521 GenSalt study participants who were free from hypertension at baseline and participated in the follow-up study.
Genotyping and Imputation
The Affymetrix Genomewide Human SNP array 6.0 (Affymetrix, Inc, Santa Clara, CA) was used to genotype a total of 868 158 autosomal single-nucleotide polymorphisms (SNPs) among 1881 GenSalt study participants. After removal of 44 237 monomorphic SNPs, 3638 SNPs because of deviations from Hardy–Weinberg equilibrium (P<1×10–6), 1 SNP with all missing data, and 265 SNPs with missing rate >25% and minor allele frequency <1%, a total of 820 017 SNPs remained. There was an overall non–Mendelian inheritance error rate of 0.019%. Non–Mendelian inheritance errors were identified and corrected using PLINK16 and PedCheck.17
A total of 2 416 663 SNPs from the HapMap release 22 build 36 Chinese Han of Beijing and Japanese of Tokyo samples were imputed using MACH software.18 After removing 25 814 monomorphic SNPs along with 174 075 SNPs with r2<0.30, minor allele frequency <1% and Hardy–Weinberg equilibrium P<1×10–6, 2 216 774 SNPs remained for analysis. There was an overall non–Mendelian inheritance error rate of 0.022%. Imputation results are summarized as dosage scores (fractional values ranging from 0 to 2, representing the expected number of copies of the coded allele at each SNP).
Based on GWAS findings, a total of 143 independent SNPs (with pairwise r2<0.90) were selected for de novo genotyping. Genotyping in the replication study was performed using the Sequenom MassARRAY system (Sequenom, Inc, San Diego, CA). Seven SNPs, which did not pass quality control, were regenotyped using the Taqman assay (Applied Biosystems, Foster City, CA). Two of the 143 SNPs were excluded from the analyses because they appeared monomorphic in the GenSalt-replication study.
We used an additive genetic model to examine the association between each SNP and continuous intervention BP phenotypes among the GenSalt study participants. A mixed-effects linear regression model was used to account for family structure and adjust for age, sex, and body mass index (SAS 9.2, SAS Institute Inc, Cary, NC). A sandwich option was used to compute the estimated variance–covariance matrix of the fixed-effects (genetic variant effects) parameters using the asymptotically consistent estimator. Because most of the studied families (random effects) only included sib-pairs, we selected compound symmetry as the covariance structure, which assumes the same degree of dependency among family members. A conventional genome-wide level of significance (P≤5×10–8) was used, although multiple phenotypes were tested. However, all phenotypes and a large proportion of SNPs are highly correlated with each other in our analysis.
We combined association results for each of the top 141 SNPs across the GenSalt and GenSalt-replication studies. We conducted a meta-analysis of study-specific estimates weighting by their inverse variance. Associations were considered genome-wide significant if they attained P<5×10–8 in combined analysis.
We examined the cumulative effects of risk alleles from genome-wide significant loci on the incidence of hypertension. BP genetic risk score was calculated as the sum of the number of risk alleles carried by each participant at all genome-wide significant SNPs.11,12 We defined risk alleles as those associated with greater BP reduction during low-sodium and potassium-supplementation interventions, greater BP increase during high-sodium intervention and CPT, and higher BP level during dietary intervention. Generalized linear mixed models were used to calculate the multivariable-adjusted incidence and odds ratio of hypertension according to quartile of genetic risk score while accounting for the nonindependence of study participants. Age, sex, body mass index, field center, and follow-up duration were adjusted in the multivariable models.
Characteristics of Study Participants
Characteristics of the GenSalt and GenSalt-replication study participants are presented in Table 1. On average, BP significantly (all P<0.0001) decreased in response to low-sodium and potassium-supplementation interventions and increased in response to high-sodium intervention and CPT.
Genome-Wide Association Analyses and Meta-Analyses of Top Signals
For the GWAS analyses of 2.2 million genotyped and imputed SNPs with the intervention BP phenotypes, genomic inflation factors ranged from 1.01 to 1.03, demonstrating no evidence of population stratification in the GenSalt sample. Quantile-quantile plots (Figure I in the online-only Data Supplement) showed large deviations between observed and expected P values among highly significant SNPs for the majority of phenotypes: SBP, DBP, and mean arterial BP (MAP) during low-sodium intervention; SBP responses to low-sodium intervention; SBP, DBP, and MAP during high-sodium intervention; SBP, DBP, and MAP responses to high-sodium intervention; SBP, DBP, and MAP during potassium-supplementation; and SBP, DBP, and MAP responses to CPT.
There were 10 SNPs that achieved genome-wide significance (P<5×10–8) in the initial GWASs of GenSalt participants: rs10930597 with MAP during low-sodium (P=2.05×10–8) and with MAP during potassium supplementation (P=1.21×10–8); rs13178964 with SBP during low sodium (P=1.02×10–8); rs8002688 with SBP responses to low sodium (P=3.69×10–8); rs12410212 with DBP during high sodium (P=4.13×10–8) and with DBP during potassium supplementation (P=2.09×10–8); rs16890334 with SBP during high sodium (P=2.92×10–8) and with SBP during potassium supplementation (P=1.74×10–8); rs4243280 with SBP during high sodium (P=3.29×10–8); rs11887188 with DBP during potassium supplementation (P=4.80×10–8); rs10086770 with DBP during potassium supplementation (P=1.73×10–8), rs17135875 with MAP responses to CPT (1.53×10–9), and rs7779854 with MAP responses to CPT (P=3.38×10–9). The -log10 P values by chromosomal locations for intervention BP phenotypes that achieved genome-wide significance in combined analyses of GenSalt and GenSalt-replication study participants are presented in Figure II in the online-only Data Supplement. The −log10 P values by chromosomal locations for the remaining intervention BP phenotypes are given in Figure III in the online-only Data Supplement.
To increase statistical power and provide replication evidence for initial GWAS findings, 143 independent SNPs were carried forward for genotyping among the GenSalt-replication study participants. The meta-analyses of GenSalt and GenSalt-replication study participants revealed 8 novel loci that achieved 12 genome-wide significant signals across 10 phenotypes (Table 2; Figure II in the online-only Data Supplement). Five of the 8 loci (rs1330225, rs8002688, rs11887188, rs2030114, and rs17135875) are low-frequency markers with minor allele frequencies ranging from 0.01 to 0.05. In addition, 16 loci achieved suggestive significance in the meta-analyses (P<5×10–7; Table II in the online-only Data Supplement).
Regional association plots for the 8 novel loci with genome-wide significance in the meta-analyses are given in Figure 1. Some loci (eg, rs10930597 and rs16890334) achieved genome-wide significance with >1 BP phenotype. However, only 1 regional association plot was presented for each locus. These loci are depicted using the most significant phenotype associations.
Two genome-wide significant loci for BP during low-sodium intervention were identified in the current study. A genome-wide significant signal at 1p21.1 was achieved for the association between rs1330225 and both DBP and MAP during low-sodium intervention (P=1.08×10–8 and 7.29×10–9, respectively). This intergenic variant is located >500 kbp downstream of its closest gene neighbor, PRMT6 (Figure 1A). At 2q31.1, intergenic variant rs10930597 achieved genome-wide significance for its association with MAP during low-sodium intervention (P=3.57×10–8). This variant is located within 500 kbp of the relatively unstudied RAPGEF4, ZAK, CDCA7, and SP3 genes (Figure 1C). In addition, 1 locus for the BP responses to low-sodium intervention achieved genome-wide significance. At 13q22.1, the intronic PIBF1 marker rs8002688 was associated with SBP responses to low sodium with P=1.78×10–9 (Figure 1B). Other genes within the 1 mega-base pair region include transcription factor gene KLF5 and the DIS3 gene. A genome-wide significant signal for SBP during high-sodium intervention (P=4.23×10–9) was observed at 6q14.1 with marker rs16890334, which is located just 21 kbp upstream of the IRAK1BP1 gene (Figures 1E).
Four loci attained genome-wide significance for BP during potassium-supplementation intervention. The CDCA7 locus marker rs10930597, which achieved genome-wide significance for its association with MAP during low-sodium intervention, again attained this significance threshold for both DBP and MAP during potassium supplementation (P=4.25×10–8 and 1.10×10–8, respectively; Figure 1C). At 2q37.2, a novel intergenic marker rs1187188 attained P=1.86×10–8 for association with DBP during potassium supplementation (Figure 1D). The closest gene to marker rs1187188 is ARL4C, whereas distant genes include SPP2 and TRPM8. Similarly, at 6q14.1 IRAKBP1 marker rs16890334, which robustly associated with BP during high sodium, attained genome-wide significance for SBP during potassium supplementation (P=1.44×10−10; Figure 1E). At 16q12.2, low-frequency variant rs2030114 achieved a genome-wide significant association with DBP during potassium supplementation (P=7.01×10–13; Figure 1F). The only gene at this locus SALL1 is located >400 kbp away from rs2030114.
Two signals were identified for the BP responses to CPT. Located at 2q37.1 just 7 kbp upstream of the TRPM8 gene, rs7577262 attained genome-wide significance for its association with SBP responses to CPT (P=2.68×10–8; Figure 1G). Other genes nearby rs7577262 include HJURP, SPP2, UGT1A8-UGT1A10, USP40, and DGKD. At 7q22.1, intronic FBXL13 marker rs17135875 achieved genome-wide significant associations with MAP response to CPT (P=3.74×10–9; Figure 1H). Other genes in the region include PRKRIP1, ORAI2, ALKBH4, POLR2J3, SPDYE2-2L, ARMC10, NAPEPLD, RPL19P12, DPY19L2P2, PMPCB, and DNAJC2.
Effect Size of Genome-Wide Significant Variants on BP Phenotypes
The absolute differences in BP during dietary sodium and potassium interventions for genome-wide significant SNPs ranged from 5.38 to 5.43 mm Hg for SBP and 3.14 to 5.48 mm Hg for DBP per coded allele (Table 2). The differences in BP responses to dietary sodium and potassium interventions or CPT were slightly smaller. BP differences for genome-wide significant signals were consistent in direction and magnitude across SBP, DBP, and MAP within each intervention (Figure 2).
Cumulative Effects on Hypertension Incidence
There was a strong dose–response relationship between risk allele quartile and development of hypertension (P=0.0003; Figure 3). The cumulative incidence of hypertension during a median follow-up time of 7.5 years was 15.0%, 19.7%, 23.2%, and 24.5% from the lowest to highest quartiles of risk alleles. Compared with those in the lowest quartile of risk alleles, odds ratios (95% confidence intervals) for those in the second, third, and fourth quartiles were 1.39 (0.97–1.99), 1.72 (1.19–2.47), and 1.84 (1.29–2.62), respectively.
We identified 8 novel loci for BP responses to dietary sodium and potassium interventions and CPT in the Han Chinese population. This study is the first GWAS to report genome-wide significant associations between genetic variants and intermediate BP phenotypes from interventions. The effect sizes of intermediate BP phenotypes associated with genetic variants are much greater than usual BP reported in the previous GWAS meta-analyses.9–13 Our study suggests that there are undiscovered pathways for BP regulation through sodium and potassium metabolism or the sympathetic system. Our study was able to identify multiple novel loci with a relatively small sample size because of its several unique design features. By controlling dietary intake of sodium, potassium, and other nutrients, environmental influences on BP variations are reduced; therefore, genetic effects on BP variations are amplified and therefore easier to detect in our study. The extreme low- and high-sodium intake, potassium supplementation, and cold pressor stimulate the expression of genes that are involved in sodium and potassium metabolisms, sympathetic function, and BP regulation. Thus, the associations of these genes with BP are easier to identify. In addition, averaging the multiple BP readings obtained on multiple days reduced the measurement errors of study phenotypes.
Several studies, including the GenSalt study, have showed that BP responses to dietary sodium intake and CPT are reliable and reproducible traits.19–22 Furthermore, BP responses to sodium intake and CPT are associated with the increased risk of hypertension, cardiovascular disease, and mortality.23–25
We identified 4 novel loci for sodium BP phenotypes, which physically mapped in or near PRMT6, CDCA7, PIBF1, and IRAK1BP1. The most significant SNP from each of the first 2 loci is located in intergenic regions. The PIBF1 gene encodes a progesterone-induced molecule known to interact with leptin to mediate the effects of progesterone during pregnancy.26,27 The putative role of this gene in BP regulation is unclear. IRAK1BP1 is part of the signaling pathway that leads to activation of nuclear factor-κB1.28 A transcription factor for proinflammatory pathway genes, inhibition of nuclear factor-κB has been shown to decrease inflammation, BP, and angiotensin-II–induced target end-organ damage in animal models,29,30 representing a plausible biological mechanism underlying the observed association. In addition, the nearby gene PHIP has been shown to modulate insulin signaling,31 whereas HMGN3 represents an important regulator of glucose-stimulated insulin secretion.32
We identified a suggestive genome-wide significant locus at 11p15.5 for MAP responses to high-sodium intervention (P=3.58×10–7). Marker rs10832417 is located in the intronic region of the KCNQ1 gene. Robust signals at KCNQ1 have been reported previously for type-2 diabetes mellitus,33–35 QT interval duration,36–38 and atrial fibrillation.39 Although not previously associated with BP-related traits, as a potassium channel with known protein expression in kidney cell lines,28 KCNQ1 represents a promising salt-sensitivity susceptibility locus.
Four loci were identified for BP during high sodium and potassium supplementation, which physically mapped in or near the CDCA7, ARL4C, IRAK1BP1, and SALL1 genes. CDCA7 and IRAK1BP1 were also associated with sodium BP phenotypes. ARL4C might be involved in lipid metabolism and inflammation.40,41 SALL1 was previously reported to associate with C-reactive protein in a GWAS.42 In addition, a SALL1 mutation was associated with impaired kidney function in a family.43 The associations between these loci with BP phenotypes have not been reported previously.
Two loci, which physically mapped in or near TRPM8 and FBXL13, were associated with BP response to CPT. Linked previously to neuropathic pain,44 TRPM8 is a logical candidate for BP response to CPT. Acting as a sensor for cold and cold-induced pain, TRPM8 encodes a nonselective cation channel that is activated by cold temperature <25°C and permeable to sodium, potassium, cesium, and calcium.28,45,46 TRPM8 was also close to marker rs1187188, which achieved genome-wide association with BP during high-sodium and potassium-supplementation intervention. Encoding a protein ubiquitin ligase, a functional role of FBXL13 in BP response to CPT is unclear. However, FBXL13 marker rs17135875 lies in a gene-dense region and is highly correlated with missense mutation rs17842496 (not successfully imputed in GenSalt but r2=1.00 in the HapMap CHB sample) of the relatively unstudied FAM18A gene. In addition, this marker was also highly correlated with LRRC17 transcription factor binding sites rs17135916 (r2=0.89) and rs7779854 (r2=0.89), as well as NFE4 transcription factor binding site rs2411061 (r2=0.84).
Several limitations of this study should be noted. Because of the uniqueness of intervention phenotypes, our study sample size is smaller when compared with other (nonintervention) BP GWASs.9–13 In addition, we were not able to identify additional independent samples for replication of our study findings. However, 5 of these SNPs showed nominal significance with usual BP in East Asians of the Asia Genetic Epidemiology Network (Table III in the online-only Data Supplement). Furthermore, previously reported SNPs are associated with absolute BP levels but not BP responses to interventions in our samples (Tables IV and V in the online-only Data Supplement). Our study is conducted in a community-based sample of the Chinese population. Therefore, the findings from this study may apply to the Chinese general population and other East Asian populations. In addition, previous studies have shown transethnicity replications of GWAS findings of usual BP.11 It is possible that some of our novel genetic loci associated with BP responses can be replicated in other race/ethnicities. Future studies are needed to confirm our findings in other populations.
Additional limitations include that most genetic variants reported in our study are not functional. Candidate genes mentioned in this article are only physically closest to identified novel SNPs. The causal variants in high LD with these SNPs might not be located within these candidate genes. Therefore, targeted deep sequencing studies in the entire genomic regions implied are required to identify rare or low-frequency novel functional variants for BP responses to intervention.47 In addition, only a few SNPs for each intervention phenotype were identified. We are not able to develop intervention-specific genetic risk scores for the prediction of hypertension. Furthermore, BP responses to 7-day low-sodium, high-sodium, or potassium-supplementation intervention might not reflect the long-term effect of diet on BP. However, our study and others have documented that BP responses to dietary sodium and potassium interventions become stable after 5 days.48 Finally, multiple correlated BP phenotypes (absolute levels and responses to intervention) are included in our analysis, which may inflate false-positive findings.
In summary, our study identified 8 novel loci for BP phenotypes during dietary sodium and potassium intervention and CPT. The effect size of these novel loci on BP phenotypes are much larger than those reported by the previously published BP GWAS meta-analyses.9–13 Furthermore, these variants predict the risk of developing hypertension among individuals with normal BP at baseline. Future studies are warranted to confirm these findings in independent populations and investigate the functional mechanisms of these novel loci.
We acknowledge Upsher-Smith Laboratories, Inc, for providing potassium chloride tablets (Klor–Con®M20).
Sources of Funding
GenSalt is supported by research grants (U01HL072507, R01HL087263, and R01HL090682) from the National Heart, Lung, and Blood Institute, National Institutes of Health, and partially supported by the Collins C. Diboll Private Foundation, New Orleans, LA. This study is also partially funded by research grant (2012AA02A516) of the High-Tech Research and Development Program of China (863 Plan) from the Ministry of Science and Technology of China.
From the Department of Epidemiology (J. He, T.N.K., Q.Z., S.L., Jing Chen, H.M., C.-S.C., L.L.H.), Tulane University School of Public Health and Tropical Medicine, and Department of Medicine (J. He, Jing Chen, L.L.H.), Tulane University School of Medicine, New Orleans, LA; State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (H.L., J. Huang, S.C., Jichun Chen, J.L., J. Cao, X.L., X.W., D. Gu) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China; National Human Genome Center at Beijing, Beijing, China (H.L., L.W.); National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD (C.E.J.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (Y.J.S., T.K.R., C.C.G., K.S., D.C.R.); Human Genetics Center, University of Texas School of Public Health, Houston, TX (L.C.S., J.E.H.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Center for Disease Control and Prevention of Shandong, Jinan, Shandong, China (J. Ma); First Affiliated Hospital of Medical College of Xi’an Jiaotong University, Xi’an, Shaanxi, China (J. Mu); Shenzhen University Medical Center, Shenzhen, Guangdong, China (D.H.); Xinle Traditional Medicine Hospital, Xinle, Hebei, China (X.J.); Department of Epidemiology and Biostatistics, Nanjing Medical University School of Public Health, Nanjing, China (C.S.); Yuxian People’s Hospital, Yangquan, Shanxi, China (D. Guo); Hebei Changcheng Hospital, Shijiazhuang, Hebei (R.W.); and Center for Disease Control and Prevention of Yancheng, Yancheng, Jiangsu, China (J.S.).
Dietary sodium reduction and potassium supplementation have been recommended for the prevention and treatment of hypertension. However, blood pressure responses to dietary sodium and potassium intake vary considerably among individuals. Blood pressure responses to the cold pressor test have been related to salt sensitivity and risk of hypertension. Identifying genetic variants associated with blood pressure responses to dietary sodium and potassium intake and cold pressor test will lead to a better understanding of the mechanism of blood pressure regulation and help to develop new pharmaceutical treatment for hypertension. In the current study, we identified 8 novel loci influencing individuals’ blood pressure responses to dietary sodium and potassium intervention and cold pressor test. The effect size of these novel loci on blood pressure phenotypes is much larger than those reported by the previously published studies. Furthermore, these variants predict the risk of developing hypertension among individuals with normal blood pressure at baseline. Future studies are warranted to confirm these findings in independent populations and to investigate the functional mechanisms of these novel loci.
The online-only Data Supplement is available at http://circgenetics.ahajournals.org/lookup/suppl/doi:10.1161/CIRCGENETICS.113.000307/-/DC1.
- Received May 9, 2013.
- Accepted October 12, 2013.
- © 2013 American Heart Association, Inc.
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