Human Molecular Genetics, 2001, Vol. 10, No. 19 2157-2164
© 2001 Oxford University Press
Genetic variation in the human urea transporter-2 is associated with variation in blood pressure
Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305-5120, USA, 1Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan, 2Section of General Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, 3Division of Cardiology, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, 4Tri-Service General Hospital, Taipei, Taiwan, 5Division of Endocrinology, Stanford University School of Medicine, Stanford, CA 94305, USA, 6Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA, 7Health Research and Policy, Stanford University School of Medicine, Stanford, CA 94305, USA and 8Hawaii Center for Health Research, 846 South Hotel Street, Suite 306, Honolulu, HI 9681, USA
Received June 8, 2001; Revised and Accepted July 22, 2001.
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ABSTRACT |
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The kidney, by regulating the volume of fluid in the body, plays a key role in regulating blood pressure (BP). The kidney uses primarily sodium and, to a lesser extent, urea to maintain the appropriate volume of fluid. Genetic variation in proteins that determine sodium reabsorption and excretion is known to significantly influence BP. However, the influence of genetic variation in urea transporters on BP has not been examined. We determined therefore whether nucleotide variation in the kidney-specific human urea transporter, HUT2, is associated with variation in BP. After determining the genomic structure of the coding sequence, seven single nucleotide polymorphisms (SNPs) were identified. Two of the SNPs result in Val/Ile and Ala/Thr amino acid substitutions at positions 227 and 357 in the HUT2 open reading frame, respectively. Another SNP is silent and four others are in introns or the 3' untranslated region. Over 1000 hypertensive and low-normotensive individuals of Chinese origin were typed for five of these SNPs using a high-throughput genotyping method. The Ile227 and Ala357 alleles were associated with low diastolic BP in men but not women, with odds ratios 2.1 [95% confidence interval (CI) 1.5–2.7, P < 0.001] and 1.5 (95% CI 1.2–1.8, P < 0.001), respectively. There was a similar trend for systolic BP, and odds ratios for the Ile227 and Ala357 alleles were 1.7 (95% CI 1.2–2.3, P = 0.002) and 1.3 (95% CI 1.1–1.6, P = 0.007), respectively, in men.
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INTRODUCTION |
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In adult humans, systolic blood pressure (BP) (maximum pressure as the heart contracts) <120 mm of mercury and diastolic pressure (lowest pressure between heartbeats) <85 mm of mercury is considered normal. The body, using a variety of short-term and long-term regulators, tries to maintain BP within 10–15% of this level (1). Hypertension is currently defined as systolic BP >140 mm of mercury or diastolic BP >90 mm of mercury. Although BP is regulated by a network of interacting complex systems, physiological studies and genetic analysis in humans suggest strongly that defects in kidney function play a major role in causing abnormal changes in BP. For example, hypertension can be transferred from a genetically hypertensive individual to a normotensive one merely by transplanting the kidney of the hypertensive individual (2). Genes that cause rare Mendelian forms of hypertension or hypotension (low BP) in humans directly or indirectly affect reabsorption of sodium (and hence water) by the kidney (3).
Underlying the complicated system employed by the kidney to regulate BP is a conceptually straightforward mechanism: increased BP causes the kidneys to excrete more water and salt, resulting in a decrease in the volume of fluid in the body. This decrease in fluid volume in turn causes the heart to pump less blood, resulting in a fall in BP. Conversely, if BP falls below the normal range, the kidneys retain salt and water more avidly, raising the volume of fluid in the body and thus increasing BP. Indeed, incremental changes in body fluid volume can have a profound long-term impact on BP (4). Among the solutes, sodium ions play a vital role in maintaining fluid volume in the body; urea plays an additional and important part in the urinary concentrating mechanism, and hence in conserving water and maintaining body fluid volume.
Urea transport is relevant, in principle, to BP homeostasis because the kidney reabsorbs a substantial fraction of the urea that is generated by protein catabolism and uses it to maintain an osmolality gradient in the inner medulla. The ability of the kidney to maintain and adjust osmotic gradients in the face of environmental changes is essential for its function of regulating the volume of fluid in the body, and therefore its capacity to maintain BP (5).
Movement of urea across plasma membranes is accomplished by urea-specific transporter proteins. There are at least two types of urea transporters known. One is expressed in a variety of tissues including the kidney, brain, testis, bone marrow and erythrocytes; the other is expressed primarily in the kidney (for recent reviews see refs 6 and 7). In the rat, there are four known isoforms of the kidney-specific urea transporter. The largest, UT-A1, encodes a protein of 97 kDa. The other isoforms, UT-A2-4, can be thought of as alternatively spliced products of UT-A1, although alternative splicing has not been explicitly demonstrated for all the isoforms. UT-A2 is essentially the C-terminal half of UT-A1, and UT-A3, the N-terminal half. UT-A4 is composed of the N-terminal half of UT-A3 and the C-terminal half of UT-A2.
The activity/expression of these urea transporters is affected by acute and chronic stressors. Studies with perfused rat inner medullary collecting ducts revealed a rapid increase in urea permeability in response to vasopressin (8) or increased osmolality (9), although the particular urea transporter contributing to this effect has not been determined. Long-term changes in water and protein intake were shown to affect the expression of UT-A1 and UT-A2 genes in a Sprague–Dawley rat model (10). Finally, furosemide, a diuretic commonly used to treat hypertension, affects the expression of UT-A2 (11).
Taken together, these observations suggest that disturbances in urea permeability might affect the kidney’s ability to regulate fluid volume, and this in turn might have an impact on BP. For this reason, we examined whether nucleotide variation in human urea transporter -2 (HUT2), the human homolog of UT-A2 and the only kidney-specific urea transporter cloned in humans (12), is associated with variation in BP.
We determined the genomic structure of the coding sequence of HUT2 and identified several single nucleotide polymorphisms (SNPs) in this gene. We then tested whether these SNPs were associated with BP variation by genotyping over 1000 hypertensive and low-normotensive individuals of Chinese origin.
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RESULTS |
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Genomic structure of HUT2
The exon–intron structure of the coding sequence of the HUT2 gene was determined using a PCR-based strategy as described in Materials and Methods. The coding sequence is divided into eight exons (Fig. 1). The sequence at the exon–intron boundaries is given in Table 1. All introns follow the GT-AG rule, and range in size from 327 bp for intron 3 to >5000 bp for intron 7.
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Polymorphism identification
Denaturing high-performance liquid chromatography (dHPLC) was used to detect polymorphisms as described by Oefner and Underhill (13) (see Materials and Methods). Altered dHPLC profiles, i.e. putative heterozygotes, were detected for exons 1, 2, 3, 5 and 8. Sequencing of putative heterozygotes and homozygotes led to the detection of seven polymorphisms. Representative data for exon 3 are shown (Supplementary Material, Fig. 1).
The distribution of SNPs is shown in Figure 1. Three SNPs are in the coding sequence. SNP1, a G
C transversion 102 bp from the start of exon 1, is silent; the other two cause amino acid substitutions. SNP5 is a GA transition 19 bp from the start of exon 5 that results in a valine/isoleucine substitution at position 227 in the published HUT2 amino acid sequence (12). SNP7 is another GA transition 76 bp from the start of exon 8 which results in an alanine/threonine substitution at position 357 in the HUT2 amino acid sequence. 141 bp downstream of SNP7, and 16 bp into the 3'-untranslated region (3'-UTR) is a CT transition (SNP8). Three SNPs are in introns. SNP2 is 13 bp upstream of exon 2, and the other two are 61 and 66 bp downstream of exon 3. The last two SNPs are in complete disequilibrium and are referred to as though they were a single SNP (SNP3 in Fig. 1 and Supplementary Material, Fig. 1).
Association study
To determine whether these newly identified SNPs were associated with BP variation, hypertensive and low-normotensive subjects (Table 2) of Chinese origin were genotyped using a high-throughput method. In the first round of genotyping, 263 low-normotensive and 587 hypertensive individuals were genotyped for five SNPs (1, 2, 3, 5 and 7), and preliminary analysis revealed that the coding SNPs 5 and 7, but not the non-coding SNPs 1, 2 and 3, were associated with hypertension, as judged by a 2 x 2 contingency table (data not shown). Therefore, when an additional 250 samples (80 low-normotensive and 170 hypertensive) became available, these were typed only for SNPs 5 and 7. Representative genotyping results for SNP5 are shown (Supplementary Material, Fig. 2), and the genotype frequencies stratified by hypertension status are given in Table 3.
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Because
90% of the affected hypertensive individuals take antihypertensive medication (Table 2), we could not use their measured BP directly. Instead, we analyzed BPs of affected and unaffected individuals together using a Cox proportional hazards model with BP as the ‘time’ (outcome) variable and ‘censored’ the BP of individuals undergoing treatment for hypertension (14). This procedure performs a semiparametric regression of BP on HUT2 genotype. The implication of the censoring is that the BP of individuals taking antihypertensive medication is assumed to be greater than or equal to what was measured. Since age and body mass index (BMI) are known to affect BP, they were included as covariates in the analysis. The results are presented in Table 4 and Supplementary Material, table 1.
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Both the coding SNPs, Val227Ile (SNP5) and Ala357Thr (SNP7) were significantly associated with BP variation in men but not women. For a recessive model, comparing the Ile/Ile homozygotes to the Val/Val homozygotes and Val/Ile heterozygotes, the hazard ratios (equivalent to the odds ratios from standard regression analysis) for diastolic and systolic BPs were 2.1 (95% CI 1.5–2.7; P < 0.001) and 1.7 (95% CI 1.2–2.3; P = 0.002), respectively; i.e. individuals with the Ile/Ile genotype were more likely to have low-normal BP. The Kaplan–Meier estimates of mean BP for the Ile/Ile homozygous individuals were 151 mm Hg and 87 mm Hg for systolic and diastolic BP, respectively. For the combined Val/Ile heterozygous and Val/Val homozygous class, the Kaplan–Meier estimates were 161 mm Hg and 97 mm Hg for systolic and diastolic BP, respectively. For the Ala357Thr SNP, there was significant evidence for a dominant Thr model predisposing to hypertension, comparing Ala/Ala homozygotes with Ala/Thr heterozygotes and Thr/Thr homozygotes. Ala/Ala homozygotes were more likely to be low-normotensive: hazard ratios were 1.3 (95% CI 1.1–1.6; P = 0.007) for systolic BP and 1.5 (95% CI 1.2–1.6; P < 0.001) for diastolic BP. The Kaplan–Meier estimates for mean systolic and diastolic BPs were 155 mm Hg and 91 mm Hg, respectively for Alal/Ala homozygotes, and 163 mm Hg and 98 mm Hg for the combined Ala/Thr heterozygous and Thr/Thr homozygous group.
In contrast, in females neither SNP was significantly associated with BP under either the dominant or recessive models. The non-coding SNPs were not associated with BP variation in either men or women as confidence intervals for all hazard ratios contained 1 (Supplementary Material, Table 1). When men and women were analyzed together none of the SNPs was significantly associated with BP (data not shown).
Pairwise linkage disequilibrium
We estimated pairwise linkage disequilibrium values using 365 unrelated individuals randomly picked from the families used in the association analyses. The results are presented in Table 5. The non-coding SNPs 1, 2 and 3 which are <2000 bp from one another were in tight linkage disequilibrium, with D'-values of 1. This block of SNPs was in weak disequilibrium with the Val227Ile SNP with D'-values ranging from 0.26 to 0.39. There was little or no association between SNPs 1 and 3 and the Ala357Thr SNP with a D'-value of –0.15. There was weak linkage disequilibrium between SNP2 and the Ala357Thr SNP however (D'-value = –0.34). In contrast, the Val227Ile and Ala357Thr SNPs were in substantial disequilibrium with each other (D' = 0.48). These results are consistent with the observation that these SNPs, because they are associated with each other, were both associated with BP, but SNPs 1–3, which are in weak linkage disequilibrium with these two SNPs, were not associated with BP.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSSUPPLEMENTARY MATERIALREFERENCES |
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Hypertension affects 15–50% of the adult population, and is one of the major risk factors for stroke, myocardial infarction and renal disease. Despite intense effort, our understanding of heritable factors in the etiology of hypertension is rather poor. Twin, adoption and epidemiologic studies indicate that variation in BP is genetically determined to some extent (3). One of the goals of the Stanford, Asia and Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) is to identify genes for essential hypertension.
The failure of at least two large genome scans (15,16) to provide significant evidence of linkage to hypertension suggests that the phenotype might be caused by combinations of several genes, with each gene making only a small contribution. To maximize our chances of finding such ‘susceptibility’ genes, we took several steps. First, in an attempt to reduce genetic heterogeneity, we focused on a relatively homogeneous population of Chinese descent. Secondly, we sampled subjects from tails of the BP distribution. The affected hypertensives were recruited from the upper 20% of the distribution, whereas the unaffected low-normotensive individuals had BP readings in the lower 30% of the distribution (17). Thirdly, because recent theoretical work suggests that association studies might be adequately powerful to detect susceptibility loci (18), we began candidate gene studies—testing specific variants in genes that might, for biological reasons, be expected to be involved in BP regulation for association with hypertension. We focused on genes expressed primarily in the kidney because of the central role played by this organ in BP regulation. The results presented above represent one of the first genes we examined, the kidney-specific human urea transporter, HUT2.
Two coding SNPs in the HUT2 gene, Val227Ile and Ala357Thr, were associated with BP in men but not women. However , the Ile227 and Ala357 alleles provide only modest protection against hypertension: the hazard ratios are 2.1 and 1.5 (P < 0.001), respectively, for diastolic BP. The Ile227 allele and Ala357 allele also protect against high systolic BP with hazard ratios of 1.7 (P = 0.002) and 1.3 (P = 0.007), but these hazard ratios probably are only marginally significant when the P-values are corrected for multiple testing (Materials and Methods). Although the hazard ratios for the Ile227 variant are greater than that for the Ala357 allele, the latter result seems more credible. The reason for this is that the frequency of the Ile227 allele (0.3) is lower than that of the Ala357 allele (0.6). Therefore, under the recessive Ile227 model for which there is significant evidence, the hazard ratio for the Ile227 allele is based on comparing the small number (49) of Ile/Ile homozygotes to the 482 Val/Ile heterozygotes and Val/Val homozygotes. In contrast, for the Ala357Thr SNP there is significant evidence for a dominant model, and under this model there is a more even distribution of genotypes: the comparison is between 202 Ala/Ala homozygotes and 327 Ala/Thr heterozygotes and Thr/Thr homozygotes.
Unlike the association seen in men, there is no evidence of association in women. We do not understand the basis for this sexual dimorphism. An obvious possibility is the hormonal difference between men and women. In an attempt to address this issue, we stratified women based on menopausal status, but neither coding variant was associated with BP in such a stratified population (data not shown). This phenomenon of gender-specific association is not unprecedented in the genetics of hypertension, however. Most notably, an insertion/deletion polymorphism in the angiotensinogen converting enzyme was associated with hypertension in males, but not females, in two large population-based studies (19,20). Furthermore, it is well-known that men have higher BP in general, and are more susceptible to hypertension (21,22).
The fact that coding variants in HUT2, but not the non-coding ones, are associated with BP suggests that variation in HUT2 makes a functional contribution to variation in BP. Furthermore, Val227 and Ala357 residues are evolutionarily conserved; Val227 among rat, rabbit and human and Ala357 between rabbit and human, suggesting that these residues might be important for urea transporter function. How might these polymorphisms contribute to BP variation? One possibility is that the Ile227 residue decreases the activity of the transporter, perhaps by affecting the structure of the protein, such that urea, and therefore water, is reabsorbed less avidly. This decrease in the reabsorption of water in turn might result in lower BP and thus, protection from hypertension. This hypothesis would be consistent with the recessive effect of the Ile227 allele on BP. The Thr357 allele, in contrast, might increase the activity of the transporter, thereby resulting in increased urea and water reabsorption, and therefore predispose to high BP.
It is possible however, that the Val227Ile and Ala357Thr SNPs are merely in linkage disequilibrium with variants in a nearby gene. If this is the case, then such a gene would most likely reside 3' or downstream of the Ala357Thr SNP because the upstream SNPs (SNPs 1, 2 and 3) showed no association with hypertension. Examination of the published gene maps of the region downstream of HUT2 revealed no obvious candidates. Further studies of the impact of these polymorphisms on HUT2 function, and of nucleotide variation in this region would help to clarify whether variation in HUT2 alone, or in combination with other SNPs in the region contributes to BP variation. In either case, our results underscore the importance of examining multiple SNPs in a candidate gene. The general validity of these association results needs to be determined by studying these variants in different populations.
SNPs identified here will also be useful for other kinds of studies. For example, given that furosemide, a diuretic commonly used to treat hypertension, affects the expression/activity of the rat homolog of HUT2, it would be of interest to determine whether either the Val227Ile or Ala357Thr SNPs are associated with response to treatment with diuretics. In addition, very recent work suggests that the region of chromosome 18 around HUT2 is linked to orthostatic hypotension (23) and BP variation associated with changes in posture (24); our results make the HUT2 gene an attractive candidate for these phenotypes.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSSUPPLEMENTARY MATERIALREFERENCES |
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Genomic structure of HUT2
The genomic structure of the coding sequence of HUT2 was determined using human genomic clones and a PCR-based strategy. Based on the published cDNA sequence of HUT2 (12), a sequence-tagged site of 284 bp was designed using primers specific for the 3'-UTR (Table 6). Ten genomic clones bearing this DNA fragment were purchased from Research Genetics (Huntsville, AL). Two of these clones, designated RPCI.11 58 B 19 and RPCI.11 61 I 5, were chosen for further study. Both clones had inserts of
150 kb (based on pulsed-field gels; data not shown).
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An overlapping set of primers based on HUT2 cDNA sequence was used to amplify DNA from the genomic clones noted above. Of the seven primer-pairs used, all except two gave robust PCR products with both clones (data not shown). The remaining five PCR products were gel-purified and sequenced directly or cloned into the plasmid vector pKRX (25) and then sequenced. Comparison of the sequence so obtained with published HUT2 cDNA sequence allowed unambiguous determination of exon–intron boundaries. Of the two primer pairs that failed to amplify genomic DNA, one was designed to amplify the 5' untranslated sequence, and was not investigated further. The other failure was in the coding sequence (exon 7 in Fig. 1) and a different strategy, bubble PCR, was used to determine exon–intron junctions in this region (26). RPCI.11 58 B 19 DNA was cut with AluI and ligated with a bubble adaptor. The resulting ligated fragments were amplified using primers specific for HUT2 cDNA and the bubble adaptor. Amplified DNA fragments were cloned and sequenced to determine exon–intron junctions. Because we obtained sufficient coverage of the gene, in terms of SNPs (see below), intron 4 was not sequenced completely.
Polymorphism detection
DNA from 31 subjects, 23 hypertensive and eight low-normotensive, was chosen to identify SNPs in the HUT2 gene. HUT2 exon sequence along with 100 bp of flanking intron sequence was amplified from these individuals using primers listed in Table 1. All PCRs were done under the following conditions: 100 ng genomic DNA, 1 µM of each primer, 200 µM dNTPs and 0.5 U Taq (Gibco BRL, Rockville, MD) in 50 µl of 1x Taq buffer (10 mM Tris pH 8.3, 1.5 mM MgCl2, 50 mM KCl, 0.1 mg/ml gelatin). An initial denaturation step of 95°C for 5 min was followed by 30 cycles of 94°C for 30 s, 60°C for 30 s and 72°C for 30 s. To identify heterozygotes, the resulting PCR products were analyzed by dHPLC on a TransGenomic instrument (13). All exons except the 50 bp exon 7 (Fig. 1) were examined for SNPs. Conditions for dHPLC were as prescribed by the Tm program (http://hardy-weinberg.stanford.edu/dhplc/melt.html). Polymorphisms were identified by sequencing DNA from four apparently heterozygous and two homozygous individuals.
Subjects
Details of our study population have been published (27). The study design incorporated concordant (both sibs have hypertension) and discordant sib-pairs (one sib is hypertensive and the other has low-normal BP, see below). In this study, 343 low-normotensive and 757 hypertensive subjects of Chinese origin were genotyped. These 1100 subjects were drawn from 480 families. The distribution of family sizes is as follows: 124 singletons, 191, 94, 49, 16 and 6 with two, three, four, five and six sibs, respectively. Among these 480 families, 228 had both hypertensive and low-normotensive sibs; 127 families had only hypertensive sibs; one family had only low-normotensive sibs and the remainder were singletons. The vast majority (85%) of hypertensive and low-normotensive subjects of Chinese origin were recruited in Taiwan. 114 individuals were recruited from the San Francisco Bay area and 53 from Hawaii. This study was approved by Institutional Review Boards at all participating sites and all subjects provided written informed consent.
Hypertension was defined as BP in the upper 20% of the BP distribution, which in our population translated into the following values: systolic BP (SBP) 
160 mm Hg or diastolic BP (DBP) 160 mm Hg or taking two medications for high BP (stage II hypertension). Alternatively, the subject had uncontrolled hypertension, i.e. took one medication for high BP and had either SBP 140 or DBP 90 mm Hg. Low-normal BP was defined as BP in the bottom 30% of the age and sex-adjusted BP distribution, which in our population translated into the following BP values: for males under 45 years, SBP 
115 mm Hg and DBP 76. For males over 45, SBP 122 and DBP 78 were used. For females younger than 45, low-normal BP was defined as SBP 107 and DBP 70 mm Hg. For those over 45, the cut-off was SBP 118 and DBP 75. In addition to these BP criteria, subjects had to be between 35 and 60 years of age. Subjects currently over age 60 were also recruited provided that documentation of their hypertension status prior to age 60 was available. All subjects had to have Chinese ancestry, i.e. all four grandparents were Chinese.
Families were excluded from the study if they met any of the following criteria: (i) One of the affected sibs was adopted (i.e. no parent in common) or if the sibs had only one parent in common. (ii) Both parents were treated for hypertension before the age of 60. If offspring reports about their parents’ hypertension status were conflicting, then a single reliable report of hypertension in both parents before age 60 was a cause for exclusion. This exclusion criterion, however, did not apply to discordant sib-pairs. (iii) Diabetic individuals were excluded. Diabetes uncovered as a result of SAPPHIRe laboratory work did not lead to exclusion however. (iv) Severe kidney disease (except stones and remote infections) of creatinine >1.5 mg/dl, unless documented proof that the subject met inclusion criteria prior to increase in creatinine levels. (v) A BMI >35. 6. In addition, the following conditions were considered as cause for exclusion: (i) ongoing (or within the past 6 months) treatment for cancer; (ii) terminal illness (life expectancy <6 months); (iii) liver cirrhosis or any other chronic illness (e.g. heart disease); and (iv) pregnancy or <6 months post-partum.
BP measurements
BP was measured with an oscillometric device, the Dinamap model 1846 SX (Critikon, Tampa, FL) at all field centers, using the following protocol. The participant was seated with both legs uncrossed and asked to refrain from talking for 5 min. After determining the proper cuff size, BP measurements were taken three times with at least 1 min time lapse between two readings, and the average of the second and third readings was used in the analysis. To ensure uniform BP measurement at the different sites, technicians/clinicians at all the sites were trained to measure BP using this protocol, and they were monitored annually during site visits. Furthermore, there was a centralized retraining and recertification of key technicians each year.
Genotyping
Subjects were typed for SNPs 1, 2, 3, 5 and 7 (Fig. 1) using the TaqMan assay as described by Ranade et al. (27,28). The probes and primer sequences used in the genotyping are given in Table 7.
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Association analysis
Genotype data were analyzed using a Cox proportional hazards model, as described by Province et al. (14). In this method of analysis, BP is the outcome variable and HUT2 genotype is the predictor variable, with age and BMI as covariates. Because sibs without parents were used in the analysis, the genotypes are not independent. Therefore, hazard ratios (equivalent to the odds ratios estimated from standard regression analysis) and their CIs were estimated using bootstrapping. Each bootstrap subsample consisted of one individual drawn at random from each family, and hazard ratios were estimated repeatedly in 1000 such subsamples. The overall mean of these subsamples was used as the estimate of the hazard ratio. These 1000 hazard ratios were ranked and the 25th and 975th values were used as the 95% CIs (29). Because we evaluated five SNPs, with two models each (dominant and recessive) for each sex, we considered a nominal P-value <0.0025 (0.05/20) to be significant. This correction might be too conservative however, because SNPs 1–3 are in complete linkage disequilibrium with one another, and therefore, probably cannot be considered as independent tests. In this case, the nominal P-value would have to be <0.0042 (0.05/12).
Linkage disequilibrium
One individual was chosen at random from each of the families studied. Pairwise haplotype frequencies were estimated from these 365 individuals using the expectation-maximization algorithm as implemented in the EH program (30; ftp://linkage.rockefeller.edu/software/eh). Linkage disequilibrium values (D') were calculated as described by Lewontin (31). Note that the number of individuals used in this analysis is smaller than the number of families cited above because not all subjects were typed for SNPs 1, 2 and 3.
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ACKNOWLEDGEMENTS |
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We thank patients for participating in this study. We also thank Stephen Mockrin, Susan Old and Cashell Jaquish of the National Heart, Lung and Blood Institute, and other members of the SAPPHIRe project for their help. We thank Peter Underhill and Adrienne Roxas for their advice and assistance in the dHPLC. We thank Ken Livak and Mike Lucero of Perkin-Elmer, Applied Biosystems Division for help with the TaqMan genotyping assay. K.R. thanks Ellie Click for helpful discussions about renal physiology. This work was supported by grant U01 HL54527-0151 from the National Heart, Lung and Blood Institute, NIH.
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Supplementary material relating to this paper is available at http://www.hmg.oupjournals.org.
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FOOTNOTES |
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+ To whom correspondence should be addressed at: Bristol-Myers Squibb, Pharmaceutical Research Institute, PO Box 5400, Princeton, NJ 08543-5400, USA. Tel: +1 609 818 5342; Fax: +1 609 818 5839; Email: koustubh.ranade@bms.com
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REFERENCES |
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