| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Hypertension. 2007;50:1114.)
© 2007 American Heart Association, Inc.
Original Articles |
From the Division of Preventive Medicine, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Mass.
Correspondence to David Conen, Division of Preventive Medicine, Brigham and Womens Hospital, 900 Commonwealth Ave East, Boston, MA 02215. E-mail conend{at}uhbs.ch
| Abstract |
|---|
|
|
|---|
Key Words: blood pressure hypertension natriuretic peptide precursor A gene polymorphism atrial natriuretic peptide
| Introduction |
|---|
|
|
|---|
Atrial natriuretic peptide plays a significant role in the regulation of vascular tone and sodium homeostasis.4 Experimental studies showed that underexpression of the natriuretic peptide precursor A gene (NPPA; gene ID 4878, chromosome location 1p36.21) is associated with elevated blood pressure in transgenic mice,5 whereas overexpression of NPPA leads to decreased blood pressure levels.6 In humans, few studies revealing controversial findings are available on the association between hypertension and polymorphisms within the NPPA gene.7–10
The large sample size and long follow-up of the Womens Health Study provide a unique opportunity to prospectively analyze genetic influences on multifactorial disorders. We, therefore, tested the hypothesis that NPPA gene polymorphisms are significantly associated with blood pressure progression and incident hypertension in initially healthy, middle-aged women.
| Methods |
|---|
|
|
|---|
Briefly, information on baseline variables was collected using mailed questionnaires. Follow-up questionnaires asking participants about study outcomes and other information were sent every 6 months during the first year and every 12 months thereafter. Follow-up information from randomization through the end of the trial, March 31, 2004, was used for the present analysis. For the present study, we included 18 437 white women who were free of hypertension at baseline and had both NPPA genotypes determined. Median follow-up for this sample population was 9.8 years (interquartile range: 6.6 to 10.5 years). Written informed consent was obtained from all of the participants.
Study Variables
Blood pressure at randomization was self-reported by the female health professionals, a group where self-report of blood pressure has proven highly accurate.14–16 Women were classified into 3 predefined blood pressure categories: <120 mm Hg for systolic and 75 mm Hg for diastolic blood pressure; 120 to 129 mm Hg for systolic or 75 to 84 mm Hg for diastolic blood pressure; and 130 to 139 mm Hg for systolic or 85 to 89 mm Hg for diastolic blood pressure.17 Women with discordant systolic and diastolic blood pressure categories were classified into the higher category. Covariates of interest were ascertained at study entry and included age, smoking, history of hypercholesterolemia (self-reported cholesterol of
240 mg/dL; 6.22 mmol/L), body mass index (weight in kilograms divided by the square of height in meters), history of diabetes, exercise, alcohol consumption, and highest education level achieved.
Outcome Assessment
Blood pressure information at 48 months was missing in 1874 women, and 182 women with complete blood pressure information had a cardiovascular event or died during the first 48 months of follow-up. After excluding these women, 16 381 women remained in the analysis for blood pressure progression at 48 months.
To assess blood pressure progression, we created categories of self-reported blood pressure at 48 months of follow-up identical to those at baseline. Blood pressure progression was defined by progressing
1 blood pressure category compared with baseline or by a new diagnosis of hypertension during the first 48 months.
Incident cases of hypertension were defined by meeting
1 of the following criteria: self-report of a new physician diagnosis of hypertension assessed at years 1 and 3 and yearly thereafter; self-report of antihypertensive treatment assessed at years 1, 3, and 4; or self-reported systolic blood pressure of
140 mm Hg or diastolic blood pressure of
90 mm Hg assessed at years 1 and 4.
Women reporting a new physician diagnosis of hypertension also provided month and year of diagnosis. For a diagnosis defined by another criterion or a missing date for a physician diagnosis, a date between the current and the previous questionnaire was randomly assigned. Women who developed cardiovascular disease, for which the management may affect blood pressure levels, were censored at the date of diagnosis and not considered at risk for incident hypertension thereafter. All 18 437 of the women were included in the incident hypertension analyses.
NPPA Genotype Determination
We analyzed 2 previously described polymorphisms in the NPPA gene: rs5063 (664 G>A) and rs5065 (2238 T>C). Genotyping was performed in the context of a multimarker assay using an immobilized probe approach, as described previously (Roche Molecular Systems).18 In brief, each DNA sample was amplified by PCR with biotinylated primers. Each PCR product pool was then hybridized to a panel of sequence-specific oligonucleotide probes immobilized in a linear array. The colorimetric detection method was based on the use of streptavidin-horseradish peroxidase conjugate with hydrogen peroxide and 3,3',5,5'-tetramethylbenzidine as substrates. To confirm genotype assignment, scoring was carried out by 2 independent observers. Discordant results (<1% of all scoring) were resolved by a joint reading and, where necessary, a repeat genotyping.
Statistical Analysis
We calculated allele frequencies and performed a Hardy-Weinberg equilibrium test using the Fisher probability test statistics. Baseline characteristics according to NPPA genotype groups were compared using
2 tests for categorical variables and ANOVA for continuous variables.
Next, we performed logistic regression analysis to examine the association between blood pressure progression at 48 months and NPPA genotype groups assuming an additive model. Separate models were created for each polymorphism. The common wild type was used as the reference group. In a first step, age-adjusted models are presented. Thereafter, we fitted a multivariable model adjusting for age, smoking, baseline blood pressure category, history of diabetes, body mass index, history of hypercholesterolemia, exercise, alcohol consumption, highest education level, and randomized treatment assignments (aspirin, vitamin E, and ß-carotene).
Subsequently, we fitted Cox proportional hazards models to compare the risk of incident hypertension during the entire follow-up period across NPPA genotype groups. Again, an additive model was assumed. This analysis was adjusted for the same variables described above.
To further assess the independent effect of the NPPA genotype groups on blood pressure progression and incident hypertension, we stratified the study sample in 3 groups according to baseline blood pressure category. Subsequently, we repeated all of the regression analyses described above within each blood pressure stratum. Differences according to baseline blood pressure category were also assessed by including baseline blood pressure by genotype interaction terms into the nonstratified models. The significance of the interaction was assessed by comparing the likelihood ratio with and without the interaction terms in the model.
Pairwise linkage disequilibrium was examined as described by Devlin and Risch.19 Haplotype estimation and inference was determined using PHASE version 2.1.1.20–22 Subsequently, the same multivariable regression models as described above were constructed using inferred haplotypes as the predictor of interest. Only women with an inferred haplotype probability of 1.0 were considered for these analyses. We prespecified that haplotypes with a inferred frequency <0.01 would not be analyzed individually. Accordingly, the A-C haplotype was not assessed. Statistical significance was based on a likelihood ratio test with and without all of the haplotype indicator variables in the fully adjusted models. Only if this overall test was statistically significant were the indicator variables analyzed for individual statistical significance. The most common haplotype (G-T) was used as a reference category for all of the analyses.
Categorical variables were entered in the regression models using binary indicator variables. The proportional hazards assumption was examined for all of the models by including a genotype by logarithm of time interaction into each model.23 No violation of this assumption was found. All of the analyzes were carried out using SAS version 9 (SAS Institute Inc). A 2-tailed P<0.05 was considered to indicate statistical significance.
| Results |
|---|
|
|
|---|
|
At 48 months of follow-up, 7756 of 16 381 women (47.4%) had blood pressure progression. The risk of blood pressure progression among women with the rs5063 GG, GA, and AA genotypes was 47.8%, 43.4%, and 43.9%, respectively. The risk of blood pressure progression for the rs5065 TT, TC, and CC genotypes was 47.9%, 46.0%, and 46.0%, respectively.
During 9.8 years of follow-up, 5452 (29.6%) of 18 437 women developed incident hypertension. Among women with the rs5063 GG, GA, and AA genotypes, 29.8%, 28.1%, and 15.7% became hypertensive during follow-up. The corresponding numbers for the rs5065 TT, TC, and CC genotypes were 29.8%, 29.1%, and 26.3%, respectively.
Risk of blood pressure progression according to NPPA genotype group is shown in Table 2. The A allele of the rs5063 polymorphism was consistently associated with a lower risk of blood pressure progression compared with the G allele. Multivariable adjustment only minimally influenced the effect estimates and 95% CIs. The C allele of the rs5065 polymorphism was significantly associated with a lower risk of blood pressure progression (P=0.050). However, the lower risk of incident hypertension did not reach statistical significance in the Cox model (P=0.068) for the entire follow-up period.
|
After stratification according to baseline blood pressure category, consistent results were obtained for both polymorphisms (Table 3). Although the individual relative risks usually did not achieve statistical significance, all of the point estimates were <1.0, and CIs were broadly overlapping, suggesting that the effect of NPPA genotypes was independent of baseline blood pressure. Accordingly, none of the baseline blood pressure by genotype interaction terms was statistically significant (Table 3).
|
Inferred haplotype frequencies for the present sample were 0.80 for the G-T haplotype, 0.15 for the G-C haplotype, 0.05 for the A-T haplotype, and <0.01 for the A-C haplotype. Multivariable regression analyses using inferred haplotype indicators are shown in Table 4. Overall likelihood ratio tests for blood pressure progression within 48 months and incident hypertension during overall follow-up were all statistically significant (P<0.001 and P=0.037, respectively). The logistic regression analysis showed a strong and consistent reduction in blood pressure progression of the G-C and the A-T haplotypes when compared with the G-T haplotype. In the Cox proportional hazards analysis, only the A-T haplotype but not the G-C haplotype was associated with a significantly lower incidence of hypertension during follow-up.
|
| Discussion |
|---|
|
|
|---|
Few studies have assessed the association between NPPA gene variations and hypertension. To our knowledge, this is the first large-scale prospective study analyzing the relationship between NPPA gene variations and incident hypertension during follow-up. A cross-sectional study in Europe among 1033 subjects found a lower prevalence of the rs5065 C allele in hypertensive subjects compared with control subjects.7 Interestingly, Gruchala et al24 reported that, among 847 subjects with coronary heart disease, those carrying the C allele had less severe disease based on coronary angiography, suggesting that even in individuals with prevalent disease, this polymorphism might have a protective effect. A small study of 104 African Americans did not find a significant difference in the prevalence of rs5065 gene variants between normotensive and hypertensive participants.8
Data are somewhat more equivocal concerning the A allele of the rs5063 polymorphism. Zhang et al10 documented a lower diastolic but not systolic blood pressure among 756 Chinese hypertensive patients carrying
1 copy of the A allele. However, in a small European study, among 203 untreated hypertensive subjects, a greater left ventricular mass index was documented among carriers of the A allele.9 These results must be interpreted with caution in light of the absence of nondiseased control subjects and small sample sizes. Only 11 participants of this study were heterozygous, and none of the participants was homozygous for the rs5063 variant.
The functional roles of the genetic polymorphisms described in the present study are not known. However, the direct effects of natriuretic peptides on the systemic vasculature and the kidney make the association between NPPA polymorphisms and blood pressure progression plausible.4 Furthermore, animal studies have shown the involvement of atrial natriuretic peptide in blood pressure regulation and development of hypertension.5,6 Finally, rs5063 and rs5065 both encode changes to the amino acid sequence of the NPPA gene and are, thus, intrinsically candidates for altering its biological function. The valine-to-methionine substitution encoded by the minor allele of rs5063 is not predicted to be deleterious, but it may affect function in other ways.25 The major allele of rs5065 encodes termination of the NPPA gene 3 amino acids (tyrosine, arginine, and arginine) earlier than the minor allele. Remarkably, the minor allele is likely the ancestral allele, because it and the extra 3 amino acids are found in the sequences from chimpanzee and macaque. Although the NPPA locus was not identified as a site of strong selection in recent studies,26,27 the higher frequency of the derived allele of rs5065 compared with the ancestral allele supports a functional role of the encoded termination.
Strengths and Limitations
Strengths of the present study are the large sample size, the prospective design, and the complete long-term follow-up with a large number of events. Furthermore, our study highlights the challenges of genetic investigations in complex diseases such as hypertension, in which a substantial sample size is needed to detect low-to-moderate effects of 1 individual polymorphism. Some potential limitations of our study require discussion. First, we used self-reported blood pressure and hypertension status. However, the prognostic value of self-reported blood pressure in cohort studies involving US health professionals is similar compared with directly measured blood pressure values in participants of other cohort studies.14 Furthermore, the validity of this approach has been examined in the comparable Nurses Health Study, where 99% of the women who reported high blood pressure levels had their diagnosis confirmed based on medical chart review.15 Finally, self-reported blood pressure, total cholesterol, and body mass index have been shown previously in the Womens Health Study to be strong predictors of cardiovascular risk, with relative risks consistent in magnitude with those observed in other major studies.28–30 Second, this study included only white female health professionals, and our findings may not be generalizable to other populations. Third, plasma levels of natriuretic peptides are not available in the present study. Finally, we cannot exclude that the observed associations are caused by yet-to-be identified susceptibility gene(s)/locus(i) in linkage disequilibrium with the NPPA polymorphisms assessed in this study.
Perspectives
This prospective study provides evidence that NPPA gene polymorphisms are associated with a protective effect on blood pressure progression and incident hypertension. If corroborated by other large-scale prospective studies, these data suggest an important role for natriuretic peptides in blood pressure regulation and development of hypertension in humans.
| Acknowledgments |
|---|
Sources of Funding
This study was supported by grants HL-43851 and CA-47988 from the National Heart, Lung, and Blood Institute; the National Cancer Institute; and F. Hoffmann La-Roche Ltd (Basel, Switzerland). D.C. is supported by grants of the Swiss National Science Foundation (PBBSB-113207) and the Janggen-Poehn Foundation (St Gallen, Switzerland).
Disclosures
None.
Received July 9, 2007; first decision July 27, 2007; accepted October 11, 2007.
| References |
|---|
|
|
|---|
2. Haslam DW, James WP. Obesity. Lancet. 2005; 366: 1197–1209.[CrossRef][Medline] [Order article via Infotrieve]
3. Luft FC. Twins in cardiovascular genetic research. Hypertension. 2001; 37: 350–356.
4. Levin ER, Gardner DG, Samson WK. Natriuretic peptides. N Engl J Med. 1998; 339: 321–328.
5. John SW, Krege JH, Oliver PM, Hagaman JR, Hodgin JB, Pang SC, Flynn TG, Smithies O. Genetic decreases in atrial natriuretic peptide and salt-sensitive hypertension. Science. 1995; 267: 679–681.
6. Melo LG, Steinhelper ME, Pang SC, Tse Y, Ackermann U. ANP in regulation of arterial pressure and fluid-electrolyte balance: lessons from genetic mouse models. Physiol Genomics. 2000; 3: 45–58.
7. Nannipieri M, Manganiello M, Pezzatini A, De Bellis A, Seghieri G, Ferrannini E. Polymorphisms in the hANP (human atrial natriuretic peptide) gene, albuminuria, and hypertension. Hypertension. 2001; 37: 1416–1422.
8. Rutledge DR, Sun Y, Ross EA. Polymorphisms within the atrial natriuretic peptide gene in essential hypertension. J Hypertens. 1995; 13: 953–955.[CrossRef][Medline] [Order article via Infotrieve]
9. Rubattu S, Bigatti G, Evangelista A, Lanzani C, Stanzione R, Zagato L, Manunta P, Marchitti S, Venturelli V, Bianchi G, Volpe M, Stella P. Association of atrial natriuretic peptide and type a natriuretic peptide receptor gene polymorphisms with left ventricular mass in human essential hypertension. J Am Coll Cardiol. 2006; 48: 499–505.
10. Zhang S, Mao G, Zhang Y, Tang G, Wen Y, Hong X, Jiang S, Yu Y, Xu X. Association between human atrial natriuretic peptide Val7Met polymorphism and baseline blood pressure, plasma trough irbesartan concentrations, and the antihypertensive efficacy of irbesartan in rural Chinese patients with essential hypertension. Clin Ther. 2005; 27: 1774–1784.[CrossRef][Medline] [Order article via Infotrieve]
11. Ridker PM, Cook NR, Lee IM, Gordon D, Gaziano JM, Manson JE, Hennekens CH, Buring JE. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. N Engl J Med. 2005; 352: 1293–1304.
12. Rexrode KM, Lee IM, Cook NR, Hennekens CH, Buring JE. Baseline characteristics of participants in the Womens Health Study. J Womens Health Gend Based Med. 2000; 9: 19–27.[CrossRef][Medline] [Order article via Infotrieve]
13. Lee IM, Cook NR, Gaziano JM, Gordon D, Ridker PM, Manson JE, Hennekens CH, Buring JE. Vitamin E in the primary prevention of cardiovascular disease and cancer: the Womens Health Study: a randomized controlled trial. JAMA. 2005; 294: 56–65.
14. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet. 2002; 360: 1903–1913.[CrossRef][Medline] [Order article via Infotrieve]
15. Colditz GA, Martin P, Stampfer MJ, Willett WC, Sampson L, Rosner B, Hennekens CH, Speizer FE. Validation of questionnaire information on risk factors and disease outcomes in a prospective cohort study of women. Am J Epidemiol. 1986; 123: 894–900.
16. Conen D, Ridker PM, Buring JE, Glynn RJ. Risk of cardiovascular events among women with high normal blood pressure or blood pressure progression: prospective cohort study. BMJ. 2007; 335: 432.
17. Mancia G, De Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G, Grassi G, Heagerty AM, Kjeldsen SE, Laurent S, Narkiewicz K, Ruilope L, Rynkiewicz A, Schmieder RE, Boudier HA, Zanchetti A, Vahanian A, Camm J, De Caterina R, Dean V, Dickstein K, Filippatos G, Funck-Brentano C, Hellemans I, Kristensen SD, McGregor K, Sechtem U, Silber S, Tendera M, Widimsky P, Zamorano JL, Erdine S, Kiowski W, Agabiti-Rosei E, Ambrosioni E, Lindholm LH, Viigimaa M, Adamopoulos S, Agabiti-Rosei E, Ambrosioni E, Bertomeu V, Clement D, Erdine S, Farsang C, Gaita D, Lip G, Mallion JM, Manolis AJ, Nilsson PM, OBrien E, Ponikowski P, Redon J, Ruschitzka F, Tamargo J, van Zwieten P, Waeber B, Williams B. 2007 Guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2007; 25: 1105–1187.[CrossRef][Medline] [Order article via Infotrieve]
18. Cheng S, Grow MA, Pallaud C, Klitz W, Erlich HA, Visvikis S, Chen JJ, Pullinger CR, Malloy MJ, Siest G, Kane JP. A multilocus genotyping assay for candidate markers of cardiovascular disease risk. Genome Res. 1999; 9: 936–949.
19. Devlin B, Risch N. A comparison of linkage disequilibrium measures for fine-scale mapping. Genomics. 1995; 29: 311–322.[CrossRef][Medline] [Order article via Infotrieve]
20. Stephens M, Donnelly P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet. 2003; 73: 1162–1169.[CrossRef][Medline] [Order article via Infotrieve]
21. Stephens M, Scheet P. Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet. 2005; 76: 449–462.[CrossRef][Medline] [Order article via Infotrieve]
22. Stephens M, Smith NJ, Donnelly P. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet. 2001; 68: 978–989.[CrossRef][Medline] [Order article via Infotrieve]
23. Cox DR. Regression models and life tables. J Roy Stat Soc B. 1972; 34: 187–220.
24. Gruchala M, Ciecwierz D, Wasag B, Targonski R, Dubaniewicz W, Nowak A, Sobiczewski W, Ochman K, Romanowski P, Limon J, Rynkiewicz A. Association of the ScaI atrial natriuretic peptide gene polymorphism with nonfatal myocardial infarction and extent of coronary artery disease. Am Heart J. 2003; 145: 125–131.[CrossRef][Medline] [Order article via Infotrieve]
25. Ramensky V, Bork P, Sunyaev S. Human non-synonymous SNPs: server and survey. Nucleic Acids Res. 2002; 30: 3894–3900.
26. Bustamante CD, Fledel-Alon A, Williamson S, Nielsen R, Hubisz MT, Glanowski S, Tanenbaum DM, White TJ, Sninsky JJ, Hernandez RD, Civello D, Adams MD, Cargill M, Clark AG. Natural selection on protein-coding genes in the human genome. Nature. 2005; 437: 1153–1157.[CrossRef][Medline] [Order article via Infotrieve]
27. Voight BF, Kudaravalli S, Wen X, Pritchard JK. A map of recent positive selection in the human genome. PLoS Biol. 2006; 4: e72.[CrossRef][Medline] [Order article via Infotrieve]
28. Glynn RJ, LItalien GJ, Sesso HD, Jackson EA, Buring JE. Development of predictive models for long-term cardiovascular risk associated with systolic and diastolic blood pressure. Hypertension. 2002; 39: 105–110.
29. Kurth T, Gaziano JM, Rexrode KM, Kase CS, Cook NR, Manson JE, Buring JE. Prospective study of body mass index and risk of stroke in apparently healthy women. Circulation. 2005; 111: 1992–1998.
30. Huang PY, Buring JE, Ridker PM, Glynn RJ. Awareness, accuracy, and predictive validity of self-reported cholesterol in women. J Gen Intern Med. 2007; 22: 606–613.[CrossRef][Medline] [Order article via Infotrieve]
This article has been cited by other articles:
![]() |
P. M. McKie, A. Cataliotti, B. K. Huntley, F. L. Martin, T. M. Olson, and J. C. Burnett Jr A human atrial natriuretic peptide gene mutation reveals a novel peptide with enhanced blood pressure-lowering, renal-enhancing, and aldosterone-suppressing actions. J. Am. Coll. Cardiol., September 8, 2009; 54(11): 1024 - 1032. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. Vassalle and M. G. Andreassi Genetic Polymorphisms of the Natriuretic Peptide System in the Pathogenesis of Cardiovascular Disease: What Lies on the Horizon? Clin. Chem., May 1, 2009; 55(5): 878 - 887. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Karchin Next generation tools for the annotation of human SNPs Brief Bioinform, January 1, 2009; 10(1): 35 - 52. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Hypertension Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 2007 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |