Blood Pressure and Renal Sodium Handling in Relation to Genetic Variation in the DRD1 Promoter and GRK4
Activation of type-1 dopamine receptors (DRD1) reduces renal sodium reabsorption. In a family-based random sample of 611 untreated whites (women, 45.0%; mean age, 38.6 years), we measured blood pressure (BP). We used the endogenous lithium clearance to assess fractional sodium excretion (FENa) and proximal (RNaprox) and distal (RNadist) tubular sodium reabsorption. We investigated multivariate-adjusted associations with the DRD1 promoter (A−48G, G−94A, and C−800T) and GRK4 (Ala142Val). The frequent DRD1 haplotypes were AGC (48.2%), GGT (34.4%), and AAC (14.3%). While standardizing to mean sodium excretion (8.7 mmol/h) and adjusting for covariates and relatedness, RNadist was lower in DRD1 −94GG homozygotes than −94A allele carriers (effect size, −0.94%; P=0.005) with opposite findings for FENa (+0.084%; P=0.014). AGC carriers (−0.88%; P=0.012) and AAC carriers (+1.00%; P=0.004) had different RNadist compared to corresponding noncarriers. Furthermore, FENa was lower in AAC carriers than in noncarriers (−0.082%; P=0.019). The family-based analyses identified a significant between-family component in the variance of the renal phenotypes associated with the DRD1 polymorphisms. Transmission of the DRD1 AGC haplotype was also associated with lower systolic (−3.54 mm Hg; P=0.016) and diastolic (−2.80 mm Hg; P=0.0064) BPs without significant between-family variance component. Plasma renin activity and urinary aldosterone excretion were not associated with DRD1 variation. The GRK4 Ala142Val polymorphism did not contribute to the phenotypes under study. In conclusion, renal sodium handling and BP were associated with genetic variation in the DRD1 promoter. The between-family variance component excluded population stratification for BP, but not for the renal phenotypes.
- blood pressure
- clinical genetics
- dopamine receptor gene
- lithium clearance
- population science
- tubular transport
Dopamine reduces sodium reabsorption in the proximal renal tubules via activation of dopamine type-1 (DRD1) receptors, which leads to inhibition of sodium transporters, including the Na,H-exchanger and Na,K-ATPase.1 The DRD1 promoter harbors several single-nucleotide polymorphisms (SNPs),2 which influence the expression of the gene. Dopamine exerts its actions via G protein–coupled receptors, which in turn are under control of G protein–coupled receptor kinases (GRKs).1 Amino-acid changing polymorphisms in one particular member of this family, GRK4, cause hyperphosphorylation, desensitization, and internalization of the DRD1 receptor and enhance the expression of the angiotensin II type-1 receptor.1 The genes encoding DRD1 and GRK4 localize to chromosomes 5q35.13 and 4p16.3,4 respectively. The GRK4 gene locus is embedded in a cluster on chromosome 4p16, which is associated with hypertension5,6 and also includes α-adducin (ADD1). To our knowledge, there are no studies showing significant genome-wide linkage of hypertension with the DRD1 locus, although a genome-scan meta-analysis7 identified 5q as a suggestive region.
Measuring the clearance of endogenous lithium provides a way of estimating sodium handling in the proximal and postproximal nephron.8,9 Expressing the renal clearance of endogenous lithium as a fraction of creatinine clearance provides a measure of tubular sodium reabsorption that is standardized for the glomerular filtration rate.8,9 The fractional excretion of lithium (FELi) is a noninvasive marker of proximal tubular sodium handling and the proportion of sodium escaping reabsorption in the proximal segment of the nephron. FELi also allows the calculation of the fractional distal reabsorption of sodium (RNadist). To our knowledge, no prior study addressed the possible association of these renal measurements with genetic variation in the DRD1 promoter and GRK4. We studied these associations in a family-based random sample of a white population.
We invited 1507 participants of the Flemish Study on Environment, Genes and Health Outcomes (FLEMENGHO)10,11 for a measurement of the clearance of endogenous lithium (for details, see the expanded Methods section available in the online data supplement at http://hyper.ahajournals.org). All participants or their parents provided informed consent to a protocol, which the University of Leuven Ethics Committee had approved.
Of 806 subjects willing to participate (53.5%), we excluded 195. Two subjects did not have all measurement required to compute the clearances, and 5 had a lithium concentration in serum (≥1.0 μmol/L) or urine (≥20 μmol/L) suggestive of external contamination. We excluded 170 subjects, because they were on medications, which affect blood pressure or the activity of the renin-angiotensin-aldosterone system, such as antihypertensive drugs (n=101), oral contraceptives (n=62), or hormonal replacement therapy (n=7). We removed 10 subjects, whose DNA failed to amplify and 8 with errors in Mendelian segregation. Thus, the number of subjects statistically analyzed totaled 611.
Trained nurses administered a questionnaire to collect information about the participants’ smoking and drinking habits, and intake of medications. Blood pressure was the average of 5 consecutive readings obtained at the examination center after the subjects had rested for at least 10 minutes in the sitting position. Mean arterial pressure was diastolic pressure plus one third of pulse pressure. Hypertension was a blood pressure of at least 140 mm Hg systolic or 90 mm Hg diastolic. Body mass index was weight in kilograms divided by the square of height in meters.
Renal Sodium Handling
The participants gave a venous blood sample and collected an exactly timed urine sample over 4 to 6 hours. We determined plasma renin activity (RIA-0180, DRG Instruments GmbH) and urinary aldosterone (DSL-8600 Active, Diagnostic Systems Laboratories Inc) by radioimmunoassay. Endogenous trace lithium was measured with an electrothermal atomic absorption spectrophotometer (model AAS 300) with a HGA-700 graphite furnace (Perkin-Elmer Inc).12
Clearances (C) were calculated as Cx=Ux×V/Px, where Ux and Px are the urinary and plasma concentrations of the solute x, and V is the urine flow rate in milliliters per minute.8,9 We computed the fractional excretion of sodium (FENa) and lithium (FELi) by dividing the sodium (CNa) and lithium (CLi) clearances by the creatinine clearance.8,9 We expressed these ratios as a percentage. Fractional distal reabsorption of sodium (RNadist) was estimated as [(FELi−FENa)/FELi]×100. RNadist is a measure of the amount sodium that escapes reabsorption in the proximal tubules and is reabsorbed in the postproximal tubules.8,9 We defined the fractional proximal sodium reabsorption (RNaprox) as 100−FELi.8,9
We extracted genomic DNA from white blood cells, using standard kits (Qiagen). As described in the expanded Methods section, we genotyped DRD1 for the promoter polymorphisms A−48G, G−94A, and C−800T, and GRK4 for C+583T (Ala142Val).
We used SAS software (SAS Institute), version 9.1.3. We normalized the distributions of plasma renin activity and the urinary aldosterone excretion by a logarithmic transformation. We compared means and proportions, using the large sample z-test and Fisher exact test, respectively.
Our statistical methods also included single and multiple linear regressions. We included in our models covariates with known physiological relevance in relation to the phenotypes under study. We additionally searched for possible covariates of the phenotypes, using stepwise multiple regressions with the probability value for independent variables to enter and stay in the model set at 0.15. For analysis, we combined women and men, because the interaction terms between explanatory variables and sex were nonsignificant (P>0.15). We standardized FENa, RNaprox and RNadist to the mean sodium excretion rate for the whole study population (8.7 mmol/h), because there is a linear correlation between these renal measurements and urinary sodium excretion.9 We applied the formula Ps=Po−β(ENao−8.7), where Ps is the standardized parameter, Po the observed value, and β the regression coefficient relating the indexes of renal sodium handling to the observed sodium excretion rate (ENao).9
For analysis of single SNPs, we combined the least frequent homozygous group with the heterozygous subjects. We tested linkage disequilibrium and reconstructed haplotypes, using the SAS procedures PROC ALLELE and PROC HAPLOTYPE. We applied a generalization of the standard linear model as implemented in the PROC MIXED procedure of the SAS package to test the associations between phenotypes and SNPs or haplotypes, while accounting for the nonindependence of phenotypes within families and adjusting for covariates.
In quantitative transmission disequilibrium tests (QTDT), we partitioned the phenotypic variance into between and within family components, using the orthogonal model as implemented in Abecasis’ QTDT software, version 2.4, available at http://www.sph.umich.edu/csg/abecasis/QTDT).13 The within-family component of phenotypic variance reflects the genetic effect and is robust to population stratification.13
Characteristics of the Participants
The study population consisted of 573 relatives from 53 families and 38 unrelated individuals. Of the 53 families, 10, 31, and 12 spanned 1, 2, or 3 generations, respectively. Table 1 provides the characteristics of 459 offspring in comparison with the rest of the study population (114 founders and 38 unrelated subjects).
The study sample included 105 (17.2%) untreated hypertensive patients. Of 275 women and 336 men, 65 (23.6%) and 105 (31.3%) were smokers; 121 women (44.0%) and 251 men (74.7%) reported intake of alcohol. In smokers, median tobacco use was 12 cigarettes per day (interquartile range, 7 to 20). In drinkers, the median alcohol consumption was 10 g per day (interquartile range, 4 to 20). Among women, 53 (19.3%) reported natural or surgical menopause. Compared to men, women had lower (P≤0.01) mean values of serum sodium (141.1 versus 143.1 mmol/L), urinary excretion of sodium (7.0 versus 10.2 mmol/h) and lithium (0.16 versus 0.20 μmol/h), and RNadist (93.6 versus 94.3%). Women and men had similar RNaprox (80.7 versus 80.3%; P=0.58) and FENa (0.97 versus 0.98%; P=0.87).
Genotype and Haplotype Frequencies
Table 2 provides genotype and allele frequencies in the population sample for the 3 DRD1 SNPs and the GRK4 C +583T (Ala142Val) polymorphism. The genotypic frequencies did not depart from Hardy-Weinberg proportions (P≥0.17). The 3 DRD1 SNPs were in complete linkage disequilibrium. Lewontin disequilibrium coefficient D′ was >0.99 (P<0.0001). Among the 590 subjects, in whom the 3 DRD1 SNPs were available, the haplotype frequencies were 457 (48.2%) for the combination of −48A, −94G, and −800C (H1-AGC), 406 (34.4%) for −48G, −94G, and −800T (H2-GGT), 169 (14.3%) for −48A, −94A, and −800C (H3-AAC), 6 (0.5%) for −48A, −94G, and −800T (H4-AGT), and 3 (0.25%) for −48G, −94G, and −800C (H5-GGC).
Phenotype-Genotype Associations for SNPs
Both before and after adjustment for sex, age, body mass index, and mean arterial pressure (Table 3), RNadist was significantly lower in −94GG homozygotes than −94A allele carriers (adjusted effect size, −0.94%; 95% confidence interval [CI], −1.60 to −0.29%; P=0.005), whereas the opposite was the case for FENa (+0.084%; CI, +0.017 to +0.151%; P=0.014). FENa also tended to be lower in DRD1 −800CC homozygotes than −800T allele carriers (−0.055%; CI, −0.116 to +0.005; P=0.071). None of the other genotypic differences in the indexes of renal sodium handling reached statistical significance in relation to DRD1 or GRK4 (Table 3). For the DRD1 and GRK4 SNPs under study, the genotypic differences in systolic and diastolic blood pressures (Table 3; P≥0.24), plasma renin activity (P≥0.37) and the aldosterone excretion rate (P≥0.21) were not significant. Covariates considered in these analyses were sex, the linear and squared terms of age, and body mass index for blood pressure; sex, age, body mass index, and mean arterial pressure for plasma renin activity and the urinary aldosterone excretion rate. For plasma renin activity, we additionally entered the time of day of the blood collection into the multivariate model. The gene-gene interaction terms between the DRD1 and GRK4 SNPs did not improve the multivariate-adjusted models for any phenotype (P≥0.21).
Phenotype-Genotype Associations for Haplotypes
Both before and after adjustment (Table 4), H1-AGC carriers (adjusted effect size, −0.88%; CI, −1.55 to −0.21%; P=0.01) and H3-AAC carriers (+1.00%; CI, +0.31 to +1.61%; P=0.004) had different RNadist compared to the corresponding noncarriers. Furthermore, FENa was lower in H3-AAC carriers than in noncarriers (−0.082%; CI, −0.150 to −0.013%; P=0.019). None of the other associations between the indexes of renal sodium handling and the DRD1 haplotypes reached significance (Table 4). The number of subjects carrying 2 copies of the same haplotype was 145 (25.5%) for H1-AGC, 62 (10.9%) for H2-GGT, and 21 (3.7%) for H3-AAC (Figure). We noticed a dose-effect, depending on the number of haplotypes, for H1-AGC in relation to RNadist (P=0.011), and for H3-AAC in relation to RNadist (P=0.003) and FENa (P=0.016).
For the 3 most frequent DRD1 haplotypes, systolic and diastolic blood pressures (Table 4; P≥0.20), plasma renin activity (P≥0.24), and the aldosterone excretion rate (P≥0.09) were similar in carriers and noncarriers. Sensitivity analyses, in which we additionally adjusted for smoking and drinking alcohol produced results, which were not materially different from those shown for the DRD1 and GRK4 SNPs in Table 3 and from those for the DRD1 haplotypes in Table 4 and the Figure. Finally, we did not find any interaction between the DRD1 haplotypes and the GRK4 SNP in relation to the phenotypes (P≥0.05).
We adjusted the QTDT analyses as described above. Transmission of DRD1 or GRK4 alleles from parents to informative offspring was not associated with any difference (P≥0.19) in the indexes of renal sodium handling (number of informative offspring ranging from 112 to 208), blood pressure (112−208), plasma renin activity (100−177), or the aldosterone excretion rate (98−165). For the DRD1 −94G allele in relation to RNaprox (P=0.042) and RNadist (P=0.0026), the between-family component of variance was significant.
Table 5 summarizes the between-family and within-family effect sizes associated with the DRD1 haplotypes. Transmission of H1-AGC was associated with lower systolic (−3.54 mm Hg; P=0.016) and diastolic (−2.80 mm Hg; P=0.019) blood pressures without evidence for a significant between-family component in the variance (P≥0.28). On the other hand, RNaprox and RNadist were not associated with transmission of the DRD1 haplotypes (P≥0.26), but the between-family effect sizes were significant for RNaprox in relation to H1-AAC (P=0.009) and for RNadist in relation to H1-AGC (P=0.012) and H3-AAC (P=0.0009). The within-family (P≥0.40) and between-family (P≥0.08) effect sizes for plasma renin activity and the aldosterone excretion rate in relation to the DRD1 haplotypes were not significant.
The key finding of our study was that RNadist was significantly lower in DRD1 −94GG homozygotes than −94A allele carriers, whereas the opposite was true for FENa. RNadist varied with the DRD1 H1-AGC and H3-AAC haplotypes. FENa was lower in H3-AAC carriers than in noncarriers. Furthermore, transmission of the H1-AGC haplotype was associated with lower systolic and diastolic blood pressure. We did not find any significant interaction of the DRD1 SNPs or haplotypes with the GRK4 SNP in relation to the studied phenotypes.
In the family-based analyses, we partitioned association effects into between-family and within-family components. The within-family effects are free of confounding by population-substructure effects, regardless of the composition of families.13 The between-family effects estimate to what extent associations are attributable to population stratification or admixture. In the QTDT analyses, we noticed significant between-family effects for the renal phenotypes, but not for blood pressure. This suggests that in the population-based analyses, in which we also accounted for relatedness, population stratification might have contributed to the association of the renal phenotypes with the DRD1 polymorphisms, whereas this was not the case for blood pressure in the family-based analyses.
The role of the DRD1 receptor in the regulation of blood pressure is well established.1 Stimulation of DRD1 by fenoldopam, a D1-like agonist, decreases blood pressure,14 whereas inhibition of DRD1 by ecopipam, a long-acting DRD1 antagonist, has the opposite effect.15 Furthermore, DRD1 knock-out mice have an elevated blood pressure.16 However, previous studies2,17,18 on the possible influence of variation in DRD1 on blood pressure yielded inconsistent results. Beige and coworkers genotyped the A−48G and G−94A polymorphisms in 493 hypertensive patients and 209 normotensive controls,2 but these 2 SNPs were not associated with hypertension or blood pressure. In a study involving 407 black and 505 white normotensive twins with mean age of 17.4 years, Lu and colleagues17 found that −48G allele carriers, compared with −48AA homozygotes, had a significantly lower diastolic blood pressure at rest (58.7 versus 59.6 mm Hg, P=0.032) and during a car driving simulation test (66.3 versus 67.5 mm Hg, P=0.046). However, the sib-pair transmission disequilibrium test, involving 39 informative twin pairs for A−48G, did not reveal any significant association with systolic or diastolic blood pressure.17 In a Japanese study18 of 131 hypertensive patients and 136 normotensive controls, the allele frequencies of A−48G substantially deviated from those observed in whites, amounting to 0.92/0.08 in the normotensive controls and 0.84/0.16 in the hypertensive patients. In this study,18 the DRD1 −48G allele was more frequent in hypertensive patients than normotensive controls.18 Moreover, among untreated hypertensive patients, −48G allele carriers had a higher diastolic blood pressure than −48AA homozygotes.18
In the current study, we observed that RNadist, but not RNaprox, was associated with variation in the DRD1 gene. Most experimental and clinical studies suggest that DRD1 primarily affects proximal tubular sodium reabsorption.1 Selective DRD1 stimulation induces natriuresis via inhibition of sodium reabsorption in the proximal convoluted tubules.19,20 However, the kidney expresses DRD1 not only in the proximal tubules, but also in the medullary ascending limb of Henle, and in the medullary and cortical collecting ducts.21,22 In the current study population, we previously demonstrated an inverse relation between RNaprox and mean arterial pressure.9 In line with these findings,9 the current analyses of the DRD1 haplotypes H1-AGC and H3-AAC showed opposite trends in blood pressure and RNAprox. It is therefore possible that, along with the variation in the DRD1 gene, pressure-natriuresis can compensate for the proximal genetic effects on sodium reabsorption. The alternative hypothesis is that variation in the DRD1 gene might have extrarenal effects on blood pressure with secondary changes in proximal tubular sodium handling. Finally, in humans, juxtaglomerular cells do not express DRD1,23 and selective D1-like receptor stimulation has no significant effects on plasma renin activity.24 In keeping with our current findings, in the aforementioned Japanese study,18 plasma renin activity and the plasma aldosterone concentration were not associated with the DRD1 genotype in 90 untreated hypertensive patients.
In the population-based analyses, we noticed that FENa differed across the DRD1 SNPs and haplotypes. Although there is high intraindividual variability in sodium excretion, means are accurate to reflect the average salt intake of a group.25 On the assumption that our participants were in dietary balance, our findings suggest that genetic variability in DRD1 might influence salt intake. In previous studies, we also noticed that the 24-hour urinary sodium excretion differed according to the combination of ADD1 (Gly460Trp) and ACE (I/D) genotypes10 or according to the β-adducin (ADD2 C1797T) polymorphism.26 Like DRD1, ADD1, ADD2, and ACE are involved in sodium homeostasis. Genetic factors stimulating sodium retention lead to inhibition of the renin system and to a decreased systemic or local generation of angiotensin II, a major endocrine and paracrine factor driving salt appetite. Moreover, under certain conditions,27,28 dopamine receptors participate in the regulation of salt appetite, although the evidence favors DRD2 over DRD1.28
GRK4 is expressed in the nephron segments of the kidney, where sodium transport is regulated by dopamine and angiotensin II.1 The allelic variant C+583T (GCC to GTC) results in amino acid substitution Ala142Val, and is associated with a constitutive increase in GRK4 kinase activity in proximal tubular cells from humans with essential hypertension.29 This variant in the γ isoform of GRK4, when expressed heterologously in Chinese hamster ovary cells29 but not in HEK-293 cells,30 increased the phosphorylation of DRD1 and impaired its ability to stimulate cAMP production. Reducing the activity of GRK4 with heparin or GRK4 antisense oligonucleotides in proximal tubular cells from normotensive humans with the wild-type GRK4 did not affect DRD1 function, but it restored DRD1 responsiveness in proximal tubular cells from hypertensive patients carrying GRK4 mutants.29,31 GRK4 does not cause desensitization of the angiotensin II type-1 receptor,32 but might actually increase its expression.1
Evidence for an association between blood pressure and genetic variation in GRK4 comes from a study in 503 Chinese hypertensive patients and 490 sex- and age-matched controls33 and from a twin study of 934 black (44.2%) and white (55.8) normotensive American adolescents.34 In a study of 184 newly diagnosed and untreated hypertensive Japanese,35 mutation of GRK4 reduced the natriuretic response to dopaminergic stimulation. We did not find any association of blood pressure and renal sodium handling with GRK4 or the interaction between GRK4 and DRD1. There are major ethnic differences in the GRK4 allele frequencies.36 Previous studies included Asians33,35 and black34 subjects. Furthermore, the phenotype-genotype associations with GRK4 might not occur in the absence of dopaminergic stimulation or at a very high sodium intake, as observed in our study (209 mmol/d).
The present study has potential limitations. First, salt intake is an important determinant of renal sodium handling. In population studies, salt intake is highly variable. We therefore standardized our analyses to the mean sodium excretion rate. However, analyses not standardized or not adjusted for sodium excretion showed consistent results (see supplemental information available online at http://hyper.ahajournals.org). Second, measurement of the clearances of sodium and endogenous lithium only allows differentiating between proximal and postproximal renal tubular sodium reabsorption. Third, of 3 known amino-acid changing SNPs in GRK4,1 we only genotyped Ala142Val, but not Arg65Leu and Ala486Val. However, in Whites, Arg65Leu and Ala142Val are in one contiguous haplotype block (pairwise D′=1).36 In all ethnicities, there is high linkage disequilibrium in GRK4 between noncontiguous SNPs.36 In Chinese, among 33 SNPs in 11 candidate genes, Ala142Val was associated with hypertension.33 In Japanese, Ala142Val was as single SNP 78.4% predictive of salt-sensitive hypertension, whereas the other 2 GRK4 SNPs only added 16.0% to the genetic model.35 Experimental studies showed that the Ala142Val variant is functional and leads to a constitutive increase in GRK4 kinase activity.29 Finally, a drawback of the QTDT analysis, which is robust to population stratification,13 is a sizable reduction in sample size because of the exclusion of noninformative allelic transmission from parents to offspring and hence a reduction in statistical power.
To our knowledge, our study is the first to investigate blood pressure and renal sodium handling in relation to DRD1 and GRK4 polymorphisms in a family-based random sample of a white population. We found association of RNadist, FENa, and blood pressure with genetic variation in the DRD1 promoter without significant interaction between the DRD1 and GRK4 polymorphisms. We also noticed opposite trends in the phenotype-genotype associations between the DRD1 H1-AGC and H3-AAC haplotypes. The functional relevance of these haplotypes might therefore be conditional on the presence or absence of the −94G allele. Pending confirmation by further epidemiological and experimental research, our current findings suggest that interference with dopaminergic signaling by modification of DRD1 function37 might be a way of intervening with sodium homeostasis and blood pressure.
The authors gratefully acknowledge the expert technical and secretarial assistance of Sandra Covens, Linda Custers, Marie-Jeanne Jehoul, Katrien Staessen, Hanne Truyens, and Renilde Wolfs (Studies Coordinating Centre, Leuven and Field Examination Centre, Eksel, Belgium).
Sources of Funding
The Flemish Study on Environment, Genes, and Health Outcomes (FLEMENGHO) is part of the European Project on Genes in Hypertension (EPOGH), which is endorsed by the European Council for Cardiovascular Research and the European Society of Hypertension. FLEMENGHO would not have been possible without the voluntary collaboration of the participants and their general practitioners. The municipality Hechtel-Eksel (Belgium) gave logistic support. Research included in the present study was partially funded by the European Union (grants IC15-CT98-0329-EPOGH, LSHM-CT-2006-037093 InGenious HyperCare, and HEALTH-2007-201550 HyperGenes), the Fonds voor Wetenschappelijk Onderzoek Vlaanderen, Brussels, Belgium (grants G.0256.05 and G.0575.06), and the Katholieke Universiteit Leuven, Belgium (grants OT/04/34 and OT/05/49). E.B. is supported by a Heisenberg professorship from the Deutsche Forschungsgemeinschaft (Brl589/8-1), by a grant from the Else Kröner-Fresenius foundation (P27/05 // A24/05 // F01), and the Interdisziplinäres Zentrum für Klinische Forschung (IZKF; Bra1/001/08), Münster, Germany. This study was also supported by a grant from the European Union, an ICT in the FP7-ICT-2007-2, project number 224635 (VPH2) to S.-M.B.-H.
- Received January 11, 2008.
- Revision received January 31, 2008.
- Accepted March 19, 2008.
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