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American Journal of Hypertension logoLink to American Journal of Hypertension
. 2013 Feb 26;26(5):643–656. doi: 10.1093/ajh/hps099

Common Genetic Variants in the Endothelial System Predict Blood Pressure Response to Sodium Intake: The GenSalt Study

Maria Daniela Defagó 1,2, Dongfeng Gu 3, James E Hixson 4, Lawrence C Shimmin 4, Treva K Rice 5, Charles C Gu 5, Cashell E Jaquish 6, De-Pei Liu 7, Jiang He 8,9, Tanika N Kelly 9,✉
PMCID: PMC3657485  PMID: 23443727

Abstract

BACKGROUND

We examined the association between 14 endothelial system genes and salt-sensitivity of blood pressure (BP).

METHODS

After a 3-day baseline examination, during which time the usual diet was consumed, 1,906 Chinese participants received a 7-day low-sodium diet (51.3 mmol of sodium/day) followed by a 7-day high-sodium diet (307.8 mmol of sodium/day). BP measurements were obtained at baseline and at the end of each intervention using a random-zero sphygmomanometer.

RESULTS

The DDAH1 rs11161637 variant was associated with reduced BP salt sensitivity, conferring attenuated systolic BP (SBP) and mean arterial pressure (MAP) decreases from baseline to the low-sodium intervention (both P = 2×10−4). Examination of genotype–sex interactions revealed that this relation was driven by the strong associations observed in men (P for interactions = 1.10×10−4 and 0.008, respectively). When switching from the low- to high-sodium intervention, increases in diastolic BP (DBP) and MAP were attenuated by the COL18A1 rs2838944 minor A allele (P = 1.41×10−4 and 1.55×10−4, respectively). Conversely, the VWF rs2239153 C variant was associated with increased salt sensitivity, conferring larger DBP and MAP reductions during low-sodium intervention (P = 1.22×10−4 and 4.44×10−5, respectively). Ten variants from 3 independent SELE loci displayed significant genotype–sex interactions on DBP and MAP responses to low-sodium (P for interaction = 1.56×10−3 to 1.00×10−4). Among men, minor alleles of 4 correlated markers attenuated BP responses to low-sodium intake, whereas minor alleles of another 4 correlated markers increased BP responses. No associations were observed in women for these variants. Further, qualitative interactions were shown for 2 correlated SELE markers.

CONCLUSIONS

These data support a role for the endothelial system genes in salt sensitivity.

Keywords: blood pressure, endothelial system, genes, hypertension, salt sensitivity.

Hypertension is a major global health challenge because of its high prevalence and related risk of cardiovascular disease (CVD).1,2 As a complex trait, hypertension susceptibility is influenced by the interaction of genetic and environmental factors.3 Among environmental determinants, dietary sodium intake is one of the most important risk factors for hypertension.4,5 Clinical trials, observational epidemiologic studies, and animal experiments have long demonstrated the causal relationship between high dietary sodium intake and elevated blood pressure (BP).6–9 However, there is substantial evidence suggesting that BP responses to dietary sodium intake vary considerably among individuals and are normally distributed in populations.10 This phenomenon can be described as BP salt sensitivity.

The role of the endothelial system in BP regulation by nitric oxide (NO)–mediated vasodilation has been well described.11,12 Recently, studies have also shown that endothelial cells modify their function in response to changes in extracellular concentrations of sodium, with increased sodium related to decreased endothelial NO release and increased endothelial cell stiffness.11,12 Although these data implicate the endothelial system in the pathogenesis of salt-sensitive hypertension, few studies have examined the relationship between endothelial system genes and BP response to dietary sodium intake.13–16

This study aimed to comprehensively examine the association between common genetic variants from 14 endothelial system candidate genes (Table 1) and systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP) responses to a dietary sodium intervention among 1,906 participants of the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) feeding study.

Table 1.

Genes involved in the endothelial system

Gene symbol Gene name Chr Physical position ± 5,000 bp SNPs Functiona
EDN2 Endothelin 2 1 (41944446, 41950344) 1 Induces vasoconstriction, principally through EDNRA stimulation2
DDAH1 Dimethylarginine dimethylamino‑ hydrolase 1 1 (85784168, 86044046) 90 Participates in NO generation by regulating cellular concentrations of methylarginines, which in turn inhibit NO synthase activity3
VCAM1 Vascular cell adhesion molecule 1 1 (101185196, 101204601) 5 Involved in leukocyte–endothelial cell adhesion and signal transduction1
SELE Selectin E 1 (169691781, 169703220) 21 Mediates adhesion and transmigration of leukocytes to vascular endothelium4
EDNRA Endothelin receptor type A 4 (148402069, 148466106) 25 Participates in stimulation of cytokine release and endothelial growth factors5
MEF2C Myocyte enhancer factor 2C 5 (88014058, 88199922) 31 Contributes to vascular endothelial growth factor expression in endothelial cells 6
EDN1 Endothelin 1 6 (12290529, 12297427) 13 Acts through its receptor stimulation, endothelin receptor type A (EDNRA) and endothelin receptor type B (EDNRB)7
SERPINE 1 Serpin peptidase inhibitor, clade E 7 (100770379, 100782547) 2 Contributes to cardiac ventricular remodeling by migration of inflammatory cells and attenuation of extracellular matrix degradation8
NOS3 Nitric oxide synthase 3, endothelial cell 7 (150688144, 150711687) 8 Mediates the conversion of L-arginine in NO9
VWF von Willebrand factor 12 (6058040, 6233836,) 64 Marker of endothelial damage10
EDNRB Endothelin receptor type B 13 (78469616, 78493903) 10 Participates in the control of vascular tone by stimulation of vascular smooth muscle cell receptors11
CYBA Cytochrome b-245, alpha polypeptide 16 (88709697, 88717457) 1 Participates in the activation and stabilization of NADPH–oxidase12
TGFB1 Transforming growth factor, beta 1 19 (41836812, 41859831) 1 Regulates proliferation, differentiation, adhesion, migration, and other functions of the endothelial cell13
COL18A1 Collagen, type XVIII, alpha 1 21 (46825097, 46933634) 20 COL18A1 deficiency is associated with vascular endothelial cell damage and its degradation results in the generation of endostatin, a potent vasodilator14
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Abbreviations: Chr, chromosome; NO, nitric oxide; SNPs, single nucleotide polymorphisms.

a References for gene function correspond with those found in the Supplementary References.

METHODS

Study population

The GenSalt study was conducted in a Han Chinese population from rural north China where habitual salt intake is high. A community-based BP screening was conducted among adults aged 18–60 years in the study villages to identify potential probands and their families. Those with mean SBP ≥ 130mm Hg and/or DBP ≥ 85mm Hg and no use of antihypertension medications and their spouses, siblings, and offspring were recruited as volunteers for the dietary intervention study. Detailed eligibility criteria for the probands and siblings/spouses/offspring have been presented elsewhere.6 Briefly, individuals with stage 2 hypertension, current or recent use of antihypertension medications, secondary hypertension, history of clinical CVD, diabetes, chronic kidney failure, and liver disease or peptic ulcer disease requiring treatment during the previous 2 years, along with pregnant women, heavy alcohol drinkers, and those currently adhering to a low-sodium diet or unable to sign the informed consent form, were excluded from the study. Among the 1,906 eligible participants from 633 families, 1,871 (98.2%) and 1,860 (97.6%) completed the low-sodium and high-sodium dietary interventions, respectively, and were included in the current analysis.

Dietary intervention

After a 3-day baseline examination, during which time the usual diet was consumed, study participants received a 7-day low-sodium diet (3g of salt or 51.3 mmol of sodium/day) followed by a 7-day high-sodium diet (18g of salt or 307.8 mmol of sodium/day). During both intervention phases, potassium intake remained unchanged. Total energy intake was varied according to each participant’s baseline energy intake. All study foods were cooked without salt, and pre-packaged salt was added to the individual study participant’s meal when it was served by the study staff. To ensure study participants’ compliance with the intervention program, they were required to have their breakfast, lunch, and dinner at the study kitchen under supervision of the study staff during the entire study period. Three timed urinary specimens were collected at baseline and at the end of each intervention phase (days 5, 6, and 7) to monitor each participants’ compliance with the dietary sodium intervention. The mean of 24-hour urinary excretions of sodium and potassium were 242.4 (SD = 66.7) mmol and 36.9 (SD = 9.6) mmol at baseline, 47.5 (SD = 16.0) mmol and 31.4 (SD = 7.7) mmol during the low-sodium intervention, and 244.3 (SD = 37.7) mmol and 35.7 (SD = 7.5) mmol during the high-sodium intervention, respectively.

Phenotype measurements

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. 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.17 BP was measured with the participant in the sitting position after 5 minutes of rest. In addition, participants were advised to avoid alcohol, cigarette smoking, coffee/tea, and exercise for at least 30 minutes before their BP measurements. All BP observers were blinded to the participant’s dietary intervention. Body weight and height were measured twice in light indoor clothing without shoes during the baseline examination. Body mass index was calculated as kilograms per meters squared.

Salt-sensitivity phenotypes were defined continuously as the absolute changes in SBP, DBP, and MAP when switching from baseline to low-sodium intervention and from low-sodium to high-sodium intervention. Mean BP responses to low-sodium intake were calculated as the mean of 9 measurements on days 5, 6, and 7 during the low-sodium intervention minus the mean of 9 measurements at baseline, and responses to high-sodium intake were calculated as the mean of 9 measurements on days 5, 6, and 7 during the high-sodium intervention minus the mean of 9 measurements on days 5, 6, and 7 during the low-sodium intervention.

Candidate gene selection and single nucleotide polymorphism genotyping

We conducted a Medline literature search using Medical Subject Heading term “endothelium” or keywords “endothelial” or “endothelium” and Medical Subject Heading terms “genes” or “polymorphism, single nucleotide.” Fourteen candidate genes in the endothelial system were identified by the literature search strategy, including VCAM1, EDN2, DDAH1, SELE, EDNRA, MEF2C, EDN1, SERPINE 1, NOS3, VWF, EDNRB, CYBA, TGFB1, and COL18A1 (see Table 1). References of articles used to identify genes can be found in the Supplementary Materials. Genetic data, genotyped as part of the Affymetrix platform (Affymetrix 6.0, Santa Clara, CA) and using SNPlex assays (Applied Biosystems, Carlsbad, CA) based on oligonucleotide ligation assay for capillary electrophoresis on an automated DNA sequencer (ABI 3700 DNA Analyzer), were available for 368 single nucleotide polymorphisms (SNPs) from the 14 candidate genes and their 5,000 base-pair flanking regions. After standard quality control procedures, 75 SNPs with an minor allele frequency (MAF) < 1% and 1 SNP with a genotyping call rate < 85% were excluded, leaving a total of 292 SNPs for the analysis. Supplementary Table S1 provides descriptive information and quality control parameters for these SNPs.

Statistical analysis

The percent or means of baseline and intervention variables were calculated for the 1,906 GenSalt feeding study participants. Additive associations between single SNPs and BP responses to each dietary sodium intervention were assessed using a mixed linear regression model to account for the nonindependence of family members. Age, sex, body mass index, room temperature during blood pressure measurement, and study site were adjusted in multivariable analyses. To adjust for multiple comparisons, the false discovery rate Q value was calculated for all SNPs.18 Statistical significance was determined by Q < 0.05. For significant SNPs, the mean effect size and 95% confidence interval (CI) was estimated according to genotype. Because of the known role of estrogen in the activation of endothelial system components and observed sex differences in salt sensitivity,10,19 we examined genotype–sex interactions in an additional analysis. For those interactions that were significant after adjustment for multiple testing, we estimated the mean effect size and 95% CI according to sex and genotype. SAS statistical software version 9.2 was used for the analysis (SAS Institute, Cary, NC). We used Haploview software version 4.2 (http://www.broadinstitute.org/haploview) to estimate linkage disequilibrium, defined by the pairwise r 2 value, between SNPs.20

RESULTS

Characteristics of 1,906 GenSalt intervention participants are shown in Table 2. SBP, DBP, and MAP changed significantly in response to the dietary sodium interventions, with mean decreases of 6mm Hg, 3mm Hg, and 4mm Hg, respectively, in response to low-sodium intake and increases of 5mm Hg, 2mm Hg, and 3mm Hg in response to high-sodium intake.

Table 2.

Characteristics of 1,906 GenSalt dietary intervention participants

Variable Mean ± SD or percentage Median
(interquartile range)
Age, years 38.7±9.6 39.0 (33.0–46.0)
Men, % 53.0
BMI, kg/m2 23.3±3.2 22.9 (21.1–25.2)
SBP, mm Hg
 Baseline 116.9±14.2 115.8 (106.4–127.1)
 Response to low-sodium intake −5.5±7.0* −4.4 (−8.9 to −1.3)
 Response to high-sodium intake 4.9±6.0* 4.7 (0.6–8.2)
DBP, mm Hg
 Baseline 73.7±10.3 73.3 (66.7–80.7)
 Response to low-sodium intake −2.8±5.5* −2.7 (−5.6 to 0.4)
 Response to high-sodium intake 1.9±5.4* 1.8 (−1.6 to 5.3)
MAP, mm Hg
 Baseline 88.1±10.9 87.7 (80.0–95.4)
 Response to low-sodium intake −3.7±5.3* −3.3 (−6.6 to −0.6)
 Response to high-sodium intake 2.9±5.0* 2.7 (−0.4 to 5.9)
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Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure.

*P < 0.0001 when compared with no blood pressure change during sodium interventions.

Figure 1 presents the association between each SNP and absolute SBP, DBP, and MAP responses to the low- (Figure 1a) and high-sodium (Figure 1b) interventions. After adjustment for multiple testing, DDAH1 marker rs11161637 (MAF = 26%) was associated with SBP (P = 2.00×10−4; Q = 0.05) and MAP (P value = 1.83×10−4; Q = 0.02) responses to low-sodium intake. This marker explained 2.1% of the variation in each of these traits. VWF marker rs2239153 (MAF = 39%) was associated with DBP (P = 1.22×10−4; Q = 0.03) and MAP (P = 4.44×10−5; Q = 0.01) responses to low-sodium intake, explaining 1.1% and 0.9% of the variation in these traits, respectively. COL18A1 SNP rs2838944 (MAF = 7%) was associated with SBP (P value = 1.41×10−4; Q = 0.04) and MAP (P = 1.55×10−4; Q = 0.04) responses to high-sodium intake, explaining 0.6% and 0.5% of their respective variances.

Figure 1.

Figure 1.

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Log P values for the association between 292 single nucleotide polymorphisms in 14 candidate genes and systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) responses to low- (a) and high-sodium (b) interventions. Labeled single nucleotide polymporphisms had Q < 0.05. SNPs.

Mean BP responses and 95% CIs to the dietary sodium interventions according to DDAH1 rs11161637, VWF rs2239153 and COL18A1 rs2838944 genotypes are shown in Table 3. The magnitude of SBP and MAP responses to low-sodium intervention decreased significantly with the number of G alleles of DDAH1 marker rs11161637. Although not significant after adjustment for multiple testing, similar trends were observed for DBP response to low-sodium intake (P = 0.002) and SBP, DBP, and MAP responses to high-sodium intake (P = 0.006, 0.005, and 0.001, respectively). In addition, DBP and MAP responses to low-sodium intake increased in magnitude with each copy of the VWF rs2239153 C allele. Although findings did not achieve statistical significance after correction for multiple testing, similar trends were observed for the association of rs2239153 with the other BP phenotypes (P = 9×10−4 for SBP response to low-sodium intervention; and P = 0.001, 0.004, and 7×10−4, respectively, for SBP, DBP, and MAP responses to the high-sodium intervention). Finally, DBP and MAP responses to high-sodium intake decreased with each copy of the COL18A1 rs2838944 A allele. A similar but nonsignificant trend was observed for SBP response to high-sodium intake (P = 0.01).

Table 3.

Blood pressure responses to dietary sodium interventions according to DDAH1, VWF, and COL18A1 genotypes

HGNC symbol Genotype No. Response to low-sodium intervention (95% CI) P Q Response to high-sodium intervention (95% CI) P Q
Systolic blood pressure
 DDAH1 rs11161637 A/A 1021 −6.20 (−6.70 to −5.70) 0.0002 0.05 4.98 (4.56–5.40) 0.006 0.66
A/G 732 −5.38 (−5.87 to −4.88) 4.04 (3.60–4.48)
G/G 128 −4.02 (−5.33 to −2.70) 4.38 (3.29–5.47)
 VWF rs2239153 T/T 681 −5.12 (−5.65 to −4.60) 0.0009 0.13 4.15 (3.68–4.62) 0.001 0.39
T/C 821 −6.06 (−6.61 to −5.52) 4.62 (4.19–5.05)
C/C 275 −6.54 (−7.40 to −5.68) 5.57 (4.82–6.32)
 COL18A1 rs2838944 G/G 1605 −5.73 (−6.14 to −5.33) 0.90 0.94 4.69 (4.35–5.02) 0.01 0.94
G/A 263 −5.69 (−6.55 to −4.83) 3.89 (3.19–4.60)
A/A 9 −7.21 (−13.36 to −1.05) 2.00 (−0.50–4.49)
Diastolic blood pressure
 DDAH1 rs11161637 A/A 1021 −3.01 (−3.43 to −2.60) 0.002 0.16 1.97 (1.61–2.32) 0.005 0.27
A/G 732 −2.46 (−2.87 to −2.05) 1.28 (0.88–1.69)
G/G 128 −1.66 (−2.64 to −0.68) 1.17 (0.21–2.13)
 VWF rs2239153 T/T 681 −2.13 (−2.55 to −1.72) 0.0001 0.03 1.32 (0.89–1.74) 0.004 0.24
T/C 821 −3.09 (−3.54 to −2.64) 1.82 (1.43–2.20)
C/C 275 −3.38 (−4.08 to −2.67) 2.34 (1.71–2.96)
 COL18A1 rs2838944 G/G 1605 −2.70 (−3.05 to −2.36) 0.78 0.89 1.83 (1.52–2.14) 0.0001 0.04
G/A 263 −2.70 (−3.39 to −2.02) 0.65 (0.00 –1.29)
A/A 9 −4.16 (−7.30 to −1.02) −1.03 (−3.45 to 1.38)
Mean arterial pressure
 DDAH1 rs11161637 A/A 1021 −4.08 (−4.47 to −3.69) 0.0002 0.02 2.97 (2.63 to 3.31) 0.001 0.13
A/G 732 −3.43 (−3.83 to −3.04) 2.20 (1.83–2.57)
G/G 128 −2.45 (−3.42 to −1.48) 2.24 (1.35–3.12)
 VWF rs2239153 T/T 681 −3.13 (−3.54 to −2.73) 4.4×10–5 0.01 2.26 (1.87–2.66) 0.0007 0.09
T/C 821 −4.08 (−4.51 to −3.65) 2.75 (2.40–3.10)
C/C 275 −4.43 (−5.11 to −3.76) 3.41 (2.83–4.00)
 COL18A1 rs2838944 G/G 1605 −3.72 (−4.04 to −3.40) 0.82 0.97 2.78 (2.50–3.07) 0.0002 0.04
G/A 263 −3.70 (−4.37 to −3.03) 1.72 (1.13–2.31)
A/A 9 −5.16 (−9.12 to −1.20) −0.04 (−1.81 to 1.72)
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Abbreviations: CI, confidence interval; COL18A1, collagen, type XVIII, alpha 1; DDAH1, dimethylarginine dimethylaminohydrolase 1; HGNC, Human Genome Nomenclature Committee; VWF, von Willebrand factor.

Figure 2 presents the P values for the tests of genotype–sex interactions on SBP, DBP, and MAP responses to the low- (Figure 2a) and high-sodium (Figure 2b) interventions. After adjustment for multiple testing, an interaction between DDAH1 marker rs11161637 and sex was identified for SBP responses to low-sodium intake (P = 2×10−4; Q = 0.05). Examination of BP responses according to genotype and sex showed that the strong association in men (P = 1.63×10−7; Q = 4.85×10−5) was likely driving the association observed in the overall analysis (Table 4). In addition, 3 independent loci (r 2 < 0.80), which included 10 genetic variants, within the SELE gene displayed significant interactions with sex on DBP and MAP responses to low-sodium intervention (P = 1.00×10−3 to 1.00×10−4). Among men, the minor alleles of highly correlated SELE markers rs5356, rs3917430, rs3917428, rs5368 (MAFs = 0.27–0.32) were associated with attenuated BP responses to the low-sodium intervention, with no associations observed in women. In contrast, the minor alleles of correlated markers rs3917436, rs3917423, rs3917406, and rs932307 were associated with increased BP responses to the low-sodium intervention among men (MAFs = 0.43–0.49), with no association among women. Finally, among correlated markers rs1534904 and rs3917412 (MAF = 0.26 and 0.28, respectively), DBP and MAP responses to low-sodium intake tended to increase in men and decrease in women with each copy of the minor allele (Table 4).

Figure 2.

Figure 2.

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Log P values for the genotype–sex interactions of 292 single nucleotide polymorphisms in 14 candidate genes and systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) responses to low- (a) and high-sodium (b) interventions. Labeled SNPs had Q < 0.05.

Table 4.

Blood pressure responses to the dietary sodium interventions according to sex and genotypes

Gene Genotype Blood pressure response to low−sodium intervention Blood pressure response to high−sodium intervention
Men Women Men Women Interaction P a
Absolute change, mm Hg (95% CI) P Absolute change, mm Hg (95% CI) P Interaction P a Absolute change, mm Hg (95% CI) P Absolute change, mm Hg (95% CI) P
Systolic blood pressure
DDAH1 rs11161637 AA −6.32 (−6.96 to −5.68) 1.72×10−7 −5.77 (−6.53 to −5.01) 0.97 0.0001b 4.75 (4.22–5.27) 0.02 5.17 (4.52–5.83) 0.19 0.54
AG −4.78 (−5.40 to −4.17) −5.79 (−6.61 to −4.98) 3.74 (3.14–4.34) 4.42 (3.77–5.07)
GG −2.28 (−3.78 to −0.79) −5.79 (−7.88 to −3.70) 3.91 (2.62–5.21) 4.93 (3.36–6.51)
SELE rs3917436 GG −4.70 (−5.47 to −3.93) 0.004 −6.03 (−6.97 to −5.08) 0.13 0.002 3.98 (3.34–4.62) 0.64 4.90 (4.13–5.67) 0.71 0.57
GA −5.57 (−6.19 to −4.95) −5.94 (−6.72 to −5.15) 4.65 (4.11–5.18) 4.92 (4.29–5.54)
AA −6.59 (−7.62 to −5.57) −4.89 (−5.97 to −3.80) 4.04 (3.22–4.86) 4.64 (3.70–5.58)
rs5356 TT −5.84 (−6.48 to −5.20) 0.06 −5.43 (−6.21 to −4.65) 0.23 0.01 4.36 (3.87–4.87) 0.35 4.90 (4.26–5.53) 0.87 0.38
TC −5.11 (−5.75 to −4.47) −6.28 (−7.13 to −5.44) 4.43 (3.84–5.02) 4.73 (4.07–5.39)
CC −4.68 (−6.28 to −3.08) −5.57 (−7.44 to −3.69) 3.11 (1.59–4.64) 5.45 (3.90–7.00)
rs3917430 CC −5.92 (−6.59 to −5.24) 0.06 −5.18 (−5.97 to −4.39) 0.08 0.006 4.42 (3.90–4.95) 0.33 4.84 (4.20–5.48) 0.64 0.78
CG −5.15 (−5.77 to −4.53) −6.46 (−7.29 to −5.64) 4.36 (3.81–4.90) 4.76 (4.12–5.40)
GG −4.73 (−6.31 to −3.16) −5.65 (−7.24 to −4.05) 3.60 (2.27–4.93) 5.41 (3.91–6.92)
rs3917428 GG −5.80 (−6.44 to −5.16) 0.07 −5.40 (−6.17 to −4.63) 0.26 0.78 4.36 (3.87–4.86) 0.32 4.84 (4.22–5.46) 0.79 0.30
GA −5.22 (−5.86 to −4.57) −6.37 (−7.23 to −5.23) 4.46 (3.86–5.06) 4.83 (4.16–5.50)
AA −4.38 (−6.03 to −2.73) −5.21 (−7.09 to −3.33) 2.98 (1.47–4.49) 5.20 (3.56–6.83)
rs5368 CC −5.93 (−6.58 to −5.27) 0.01 −5.36 (−6.16 to −4.56) 0.11 0.59 4.44 (3.92–4.97) 0.14 4.85 (4.19–5.51) 0.65 0.14
CT −5.18 (−5.87 to −4.49) −6.40 (−7.33 to −5.48) 4.30 (3.67–4.93) 4.74 (4.00–5.49)
TT −3.59 (−5.38 to −1.80) −5.81 (−7.96 to −3.66) 2.72 (0.99–4.45) 5.81 (3.92–7.70)
rs3917423 CC −4.72 (−5.56 to −3.88) 0.002 −6.10 (−7.11 to −5.08) 0.05 0.0003b 3.87 (3.15–4.59) 0.45 5.09 (4.27–5.92) 0.33 0.25
CT −5.29 (−5.91 to −4.67) −6.09 (−6.85 to −5.33) 4.58 (4.06–5.11) 4.90 (4.28–5.53)
TT −6.64 (−7.49 to −5.78) −4.81 (−5.78 to −3.85) 4.24 (3.51–4.97) 4.54 (3.73–5.35)
rs1534904 GG −5.00 (−5.60 to −4.41) 0.02 −5.86 (−6.64 to −5.09) 0.22 0.007 4.04 (3.52–4.56) 0.25 4.93 (4.29–5.66) 0.34 0.13
GT −5.85 (−6.53 to −5.17) −5.96 (−6.79 to −5.12) 4.69 (4.10–5.29) 4.91 (4.25–5.57)
TT −6.53 (−8.13 to −4.93) −4.16 (−5.65 to −2.68) 4.18 (3.10–5.25) 3.91 (2.55–5.27)
rs3917412 GG −5.14 (−5.74 to −4.54) 0.04 −5.93 (−6.69 to −5.18) 0.13 0.78 4.11 (3.60–4.61) 0.27 4.90 (4.28–5.52) 0.44 0.18
GA −5.70 (−6.36 to −5.04) −5.86 (−6.70 to −5.02) 4.60 (4.00–5.20) 4.95 (4.28–5.62)
AA −6.96 (−8.76 to −5.16) −3.97 (−5.46 to −2.48) 4.42 (3.18–5.65) 3.81 (2.26–5.37)
rs3917406 CC −4.69 (−5.54 to −3.83) 0.01 −5.85 (−6.89 to −4.81) 0.07 0.002 3.72 (2.97–4.46) 0.37 5.03 (4.15–5.90) 0.56 0.30
CT −5.50 (−6.14 to −4.85) −6.00 (−6.79 to −5.21) 4.52 (3.95–5.09) 4.95 (4.27–5.64)
TT −6.47 (−7.49 to −5.44) −4.52 (−5.52 to −3.53) 4.12 (3.33–4.92) 4.65 (3.75–5.56)
rs932307 AA −4.71 (−5.54 to −3.88) 0.005 −5.96 (−7.00 to −4.92) 0.08 0.002 3.58 (2.89–4.26) 0.14 4.88 (4.05–5.71) 0.58 0.22
AG −5.63 (−6.29 to −4.96) −6.15 (−6.96 to −5.34) 4.69 (4.14–5.24) 4.89 (4.25–5.54)
GG −6.52 (−7.48 to −5.57) −4.72 (−5.76 to −3.69) 4.24 (3.42–5.06) 4.54 (3.68–5.41)
Diastolic blood pressure
DDAH1 rs11161637 AA −2.76 (−3.13 to −2.20) 0.002 −3.02 (−3.60 to −2.44) 0.27 0.18 1.44 (0.97–1.90) 0.09 2.56 (2.01–3.11) 0.01 0.54
AG −1.94 (−2.49 to −1.38) −2.74 (−3.38 to −2.09) 0.91 (0.32–1.49) 1.69 (1.07–2.31)
GG −0.86 (−2.05 to 0.34) −2.26 (−3.87 to −0.64) 0.68 (−0.51 to 1.86) 1.54 (0.10–2.99)
SELE rs3917436 GG −1.83 (−2.47 to −1.20) 0.007 −3.25 (−3.94 to −2.55) 0.23 0.005 1.30 (0.72–1.89) 0.52 2.35 (1.68–3.01) 0.81 0.88
GA −2.30 (−2.82 to −1.78) −2.61 (−3.23 to −1.99) 1.20 (0.71–1.68) 1.95 (1.37–2.54)
AA −3.35 (−4.22 to −2.48) −2.76 (−3.62 to −1.90) 0.98 (0.16–1.79) 2.33 (1.47–3.19)
rs5356 TT −2.90 (−3.44 to −2.35) 0.0002 −2.65 (−3.26 to −2.03) 0.24 0.0004b 1.35 (0.88–1.83) 0.11 2.17 (1.57–2.76) 0.98 0.26
TC −1.90 (−2.47 to −1.33) −3.10 (−3.75 to −2.45) 1.16 (0.59–1.73) 2.12 (1.52–2.72)
CC −0.58 (−1.89 to 0.74) −3.07 (−4.47 to −1.67) 0.10 (−1.04 to 1.25) 2.23 (0.97–3.50)
rs3917430 CC −2.96 (−3.54 to −2.39) 0.0005 −2.56 (−3.19 to −1.94) 0.08 0.0002b 1.35 (0.84–1.86) 0.28 2.15 (1.54–2.75) 0.62 0.96
CG −1.95 (−2.50 to −1.39) −3.04 (−3.68 to −2.40) 1.11 (0.56–1.65) 2.02 (1.44–2.60)
GG −1.08 (−2.17 to 0.02) −3.49 (−4.69 to −2.28) 0.79 (−0.15 to 1.73) 2.76 (1.49–4.03)
rs3917428 GG −2.89 (−3.43 to −2.35) 0.0002 −2.62 (−3.22 to −2.01) 0.22 0.0004b 1.37 (0.89–1.85) 0.09 2.10 (1.52–2.67) 0.80 0.15
GA −1.92 (−2.49 to −1.35) −3.18 (−3.83 to −2.52) 1.14 (0.57–1.71) 2.22 (1.60–2.83)
AA −0.57 (−1.87 to 0.73) −2.87 (−4.22 to −1.52) 0.09 (−1.03 to 1.21) 2.15 (0.90–3.40)
rs5368 CC −3.03 (−3.57 to −2.49) 0.0003 −2.73 (−3.35 to −2.11) 0.12 0.18 1.37 (0.85–1.90) 0.21 2.21 (1.60–2.82) 0.68 0.17
CT −2.10 (−2.72 to −1.48) −3.36 (−4.06 to −2.67) 1.26 (0.67–1.85) 2.25 (1.58–2.92)
TT −0.21 (−1.74 to 1.31) −3.39 (−5.04 to −1.73) 0.14 (−1.12 to 1.39) 2.68 (1.18–4.18)
rs3917423 CC −1.73 (−2.42 to −1.04) 0.004 −3.02 (−3.75 to −2.28) 0.52 0.009 1.08 (0.46–1.69) 0.97 2.36 (1.64–3.07) 0.70 0.77
CT −2.20 (−2.74 to −1.67) −2.85 (−3.45 to −2.24) 1.29 (0.80–1.79) 2.04 (1.45–2.62)
TT −3.21 (−3.97 to −2.46) −2.71 (−3.51 to −1.91) 1.08 (0.38–1.78) 2.17 (1.41–2.93)
rs1534904 GG −1.97 (−2.48 to −1.45) 0.05 −3.15 (−3.72 to −2.57) 0.02 0.002 1.05 (0.59–1.51) 0.74 2.29 (1.72–2.86) 0.43 0.56
GT −2.72 (−3.30 to −2.15) −2.67 (−3.34 to −2.01) 1.44 (0.90–1.98) 1.97 (1.34–2.61)
TT −2.59 (−3.66 to −1..52) −1.92 (−3.00 to −0.84) 0.77 (−0.43 to 1.96) 2.05 (0.83–3.27)
rs3917412 GG −2.01 (−2.51 to −1.51) 0.06 −3.26 (−3.82 to −2.70) 0.003 0.0006b 1.13 (0.67–1.59) 0.80 2.37 (1.82–2.92) 0.17 0.22
GA −2.71 (−3.30 to −2.11) −2.51 (−3.19 to −1.83) 1.28 (0.73–1.84) 1.90 (1.25–2.54)
AA −2.69 (−3.90 to −1.47) −1.69 (−2.85 to −0.52) 1.09 (−0.17 to 2.36) 1.78 (0.38–3.18)
rs3917406 CC −1.95 (−2.64 to −1.25) 0.007 −3.27 (−4.07 to −2.46) 0.39 0.009 1.28 (0.64–1.92) 0.66 2.60 (1.81–3.39) 0.64 0.79
CT −2.05 (−2.61 to −1.48) −2.88 (−3.54 to −2.22) 1.16 (0.64–1.68) 2.12 (1.49–2.75)
TT −3.53 (−4.41 to −2.65) −2.82 (−3.68 to −1.96) 1.06 (0.27–1.86) 2.38 (1.54–3.21)
rs932307 AA −1.63 (−2.31 to −0.95) 0.002 −3.12 (−3.91 to −2.34) 0.34 0.003 0.91 (0.31–1.52) 0.58 2.33 (1.57–3.08) 0.68 0.53
AG −2.34 (−2.90 to −1.77) −2.64 (−3.27 to −2.00) 1.26 (0.76–1.76) 1.99 (1.40–2.58)
GG −3.38 (−4.22 to −2.53) −2.66 (−3.49 to −1.82) 1.14 (0.35–1.93) 2.13 (1.34–2.92)
Mean arterial pressure
DDAH1 rs11161637 AA −3.95 (−4.47 to −3.44) 1.19×10−5 −3.94 (−4.49 to −3.38) 0.47 0.008 2.54 (2.12–2.97) 0.03 3.43 (2.90–3.97) 0.02 0.84
AG −2.89 (−3.40 to −2.38) −3.76 (−4.38 to −3.15) 1.85 (1.33–2.37) 2.60 (2.04–3.16)
GG −1.33 (−2.53 to −0.13) −3.45 (−5.00 to −1.89) 1.74 (0.64–2.84) 2.68 (1.44–3.93)
SELE rs3917436 GG −2.79 (−3.40 to −2.17) 0.002 −4.18 (−4.85 to −3.50) 0.13 0.001b 2.20 (1.66–2.73) 0.79 3.20 (2.57–3.84) 0.74 0.89
GA −3.39 (−3.88 to −2.91) −3.72 (−4.32 to −3.13) 2.35 (1.91–2.79) 2.94 (2.40–3.47)
AA −4.44 (−5.26 to −3.61) −3.47 (−4.30 to −2.64) 2.00 (1.28–2.72) 3.10 (2.31–3.88)
rs5356 TT −3.88 (−4.39 to −3.37) 0.0009 −3.58 (−4.18 to −2.98) 0.18 0.0005b 2.35 (1.93–2.78) 0.14 3.08 (2.52–3.63) 0.98 0.48
TC −2.97 (−3.50 to −2.45) −4.17 (−4.78 to −3.56) 2.25 (1.74–2.77) 2.99 (2.44–3.53)
CC −1.96 (−3.23 to −0.68) −3.90 (−5.32 to −2.48) 1.12 (−0.04 to 2.27) 3.29 (2.09–4.50)
rs3917430 CC −3.95 (−4.50 to −3.40) 0.002 −3.44 (−4.04 to −2.83) 0.05 0.0002b 2.37 (1.92–2.82) 0.25 3.05 (2.49–3.61) 0.61 0.88
CG −3.02 (−3.52 to −2.51) −4.18 (−4.79 to −3.58) 2.19 (1.71–2.68) 2.92 (2.39–3.46)
GG −2.30 (−3.45 to −1.15) −4.20 (−5.39 to −3.00) 1.72 (0.76–2.68) 3.63 (2.40–4.87)
rs3917428 GG −3.86 (−4.37 to −3.35) 0.001 −3.55 (−4.14 to −2.96) 0.18 0.0005b 2.37 (1.94–2.79) 0.11 3.01 (2.48–3.55) 0.78 0.15
GA −3.02 (−3.56 to −2.49) −4.25 (−4.86 to −3.63) 2.25 (1.74–2.77) 3.08 (2.51–3.65)
AA −1.85 (−3.12 to −0.58) −3.64 (−5.02 to −2.27) 1.06 (−0.06 to 2.18) 3.17 (1.95–4.38)
rs5368 CC −4.00 (−4.52 to −3.48) 0.0004 −3.61 (−4.22 to −3.00) 0.08 0.0001b 2.39 (1.94–2.85) 0.15 3.09 (2.51–3.66) 0.66 0.12
CT −3.13 (−3.70 to −2.56) −4.38 (−5.05 to −3.71) 2.28 (1.74–2.82) 3.09 (2.51–3.66)
TT −1.35 (−2.80 to 0.10) −4.19 (−5.86 to −2.51) 1.00 (−0.30 to 2.29) 3.08 (2.44–3.71)
rs3917423 CC −2.73 (−3.39 to −2.06) 0.001 −4.05 (−4.77 to −3.32) 0.18 0.0007b 2.01 (1.43–2.59) 0.75 3.28 (2.60–3.95) 0.48 0.49
CT −3.24 (−3.73 to −2.75) −3.93 (−4.50 to −3.36) 2.39 (1.95–2.83) 2.99 (2.45–3.53)
TT −4.36 (−5.06 to −3.65) −3.41 (−4.17 to −2.65) 2.13 (1.50–2.76) 2.96 (2.26–3.65)
rs1534904 GG −2.98 (−3.47 to −2.50) 0.02 −4.06 (−4.61 to −3.50) 0.04 0.001b 2.05 (1.62–2.47) 0.48 3.17 (2.63–3.71) 0.33 0.19
GT −3.77 (−4.30 to −3.24) −3.77 (−4.41 to −3.13) 2.53 (2.04–3.02) 2.95 (2.37–3.52)
TT −3.92 (−5.05 to −2.78) −2.68 (−3.77 to −1.59) 1.90 (0.91–2.89) 2.67 (1.57–3.77)
rs3917412 GG −3.06 (−3.53 to −2.59) 0.03 −4.15 (−4.69 to −3.62) 0.007 0.0004b 2.12 (1.70–2.54) 0.53 3.21 (2.69–3.73) 0.19 0.14
GA −3.71 (−4.25 to −3.17) −3.63 (−4.29 to −2.97) 2.39 (1.89–2.89) 2.91 (2.32–3.50)
AA −4.12 (−5.41 to −2.84) −2.46 (−3.59 to −1.33) 2.20 (1.12–3.29) 2.47 (1.21–3.73)
rs3917406 CC −2.86 (−3.52 to −2.19) 0.004 −4.13 (−4.89 to −3.37) 0.16 0.002b 2.10 (1.49–2.70) 0.97 3.40 (2.67–4.13) 0.60 0.56
CT −3.21 (−3.73 to −2.69) −3.92 (−4.55 to −3.29) 2.28 (1.81–2.76) 3.05 (2.47–3.64)
TT −4.51 (−5.36 to −3.66) −3.39 (−4.19 to −2.59) 2.08 (1.39–2.78) 3.15 (2.41–3.89)
rs932307 AA −2.66 (−3.31 to −2.01) 0.0008 −4.07 (−4.81 to −3.32) 0.14 0.0005b 1.80 (1.25–2.35) 0.32 3.18 (2.49–3.87) 0.60 0.34
AG −3.44 (−3.89 to −2.90) −3.81 (−4.43 to −3.19) 2.40 (1.95–2.86) 2.95 (2.39–3.50)
GG −4.43 (−5.23 to −3.63) −3.35 (−4.15 to −2.55) 2.17 (1.46–2.88) 2.94 (2.22–3.65)
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Abbreviations: CI, confidence interval; COL18A1, collagen, type XVIII, alpha 1; DDAH1, dimethylarginine dimethylaminohydrolase 1; HGNC, Human Genome Nomenclature Committee; VWF, von Willebrand factor.

a P value for genotype–sex interaction.

bFalse discovery rate Q < 0.05.

DISCUSSION

This study identified several novel genetic variants in the endothelial system that may have important influences on BP salt sensitivity. The number of copies of the G allele of rs11161637 in the DDAH1 gene was associated with decreased SBP and MAP responses to low-sodium intake. Examination of genotype–sex interaction revealed that these findings were likely driven by the strong associations observed in men. In addition, the C allele of VWF marker rs2239153 was related to increased DBP and MAP responses to low-sodium interventions in the overall analysis, whereas the COL18A1 rs2838944 A variant was related to attenuated DBP and MAP responses to high-sodium intake. Further, genotype–sex interactions were also observed for 3 independent loci within the SELE gene. These findings could have important public health and clinical implications. Compared with common variants that have been reported previously for other BP-related traits, variants identified in our main analysis each explained a relatively large proportion of the variation in the BP salt-sensitivity phenotypes (ranging 0.5%–2.1%). These results highlight the potential utility of examining intermediate phenotypes in genomic study. Furthermore, by providing strong evidence of genotype–sex interactions, our findings suggest a genomic explanation for observed sex differences in this complex trait.

Encoding one of the major endothelium-derived vasoactive mediators, the DDAH1 gene is implicated in BP salt sensitivity because of its influence on NO production through the regulation of asymmetrical dimethylarginine (ADMA).21 ADMA, which has been shown to increase after salt loading, is inversely associated with NO synthesis and BP.22–24 DDAH1 metabolizes ADMA to L-citrulline and dimethylamine, playing a key role in the determination of in vivo ADMA concentration.25 Although previous studies have not implicated DDAH1 gene variants in the pathogenesis of salt sensitivity, DDAH1 variants have been associated with ADMA concentrations and the increased risk of important BP-related traits, including chronic kidney disease, CVD, and thrombotic stroke.26–28 The minor G allele of novel marker rs11161637, which lies in an intronic region of the DDAH1 gene, was associated with decreased BP salt sensitivity in this study. This association was likely driven by the very strong association observed in men. Interestingly, Caplin and colleagues also noted a potential DDAH1–sex interaction in their analysis of plasma ADMA levels.28 Because there is little evidence for regulatory action or conservation of rs11161637 across species, it is unlikely that it is causally associated with salt sensitivity. It is more plausible that the association reflects linkage disequilibrium with a functional but still undiscovered variant. Although we await replication and functional study to elucidate the true nature of the observed relationship, the results provide promising evidence for a role of the DDAH1 gene in salt sensitivity of BP.

VWF is a largely endothelium-derived glycoprotein that is released into the circulation by damaged endothelial cells, promoting coagulation and platelet activation.29 In this study, we observed a significant, positive association between the novel VWF rs2239153 variant and BP responses to sodium intake. Although we are the first to identify such an association, Ferri and colleagues showed that plasma levels of the VWF glycoprotein were significantly elevated among those with salt-sensitive hypertension compared with those with salt-resistant hypertension.30 Furthermore, VWF gene polymorphisms have been associated with hypertension in past studies,31,32 making it a logical candidate for genetic study of salt sensitivity. Marker rs2239153 represents a common, intronic SNP in the VWF gene with unknown functional effects. Future replication studies are needed to validate the observed association, whereas sequencing and functional studies will be required to pinpoint the true causal variant underlying this relationship.

COL18A1 encodes a potent antiangiogenic protein,33 with its deficiency related to altered matrix remodeling, enhanced inflammatory response, and vascular endothelial cell damage.34 Further, the degradation of COL18A1 results in the generation of endostatin, which has been implicated in BP regulation because of its vasorelaxing effect.35,36 Despite physiological evidence for a role of COL18A1 in BP, to the knowledge of the authors, there have been no studies examining the association between COL18A1 gene variants and BP-related phenotypes. In this study, we identified an inverse dose–allele relationship between the intronic COL18A1 rs2838944 A variant and BP responses to the dietary sodium intervention, demonstrating a potentially important influence of COL18A1 on BP salt sensitivity.

We also identified 3 independent loci within the SELE gene that interacted with sex to influence BP salt sensitivity. Encoding a component of the selectin family of cell adhesion molecules, SELE is expressed in cytokine-stimulated endothelial cells and is thought to be involved in the pathogenesis of atherosclerosis.37,38 Although not previously associated with BP salt sensitivity, other studies have reported a role for SELE in BP regulation and hypertension.37,38 In addition, significant SELE–sex interactions on hypertension were reported in a separate study of Chinese participants.37 Although some follow-up work is warranted, these findings highlight the importance of considering gene–environment interaction in the context of BP salt sensitivity.

To date, GenSalt is the largest dietary intervention study to examine the association between genetic variants in the endothelial system and BP response to dietary sodium intervention. Furthermore, study attributes, including the recruitment of all Han Chinese participants, should make the analysis robust to population stratification. Participation in the dietary intervention was high, and compliance, as assessed by urinary excretion of sodium and potassium, was excellent. In addition, stringent quality control procedures were employed during the BP measurements, collection of other study variables, conduction of the dietary interventions, genotyping, and marker data cleaning. Compared with previous reports of common BP-associated variants, the SNPs identified in this study explained a relatively large proportion of the variation in the BP salt-sensitivity phenotypes.39 There are several potential explanations for these findings. As an intermediate BP phenotype, genetic heterogeneity may be reduced, decreasing the total phenotypic variance due to genomic factors. In addition, the study participants were similar with respect to lifestyle and environmental risk factors. These study attributes, along with the controlled dietary intake of sodium, decreased phenotypic variance due to environmental factors. Moreover, the multiple BP readings obtained on multiple days reduced the measurement errors, decreasing phenotypic variance due to random error. Finally, because of the “winner’s curse,” it is also possible that these findings represent an overestimate of the true proportion of variation explained by these SNPs. Therefore, caution is warranted in generalizing these findings beyond that of the current sample. Because our research was conducted in a Han Chinese population, the findings may not be generalizable to populations with distinct linkage disequilibrium structure. Finally, although the Affymetrix 6.0 platform generally provides good genomic coverage of common polymorphisms in the Han Chinese population (approximately 75%),3 limited genotype data were available for the EDN2, CYBA, and TGFB1 genes (see Supplementary Table S1). Therefore, future research to examine the association between common variants in these genes and BP salt sensitivity is still needed.

Our study is the first to associate endothelial system genes DDAH1, VWF, COL18A1, and SELE with BP salt sensitivity. Despite these promising results, further follow-up work is needed. Replication studies will be necessary to validate the novel associations reported here. Furthermore, sequencing and functional studies to pinpoint the causal variants underlying these relationships are warranted.

SUPPLEMENTARY MATERIAL

Supplementary materials are available at American Journal of Hypertension (http://ajh.oxfordjournals.org/).

DISCLOSURE

The authors declared no conflict of interest.

ACKNOWLEDGMENTS

The Genetic Epidemiology Network of Salt Sensitivity (GenSalt) is supported by a cooperative agreement project grant (U01HL072507, R01HL087263, and R01HL090682) from the National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD. Dr. Kelly was supported by American Heart Association award number 11SDG5130026.

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