Plasma potassium is a moderately heritable phenotype, but no robust associations between common single nucleotide polymorphisms (SNPs) and plasma potassium have previously been described. Genetic influences on renal potassium handling could be important in the etiology of hypertension. We have tested whether common genetic variation in the gene encoding the β-subunit of the epithelial sodium channel (SCNN1B) affects plasma potassium and blood pressure level in a study of 1,425 members of 248 families ascertained on a proband with hypertension. We characterized family members for blood pressure using ambulatory monitoring, measured plasma potassium in venous blood samples, and genotyped four SNPs that spanned the SCNN1B gene. We found highly significant association between genotype at the SCNN1B rs889299 SNP situated in intron 4 of the gene and plasma potassium. Homozygotes for the rarer T allele had on average a 0.15 mM lower plasma potassium than homozygotes for the common C allele, with an intermediate value for heterozygotes (trend, P = 0.0003). Genotype at rs889299 accounted for ∼1% of the total variability in plasma potassium, or around 3% of the total heritable fraction. There was no association between genotype at any SCNN1B SNP and blood pressure considered as a quantitative trait, or with hypertension affection status. We have shown a modest sized but highly significant effect of common genetic variation in the SCNN1B gene on plasma potassium. Interaction between the rs889299 SNP and functional SNPs in other genes influencing aldosterone-responsive distal tubular electrolyte transport may be important in the etiology of essential hypertension.
the epithelial sodium channel (ENaC) plays a key role in the maintenance of blood pressure and electrolyte homeostasis in the distal nephron. ENaC consists of three subunits α, β, and γ, which combine in a 1-to-1-to-1 ratio to form the functional channel (15). Activating mutations in the β- and γ-subunits of ENaC (encoded by the SCNN1B and SCNN1G genes, respectively) give rise to Liddle's syndrome, an autosomal dominant condition involving amiloride-sensitive hypertension, hypokalemia, and metabolic alkalosis (10, 20). Conversely, loss of function mutations in the α-, β-, or γ-subunits of ENaC leads to recessive pseudohypoaldosteronism type I, a childhood condition characterized by severe salt wasting and hyperkalemia (6). A number of groups have investigated the role of common polymorphisms in the genes encoding the ENaC subunits as potential susceptibility alleles influencing the risk of essential hypertension to a moderate degree. However, no common single nucleotide polymorphism in any subunit of ENaC has been consistently identified as contributing to blood pressure variation in human populations thus far (19).
Both plasma potassium and 24-h urinary potassium excretion show significant heritabilities estimated at between 30–60%, suggesting that genetic influences on potassium handling may be identifiable (12, 22, 23). However, no studies so far have shown robust evidence for association between common genetic variants and plasma levels of potassium. Although there is no simple correlation between plasma potassium and blood pressure (in the absence of secondary causes of hypertension that cause hypo- or hyperkalemia), a diet that is high in potassium reduces levels of blood pressure (3). The mechanism whereby increased dietary potassium reduces blood pressure is unknown, since total body content of potassium is not different in patients with essential hypertension and matched controls (7). However, one possibility is that increased renal potassium secretion (in response to an increased dietary intake) results in an associated decrease in renal sodium and chloride reabsorption. Genetic influences on renal potassium secretion might therefore be important mediators of the effect of dietary potassium on blood pressure. We hypothesized that common variation in the SCNN1B gene could influence plasma potassium and have tested this in a large family study.
The collection strategy of this family study has been described previously (5). Briefly, families were ascertained between 1993–97 through a proband with essential hypertension. The proband was required to have had an ambulatory blood pressure monitor (either on or off treatment) with mean daytime systolic pressure >140 mmHg and mean daytime diastolic pressure >90 mmHg; or to have had multiple office blood pressure readings taken by their family practitioner >160 mmHg systolic and 95 mmHg diastolic; or to be taking two or more antihypertensive drugs for the control of blood pressure. We utilized these stringent criteria to maximize our certainty that the proband was in the upper 5–10% of the blood pressure distribution. Secondary hypertension was excluded using the standard screening protocol applied in the hypertension clinic, reinforced by further investigations if required. To be suitable for the study, families were required to consist of at least three siblings (including the proband) clinically assessable for blood pressure if at least one parent of the sibship was available to give blood for DNA analysis, and to consist of at least four assessable siblings (including the proband) if no parent was available for DNA analysis. Qualifying sibships could be either in the generation of the proband or his/her offspring, and there was no requirement for the sibship to contain additional members affected with hypertension (though this was not an exclusion criterion). Where members of the sibship were found to be hypertensive (using identical criteria to those applied in the probands), families were extended and the spouses and offspring of hypertensive sibs collected. Thus, the majority of the individuals in the family collection have blood pressures within the normal range, and the family collection includes some extended families, though most are nuclear families (16). The study received ethical clearance from the appropriate review committees, and corresponded with the principles of the Declaration of Helsinki. All participants gave informed consent to participate in the study.
Blood pressure was measured using ambulatory monitoring for a period of 24 h in all subjects willing to undergo monitoring, using the A&D TM2421 monitor (Takeda Medical) according to a previously described protocol (8). A full clinical history was taken that included the subject's medical history and lifestyle factors, including consumption of alcohol and tobacco and habitual physical exercise. Anthropometric measurements including height, weight, waist, and hip were made (waist measured at the natural waist and hip measured at the level of the greater trochanters). Blood was drawn into a variety of anticoagulants for plasma and DNA analysis, and immediately placed on ice until centrifugation, which was carried out within 2 h of blood draw in over 90% of cases. Samples with evidence of hemolysis were excluded from analysis of plasma potassium. Participants were excluded from analysis if they had a history of significant renal disease, abnormal levels of plasma creatinine, or intercurrent medical conditions that could influence either blood pressure or plasma potassium (for example, excessive alcohol intake). Plasma potassium was measured using an autoanalyzer according to standard protocols. A total of 1,425 individuals from 248 families participated in the study.
The SCNN1B gene is ∼79 kb in length and lies at ∼23 Mb from the p-terminal end of chromosome 16. It consists of 13 exons of which 12 are coding. HapMap data (www.hapmap.org) show that the gene contains four major haplotype blocks in Caucasian subjects. We selected one common SNP from each haplotype block for genotyping (rs1004749 is an A/C SNP in the intron between the transcription start site and the first translated exon; rs238547 is a synonymous T/C SNP in exon 1; rs889299 is a C/T SNP in intron 4; and rs250570 is a C/G SNP in intron 7). The minor allele frequencies at these SNPs in Caucasians lie in the range of 0.23 to 0.43 (www.ncbi.nlm.nih.gov/projects/SNP/). All SNPs were typed by PCR amplification of genomic DNA followed by digestion with appropriate restriction enzymes and agarose gel electrophoresis for allele separation (details available on request). Control individuals of known genotype were included in every plate. Genotyping was carried out blinded to phenotypic information. Mendelian inheritance of all the genotypes was checked using PEDSTATS (24); additional checks on genotyping accuracy were carried out using the error-checking option in MERLIN (1). The estimated genotyping error rate was <1%.
Preliminary analyses using MINITAB were conducted to examine the phenotypic data for normality and log-transform where appropriate (this was necessary for all the blood pressure phenotypes). Significant covariates were then identified using regression models (using a threshold of P < 0.05 for inclusion in the final model), and the residuals from these regressions were used as the input variables for the genetic analyses. Around one-third of the sample was hypertensive and taking medications that would be expected to influence both blood pressure and plasma potassium levels. Therefore, to preserve as much information as possible for the analyses of plasma potassium, we separately identified those individuals taking each of the major classes of antihypertensive drugs (beta blockers, diuretics, ACE inhibitors, and calcium antagonists) and estimated the effect of each of these drugs on plasma potassium from the data. We calculated the heritability of plasma potassium using MERLIN. Blood pressure and plasma potassium level were then examined in turn for association with genotype at each individual SNP by regression models implemented in a variance-components framework to allow for relatedness, as previously described (9). To be certain that our adjustment for treatment had not led to false positive findings, the analyses were repeated including only those participants who were not on those medications (diuretics and ACE inhibitors) that were found to influence plasma potassium level in the regression models.
Characteristics of the participants are summarized in Table 1. Fifty-two percent of the sample were female and 36% of the sample were classified as hypertensive. As expected, given the selection of families through a hypertensive proband, ambulatory blood pressures tended to be higher than would be expected in a nonselected population. Quantitative daytime recordings of ambulatory blood pressure were available in 958 people, with on-treatment recordings available in a further 224. Due to participants electing to switch off the monitor at night, fewer night recordings were available; quantitative night recordings were available in 770 people with on-treatment recordings available in a further 162. The median family size was five people, 60% of families comprising between four and six genotyped and phenotyped members. Seventy-one percent of families were two-generations and 29% were three-generations.
Plasma potassium was approximately normally distributed, so was analyzed without transformation. All blood pressure phenotypes departed significantly from normal and were therefore log-transformed prior to analysis. Blood pressure variables were adjusted by regression for the significant covariates of age, sex, smoking, and physical exercise habit. Plasma potassium was adjusted for the following significant covariates: age (β, 0.005; P < 0.001); sex (β, 0.120; female K+ lower than male K+; P < 0.001); treatment with diuretics (β, −0.272; P < 0.001); treatment with ACE inhibitors (β, 0.083; P = 0.008); and current smoking (β, 0.052; P = 0.029), which, as previously described by others, was associated with a higher plasma potassium level (11, 21). Age, sex, and smoking explained 5.38% of the variability in plasma K+, and drug therapy explained a further 5.93%, the majority of that effect being due to diuretics. Thus, the covariates together explained only ∼11% of the variability in plasma potassium. Plasma potassium was not significantly correlated with blood pressure, hypertension status, or body mass index. Plasma potassium after adjustment for covariates was significantly heritable (h2 = 35.4%; P < 10−6) in these families.
Genotyping was successful in >95% of samples for all SNPs. All SNPs were in Hardy-Weinberg equilibrium at the 0.05 level, and allele frequencies were in good agreement with previous available data from dbSNP. For those SNPs typed in the HapMap project (rs1004749, rs238547, and rs889299) linkage disequilibrium coefficients in our data (D′ and r2) were in good agreement with the HapMap CEU population. SNP rs250570, which was not typed in the HapMap project, was in weak linkage disequilibrium with rs1004749 (D′ = 0.11, r2 = 0.009) and rs238547 (D′ = 0.21, r2 = 0.013), and moderate linkage disequilibrium with rs889299 (D′ = 0.90, r2 = 0.655).
There was no significant association between any SCNN1B SNP and either systolic or diastolic blood pressure (P > 0.1 for all). There was, however, significant association between genotype at rs889299 and plasma potassium (Table 2). The major [cytosine] allele was associated with a higher plasma potassium than the minor [thymine] allele in an additive fashion. In multivariable regression analyses incorporating age, sex, diuretic therapy, ACE inhibitor therapy, and rs889299 genotype, the regression coefficient for covariate-adjusted plasma potassium on rs889299 genotype was 0.058 (with SE of 0.016); T-statistic = 3.61; P = 0.0003 (Table 3). Plasma potassium was 0.15 mM lower in rare homozygotes than in common homozygotes. Genotype at rs889299 accounted for 1% of the population variability in plasma potassium, which is ∼3% of the heritability of the trait. There was a significant association (P = 0.003) of genotype at rs230570 with plasma potassium; this SNP was in moderate linkage disequilibrium with rs889299, and when the effect of rs889299 genotype was fitted in the model, there was no additional significant effect of rs230570 genotype. None of the other three SCNN1B SNPs typed showed significant evidence of association with plasma potassium.
To ensure that our findings did not arise from some artifact in the method we used to adjust plasma potassium levels for drug treatment, the analysis was repeated using data from only those individuals whose potassium had been determined in the absence of drug treatment. Of 1,332 participants included in the drug-adjusted analyses, 1,051 were taking neither diuretics not ACE inhibitors, 125 participants were taking diuretics, 89 were taking ACE inhibitors, and 67 were taking both agents. In the analyses restricted to the 1,051 people taking neither agent, there remained significant evidence of association between plasma potassium and rs889299 genotype; although as expected with a smaller dataset, the P value was less extreme (P = 0.002). There was minimal change to any of the coefficients in the model (Table 3). Plasma potassium in the individuals not taking diuretics, or ACE inhibitors was 0.15 mM lower in common homozygotes than in rare homozygotes, as was the case in the drug-adjusted analyses conducted on larger numbers. There were no significant interactions between genotype and the other predictors in the final model (age, sex, diuretic and ACE inhibitor treatment, and smoking) with regard to plasma potassium.
A priori, we had tested association between four SNPs and the phenotypes systolic and diastolic blood pressure, and plasma potassium. Application of a Bonferroni correction is generally agreed to be markedly over-conservative in this situation as the tests are not truly independent. But, even adopting this maximally conservative approach, our results retain significance (Bonferroni corrected: P = 0.0036 for drug-adjusted analyses; P = 0.024 for adjusted analyses; correction for 12 tests). It is therefore unlikely that multiple testing accounts for our findings.
We have shown a relatively small but significant association between the rs889299 SNP in intron 4 of the SCNN1B gene and plasma potassium. There is around a 0.15 mM difference in potassium between common and rare homozygotes. This association is novel, and to our knowledge, this is the first report of a common SNP that is significantly associated with plasma potassium levels in a large study. We found no association between genotype at any of the SCNN1B polymorphisms we typed, one in each of the four haplotype blocks characterizing the gene, and blood pressure.
Electrogenic reabsorption of sodium by ENaC in the connecting tubule and collecting duct provides the driving force for chloride reabsorption by paracellular flux, and potassium secretion into the tubule by the ROMK channel. Our result suggests that individuals with the rarer T allele at rs889299 may have a higher constitutive activity of ENaC, which may in turn increase sodium reabsorption and provide a larger electrochemical gradient driving the tubular secretion of potassium via ROMK. Although major disturbances of sodium reabsorption due to genetic effects on ENaC function (such as in Liddle's syndrome or pseudohypoaldosteronism type I) can clearly have secondary effects on plasma potassium, our observation of an effect of SCNN1B SNPs on plasma potassium without an effect on blood pressure is perhaps unexpected. We would speculate that it may reflect more effective “buffering” of small differences in sodium reabsorption by the network of genes influencing that phenotype than is present for comparably small differences in plasma potassium. We observed a 0.15 mMol/l difference between common and rare homozygotes at rs889299, or around a 3.5% higher plasma potassium on average. Such a change in plasma potassium within the “normal range” would, we think, be unlikely to be visible to natural selection.
There are a number of possible mechanisms whereby the differences we have observed could arise. If rs889299 (or some variant in LD with it) is regulatory, our observations may reflect differences in levels of SCNN1B gene expression. Alternatively, functional genetic variants in SCNN1B could cause differences in the regulation of ENaC channel function by WNK4, influence trafficking of the ENaC channel, or influence the open probability of the channel. Future studies to fine map the responsible variant in SCNN1B and to determine its functional consequences will be needed to address these questions.
Previous studies have looked for association between common variants in ENaC subunits and the risk of essential hypertension, but results have been inconclusive. The T594M variant in the COOH-terminal end of SCNN1B, found almost exclusively in black people, has been associated with lower plasma renin activity, but the initially reported association with hypertension has not been convincingly replicated so far (2, 4, 18). A G442V variant in SCNN1B, similarly only seen in black people, has been associated with the urinary aldosterone-to-potassium ratio, an index of ENaC activity, but not with hypertension status (2). As argued by Pratt (19), it is very likely that the genetic regulation of sodium reabsorption requires study in an integrative fashion to identify any effects on the final phenotype of hypertension. This is because isolated genetic changes in one of the ENaC subunits with (as here) relatively small phenotypic effects will be “buffered” by other aspects of the system. In this case, increased ENaC activity would be buffered chiefly by a downward adjustment of aldosterone production. Therefore, SNPs that affect ENaC function might only affect blood pressure in people genetically predisposed to a somewhat higher level of aldosterone expression under euvolemic conditions. In this regard, we and others have shown that genetic variation at the CYP11B1/CYP11B2 locus affects baseline levels of aldosterone excretion in healthy subjects (13). There is therefore a strong rationale to test the hypothesis that genetic interaction between SCNN1B and CYP11B1/B2 SNPs influence the risk of hypertension. However, studies far larger than any conducted to date would be required to achieve reliable results.
Previous studies that have reported genetic associations with plasma potassium have focused on the C825T SNP in the G protein β-3 subunit (GNB3) gene, but the results are contradictory and study sizes relatively small. A Japanese study of 211 subjects showed significantly higher plasma potassium in carriers of the 825T allele, but a more recent study of 144 European subjects showed significant association in the opposite direction (14, 17). The present study includes data on genotype and plasma potassium for 1,332 individuals and is much larger than those previous studies. Our result accounts for around 3% of the heritability of plasma potassium. Larger effects may therefore remain to be discovered. Genome-wide SNP association studies coupled with intensive study of other genes in the signaling pathway regulating sodium reabsorption in the distal nephron (for example, WNK4, NEDD4) are complementary approaches that may both be required to identify such effects.
This study has certain limitations. No urine specimens suitable for the quantification of sodium and potassium excretion were available; such data would have enabled us to account to some extent for variability in dietary intake of these electrolytes and potentially increased the power of the study. Further studies incorporating these urinary phenotypes would be of interest in developing our findings. The SCNN1B gene is large (∼80 kb) and in a region of relatively low linkage disequilibrium, and so the four SNPs we typed did not capture all common genetic variation present. Associations of larger magnitude between other SCNN1B SNPs and plasma potassium may therefore remain to be discovered in future fine-mapping studies. Finally, as with any novel genetic association, replication in an independently ascertained large study will be desirable to further strengthen the evidence for our result.
Perspectives and Significance
Complex genetic networks govern the renal regulation of electrolyte balance; therefore, the effect of common SNPs in any individual gene are likely to be small. We have shown an association between SNPs in the SCNN1B gene and plasma potassium level, though not between genotypes and blood pressure. This implies that common variation in the genes that combine to form ENaC can affect the function of the channel, although the mechanism of the association remains to be established. It seems likely that the primary genetic effect on sodium reabsorption is “buffered” by other genes involved in that process, which are likely to have been under strong evolutionary selection pressure. Our observations suggest that interaction between variants in the SCNN1B gene and variants in other genes involved in sodium handling in the distal nephron could be important in determining susceptibility to hypertension, though very large studies, involving many thousands of individuals, would be necessary to investigate such interactions reliably.
This study was funded by grants from the Wellcome Trust and the British Heart Foundation.
We thank all the families who participated in this study.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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