(Hypertension. 2000;36:477.)
© 2000 American Heart Association, Inc.
Scientific Contributions |
Evidence for a Gene Influencing Blood Pressure on Chromosome 17
Genome Scan Linkage Results for Longitudinal Blood Pressure Phenotypes in Subjects From the Framingham Heart Study
From the National Heart, Lung, and Blood Institute Framingham Heart Study (D.L., M.G.L., C.J.D.), Framingham, Mass; the Department of Epidemiology and Biostatistics (A.L.D.S., L.A.C.), Boston University School of Public Health, Boston, Mass; the Department of Neurology (A.L.D.S., M.G.L., R.H.M.), the Cardiology Division (D.L.), the Genetics Program (A.L.D.S.), and the Hypertension Section (H.G.), Department of Medicine, Boston University School of Medicine, Boston, Mass; the Cardiology Division (C.J.D.), Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Mass; and the Howard Hughes Medical Institute (R.P.L.), Departments of Genetics and Medicine, Yale University School of Medicine, New Haven, Conn.
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Abstract |
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Abstract—Hypertension is a leading cause of morbidity and mortality. Efforts to identify hypertension genes have focused on 3 approaches: mendelian disorders, candidate genes, and genome-wide scans. Thus far, these efforts have not identified genes that contribute substantively to overall blood pressure (BP) variation in the community. A 10-centiMorgan (cM) density genome-wide scan was performed in the largest families from 2 generations of Framingham Heart Study participants. Heritability and linkage for long-term mean systolic and diastolic BP phenotypes were analyzed by use of SOLAR software. Heritability estimates were based on BP measurements in 1593 families. Genotyping was performed on 1702 subjects from 332 large families, and BP data were available for 1585 (93%) genotyped subjects who contributed 12 588 longitudinal BP observations. The mean age was 47 years, and mean BP was 127/80 (systolic/diastolic) mm Hg. Long-term systolic and diastolic BP phenotypes had high heritability estimates, 0.57 and 0.56, respectively. For systolic BP, multipoint log-of-the-odds (LOD) scores >2.0 were located on chromosome 17 at 67 cM (LOD 4.7, P=0.0000016) and 94 cM (LOD 2.2). For diastolic BP, LOD scores >2.0 were identified on chromosome 17 (74 cM, LOD 2.1) and chromosome 18 (7 cM, LOD 2.1). Using a genome-wide scan, we found strong evidence for a BP quantitative trait locus on chromosome 17. Follow-up studies are warranted to identify the gene or genes in this quantitative trait locus that influence BP. Such knowledge could extend our understanding of the genetic basis of essential hypertension and have implications for the evaluation and treatment of patients with high BP.
Key Words: genetics • genome scan • linkage • epidemiology • hypertension, essential • blood pressure • Framingham Heart Study
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Introduction |
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Hypertension affects about one quarter of adults in industrialized countries, and it contributes to considerable morbidity and mortality from stroke, heart failure, coronary heart disease, and renal failure.1 2 3 Hypertension is a complex disorder that results from the interplay of genetic and environmental influences. It is hoped that advances in understanding the genetic causes of hypertension will contribute to improvements in the diagnosis and treatment of this common condition. Three approaches to identifying genes for hypertension have been pursued: study of mendelian disorders, candidate gene evaluation, and genome-wide scans. Through the investigation of mendelian disorders affecting blood pressure (BP), several genes have been identified and characterized.4 5 6 7 8 The contribution of these rare conditions to the overall BP variation in the general population, however, is very small.
A second approach to identifying BP/hypertension genes is through the characterization of candidate genes. In recent years, a growing list of candidate genes hypothesized to influence BP has emerged, and for several of these, evidence of linkage or association with hypertension has been reported.9 10 11 12 13 To date, none of these candidate genes, however, has been shown to contribute substantively to the variation in BP in the general population.
The third approach is a genome-wide scan to identify chromosomal regions linked to BP or hypertension. Genome scan results can guide candidate gene research by according greater priority to candidates that are located within areas of linkage. Genome scanning may also identify chromosomal regions within which no known candidate genes are recognized; such a finding has the potential to identify novel BP genes. Genome scans are being used in family-based BP studies and have led to reports of multiple linkages14 15 ; however, none of the reported linkages has attained statistical significance at the genome-wide level.
The Framingham Heart Study, which began in 1948, has meticulously characterized BP and other relevant phenotypes in 2 generations of participants. A 10-centiMorgan (cM) density genome-wide scan in subjects from the largest families within the study was recently completed. The repeated measurement of BP in 2 generations of study participants has permitted the characterization of unique, longitudinal BP phenotypes unavailable in other prospective, population-based studies. In contrast to BP studies that selectively recruited hypertensive subjects, Framingham Heart Study subjects were recruited without regard to their BP. Consequently, this study is able to assess linkage across the entire range of BP values. This feature of the study may enhance the detection of linkage, because genes that affect BP may contribute not only to hypertension but also to intermediate and low BP.16 In addition, our project began in an era when hypertension was not treated; the vast majority of BP measurements that compose our longitudinal BP phenotypes were obtained in untreated individuals, thereby permitting analyses of BP as a quantitative trait, even among hypertensive individuals.
This report presents the results of linkage analyses for longitudinally measured systolic and diastolic BP phenotypes obtained in original Framingham Heart Study participants, who attended routine biennial clinic visits beginning in 1948, and their offspring, who were examined repeatedly starting in 1971.
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Methods |
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Study Subjects
The Framingham Heart Study began in 1948 with the recruitment of 5209 men and women from Framingham, Mass, who were between 28 and 62 years of age.17 Subjects underwent a medical history, physician-administered physical examination, laboratory tests, and electrocardiography. Examinations were repeated every 2 years. Beginning in 1971, 5124 offspring and spouses of offspring of original participants were recruited for similar examinations.18 The offspring cohort was reexamined 8, 12, 16, 20, and 24 years after their initial visit. At each clinic visit, the examining physician measured the seated BP twice with a mercury column sphygmomanometer. The systolic and diastolic BPs were determined by the first and fifth Korotkoff sounds, respectively. Two BP measurements were averaged to derive the systolic and diastolic pressures for that examination. Body mass index was calculated as the weight in kilograms divided by the square of height in meters (kg/m2). All subjects gave informed consent before each clinic visit, and the examination protocol was approved by the Institutional Review Board at Boston Medical Center (Boston, Mass).
BP Phenotypes
Longitudinal BP Phenotypes
All BP measurements taken when subjects were aged 25 to 75 years
were analyzed. The following criteria were stipulated: (1)
there had to be at least 10 years between a subject’s initial and
final examinations within the age range; (2) at least 4 examinations
within the age range were required for the original cohort and at least
3 for offspring cohort participants; and (3) height and weight
measurements were required, but if weight was missing, the most recent
measurement within 4 years was used.
Longitudinal BP data were analyzed for 8478 subjects who met these criteria by using a 2-stage procedure: (1) within-subject mean BP was calculated and (2) sample-wide regressions were used to adjust for age and body mass index, yielding a residual for each subject. These residuals constitute the longitudinal BP phenotypes. To calculate residuals, the following approach was taken. Let yij denote either systolic or diastolic BP for the jth examination on the ith participant, and let x1ij denote age and x2ij body mass index; also, let yi be the subject’s mean BP, and let m1i and m2i be his or her mean age and mean body mass index in the stated age range. Sample-wide regressions were used to model BP as a linear function of the subject’s mean age and mean body mass index. Specifically, the model can be stated as yi=ß0+ß1(m1i-m1)+ß2(m2i-m2 )+Ri, where m1 and m2 are sample means for age and body mass index. The residual Ri was used for the longitudinal phenotypes.
Systolic and diastolic BP phenotypes were analyzed independently. For diastolic BP, we analyzed data only for ages 25 to 54 years, because diastolic BP declines with advancing age, beginning around age 55 years.19 Also, regressions were conducted separately for each sex and cohort to accommodate sex and cohort effects.
Treated Observations
For subjects receiving hypertension treatment, the recorded
BP effectively is a right-censored value,20 since one
knows only that it is less than what the untreated value would be. We
addressed this problem by using a nonparametric algorithm
to adjust BPs for treatment effect. Data from 87 840 examinations on
10 313 subjects aged 18 to 97 years were analyzed; 13 481
(15.3%) observations reflected hypertension treatment. Separate
adjustments were conducted for men and women and for original and
offspring cohorts. Cubic regression models were fitted to account for
age effects, and then residuals were sorted from largest to smallest
within age groups (<35, 35 to 44, 45 to 54, 55 to 64, 65 to 74, and
75+). Adjustment for treatment effect proceeded within each age group.
Let r(k) denote the kth residual
sorted in descending order; let BP(k) denote the
recorded BP and let h(k)=1 if the observation
was treated, 0 otherwise. For k=1 to n, the
adjusted residual can be computed as follows:
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Genotyping
DNA was extracted from whole-blood or buffy coat specimens by
using a standard protocol.21 22 DNA aliquots from subjects
within the largest Framingham Heart Study families were sent in 4
batches to the Mammalian Genotyping Service Laboratory at the
Marshfield Clinic (Marshfield, Wis), where a 10-cM density genome scan
was performed (marker set 8A, average heterozygosity 0.77). (Details
regarding markers and primers are available on the World Wide Web at
(http://www.marshmed.org/genetics/default.htm).) Genotype data
cleaning consisted of 2 steps. Family relationships were verified on
the basis of all available markers by using the sib_kin program of the
ASPEX (ftp://lahmed.stanford.edu/pub/aspex/index.html)
package. Mendelian inconsistencies were detected and eliminated
by using the GENTEST program
(http://www.sfbr.org/sfbr/public/software/software.html).
Heritability and Linkage Analysis
Heritability estimates were obtained by using variance-component
methodology implemented in the SOLAR package23
and were based on phenotype data from 1593 families for
systolic BP and 1300 families for diastolic BP.
Two-point and multipoint quantitative trait linkage analyses
were conducted on the standardized residuals for longitudinal
systolic and diastolic BPs by using the
SOLAR package. In this approach, genotypes are
imputed for untyped individuals, conditional on all other marker data
and pedigree structure, and the proportion of marker alleles shared
identical by descent among all relative pairs is estimated. Therefore,
individuals who are not genotyped but have phenotype
data contribute to the linkage results. The pedigree-based approach of
SOLAR is more powerful than sib-pair analysis when
data on extended families are available. Linkage is assessed by fitting
a polygenic model that does not incorporate genetic marker information
(ie, identical by descent status) and comparing it with models that
incorporate genotype data at a specific marker (2-point
analysis) or across a chromosome (multipoint analysis).
The log (base 10) of the ratio of the likelihoods of the polygenic and
marker-specific models is the log-of-the-odds (LOD) score, the
traditional measure of genetic linkage.
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Study Sample
There were a total of 1702 genotyped individuals from 332 extended families, with family sizes ranging from 2 to 29 genotyped individuals. The genotyped sample included the following relative pairs: parent-offspring pairs, n=933; sibling pairs, n=1545; cousin pairs, n=742; and avuncular pairs, n=468. Criteria for analysis of longitudinal BP phenotypes were met in 2498 (1585 genotyped) subjects for systolic and 1925 (1294 genotyped) subjects for diastolic BP. The genotyped sample included 393 members of the original cohort and 1192 of the offspring cohort; 47% were men. Characteristics of the genotyped study sample are shown in Table 1. The genotyped study subjects contributed 12 588 longitudinal (repeated) BP measurements (an average of 7.9 per subject; range, 3 to 20) spanning up to 38 years for original cohort subjects and 20 years for offspring subjects. Mean age was 47 years, and mean body mass index was 26.4 kg/m2. Subjects were hypertensive (systolic BP 140 mm Hg or higher, diastolic BP 90 mm Hg or higher, or current drug treatment for high BP) at 27.9% of visits, but only 11.3% of genotyped BP observations reflected treatment with antihypertensive medication. The average BP (systolic/diastolic) was 124/78 mm Hg (unadjusted) versus 127/80 mm Hg after adjustment for hypertension treatment. Departure from normality of BP residuals was minimal, as measured by skewness (0.70 for systolic BP and 0.67 for diastolic BP) and kurtosis (0.93 for systolic BP and 0.91 for diastolic BP). Long-term systolic and diastolic BP phenotypes had high heritability estimates, 0.57 and 0.56, respectively. The corresponding heritability estimates for single-examination BPs were 0.42 and 0.39.
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Two-Point and Multipoint Linkage
The highest 2-point LOD scores for long-term systolic and
diastolic BP traits for each of the 22 autosomes are
presented in Figure 1. For
systolic BP, 2-point LOD scores of 2.0 or higher were observed
for markers on chromosomes 5 and 10 and for 2 markers on chromosome 17
(Table 2). For diastolic BP,
the only 2-point LOD score of 2.0 or higher was on chromosome 9; a LOD
score of 1.6 was found on chromosome 17 (marker GATA25A04 [D17S1299])
and a LOD score of 1.9 for chromosome 18 (AFM321xc9 [D18S481]).
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Figure 2 depicts the highest multipoint LOD scores for each of the autosomes. For systolic BP, multipoint LOD scores of 2.0 or higher were found on chromosome 17 at 2 regions (67 cM, LOD 4.7; and 94 cM, LOD 2.2; Figure 3), and an additional region of interest was identified on chromosome 5, with a multipoint LOD score of 1.9 at 23 cM. For diastolic BP, LOD scores of 2.1 were located on chromosome 17 at 74 cM (Figure 3) and on chromosome 18 at 7 cM (Figure 4). LOD scores for 2 locations that were suggestive in 2-point analyses (chromosome 10 for systolic BP and chromosome 9 for diastolic BP) diminished in the multipoint analyses (LOD scores of 0.72 and 1.2, respectively); examination of the 2-point data revealed that in each case, flanking markers showed little or no evidence of linkage (LOD scores ranged from 0.0 to 0.23), thereby reducing the magnitude of the LOD scores at these locations in the multipoint analysis.
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Discussion |
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Using a 10-cM density genome-wide scan in participants from the Framingham Heart Study, we found significant evidence of linkage of longitudinal systolic BP to chromosome 17q12–21, with a LOD score of 4.7, with odds of 50 000:1 in favor of linkage (corresponding P value of 0.0000016). To our knowledge, this is the first population-based study to report linkage of BP that attained significance at a genome-wide level.24
These results provide overwhelming evidence for a BP quantitative trait locus (QTL) in this interval. First, the LOD score substantially exceeds the minimum threshold for significant linkage in such a genome-wide study.24 Second, this interval has been implicated in hypertension.25 26 Third, there are plausible candidate genes in the interval. Fourth, the highest LOD score for diastolic BP lies in the same interval, providing corroborating evidence. Finally, this interval is homologous with BP QTLs in the rat and mouse.
A major challenge confronting the field of hypertension genetics is the need for better BP phenotypes.27 The Framingham Heart Study is unique among prospective epidemiological studies by virtue of its longevity and multigenerational structure. The serial measurement of BP in study participants facilitated the characterization of longitudinal BP phenotypes that are unavailable in newly recruited family studies. Specifically, BPs obtained in the same age interval were available for 2 generations of participants. Moreover, because the overwhelming majority of BP measurements were obtained in untreated subjects, we were able to study BP as a quantitative trait, in contrast to many current studies, which are limited to classification of qualitative phenotypes. Finally, this is 1 of a small number of large studies performing a comprehensive genome-wide analysis of linkage, rather than simply testing candidate genes or chromosome intervals, thereby permitting an unbiased search for BP QTLs. As a result, this comprehensive linkage study offers a unique and powerful approach to the detection of BP QTLs in the general population.
The LOD-1 interval (the support interval for which the LOD score equals the maximum minus 1) of the location of the chromosome 17 QTL spans a 16-cM interval at 17q12–21, flanked by loci GGAA7D11 (D17S1293) and GATA49C09 (D17S1290). This interval is of great interest, as it has been previously implicated in BP variation in humans. Pseudohypoaldosteronism type II, an autosomal dominant form of hypertension with hyperkalemia, is linked to this interval.28 Moreover, 2 other studies have provided evidence of increased allele sharing among hypertensive siblings at this location, although neither of these studies reached the threshold for significance in a genome-wide analysis.25 26 This QTL is also of particular interest, because it is syntenic with a QTL on rat chromosome 10 that was reported to be linked to hypertension in several studies of spontaneously hypertensive rats.29 30 31 32 Furthermore, in a salt-sensitive hypertensive mouse strain, Paigen et al33 found linkage to BP on mouse chromosome 11 that is homologous with rat chromosome 10q and human chromosome 17q, indicating a remarkable concordance across 3 species.
Examination of databases reveals many known genes and expressed
sequence tags in or near the 16-cM QTL interval at 17q12–21. No genes
that have been strongly implicated in BP variation lie in this
interval; however, potential candidate genes in the interval include
the 
-1 thyroid receptors, the neuronal homologue of the
amiloride-sensitive epithelial sodium channel, the
corticotropin-releasing hormone receptor 1, insulinlike growth
factor–binding protein-4, hepatocyte nuclear factor 1-ß,
and the chloride/bicarbonate exchanger AE1. It also is possible that
the gene underlying the QTL locus has not yet been identified.
In addition to the chromosome 17q12–21 interval, there are 2 additional regions yielding LOD scores >2.0 in multipoint analyses. One of these lies just distal on chromosome 17, and it is possible that this locus is independent of our largest peak. This second chromosome 17 peak overlaps the locus encoding the angiotensin-converting enzyme locus,34 a much-studied candidate gene for hypertension.10 The final locus is on chromosome 18, an interval that, to our knowledge, has not been previously implicated in BP variation. An interesting candidate gene in the chromosome 18 interval is the melanocortin receptor 2, which is the physiological receptor for corticotropin. Given the known effects of glucocorticoids on BP, it is of interest that receptors involved in the regulation of cortisol secretion lie in both the chromosome 17 and chromosome 18 intervals. The locations on chromosomes 5, 9, and 10 identified in 2-point analyses remain regions of interest, despite the reduced evidence of linkage in the multipoint analyses. Reasons for differences in LOD scores between 2-point and multipoint results include map or genotyping errors, large gaps between adjacent markers, or isolated false-positive results.
Study Strengths and Limitations
The Framingham Heart Study recruited 2 generations of subjects
without regard to their BP and followed them up prospectively. BP
phenotypes were sex-specific and were adjusted for age and body
mass index, the 2 leading determinants of BP in the general population.
The high estimates of heritability of our long-term BP
phenotypes, 0.57 for systolic and 0.56 for
diastolic BP, are considerably higher than those of
single-examination systolic and diastolic BP, 0.42
and 0.39, respectively, and are an indication of the far greater value
of the long-term BP phenotypes available in the Framingham
data.
The study has several potential limitations. First, although we believe
that the adjustment of BP for subjects who were receiving
antihypertensive drug treatment is a major strength of our study, it is
possible that it introduced a degree of misclassification. Of note,
evidence for linkage at our most promising regions remained when actual
BP measurements were used in place of adjusted values. Second, this
study is based on a sample of white subjects. The extent to which our
findings apply to other racial or ethnic groups, in whom the prevalence
of hypertension differs from that in whites and in whom a different mix
of genes may be important in BP regulation, deserves investigation.
Third, there are likely to be additional QTLs involved in the
expression of BP that we were unable to detect. Specifically, there was
ample power to detect a QTL that explains 25% to 30% of the variation
in BP. On the basis of the pedigree structure in the current study, we
had 75% to 80% power to detect LOD scores >3 for a QTL that explains
25% of the variation, and >90% power to detect a QTL that explains
30% of the variation, but <50% power to detect an LOD score >3 for
a QTL that explains 20% of the variation. To detect an LOD score >2,
we had 
70% to 75% power for a QTL that explains 20% of the
variation but <50% power for a QTL that explains only 15% of the
variation. Fourth, it is possible that some of the positive linkage
findings represent false results. Based on the pedigree
structure of the 332 families used for linkage in this investigation,
simulation studies indicate that in the absence of linkage, the mean
number of 2-point LOD scores >2 that can be expected for this genome
scan is 0.5.35 We observed LOD scores >2 for 4 markers
for systolic BP and for 1 marker for diastolic BP,
several more than would be expected by chance.
Future Directions
Progress in identification of the chromosome 17q QTL can progress
on several fronts. Success in positional cloning of the genes
underlying pseudohypoaldosteronism type II and the syntenic rodent QTL
has the potential to identify the gene underlying this BP QTL. The
location of the QTL itself can potentially be refined by genotyping
additional markers and analyzing linkage in the critical interval.
Moreover, genes in the interval can be screened for variants, and these
can be examined for linkage disequilibrium with BP. Evaluation of the
functional consequences of identified variants in vitro or in animal
models can strengthen evidence for putative functional variants.
Ultimately, the genes contributing to BP variance will be pinpointed from BP QTLs, and their functional mutations will be identified. The completion of a draft version of the human genome sequence will identify and precisely locate roughly 90% of all human genes, greatly augmenting efforts to identify QTLs underlying human disease. Our finding of at least 1 BP QTL in the general population increases the likelihood that identification of the underlying gene or genes may prove clinically important for the evaluation and treatment of patients with hypertension.
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Acknowledgments |
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The Framingham Heart Study is supported by the National Heart, Lung, and Blood Institute (NHLBI, National Institutes of Health), Bethesda, Md, through contract N01-HC-38038. Portions of this work were supported by National Institutes of Health/US Public Health Service SCOR in Hypertension grants P50HL55001 (to A.L.D. and H.G.) and P50HL55007 (to R.P.L.). R.P.L. is an investigator of the Howard Hughes Medical Institute. The authors would like to acknowledge the contributions of Drs Ernst J. Schaefer and Jose M. Ordovas, who isolated the DNA that made this study possible, with funding from NHLBI grant HL54776 (to J.M.O.).
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Footnotes |
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Reprint requests to Daniel Levy, MD, Framingham Heart Study, 5 Thurber St, Framingham, MA 01702.
Received May 30, 2000; first decision June 12, 2000; accepted June 28, 2000.
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P. M. Erlich, J. Cui, I. Chazaro, L. A. Farrer, C. T. Baldwin, H. Gavras, and A. L. DeStefano Genetic Variants of WNK4 in Whites and African Americans With Hypertension Hypertension, June 1, 2003; 41(6): 1191 - 1195. [Abstract] [Full Text] [PDF]
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X. Zhu, Y.-P. C. Chang, D. Yan, A. Weder, R. Cooper, A. Luke, D. Kan, and A. Chakravarti Associations Between Hypertension and Genes in the Renin-Angiotensin System Hypertension, May 1, 2003; 41(5): 1027 - 1034. [Abstract] [Full Text] [PDF]
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Y. Y. Fadl, W. Zareba, A. J. Moss, V. J. Marder, C. S. Sparks, L. F. Miller Watelet, and E. R. Carroll History of Hypertension and Enhanced Thrombogenic Activity in Postinfarction Patients Hypertension, April 1, 2003; 41(4): 943 - 949. [Abstract] [Full Text] [PDF]
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J. Monti, H. Zimdahl, H. Schulz, R. Plehm, D. Ganten, and N. Hubner The Role of Wnk4 in Polygenic Hypertension: A Candidate Gene Analysis on Rat Chromosome 10 Hypertension, April 1, 2003; 41(4): 938 - 942. [Abstract] [Full Text] [PDF]
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C. S. Fox, J. F. Polak, I. Chazaro, A. Cupples, P. A. Wolf, R. A. D'Agostino, and C. J. O'Donnell Genetic and Environmental Contributions to Atherosclerosis Phenotypes in Men and Women: Heritability of Carotid Intima-Media Thickness in the Framingham Heart Study Stroke, February 1, 2003; 34(2): 397 - 401. [Abstract] [Full Text] [PDF]
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J. S. Cui, J. L. Hopper, and S. B. Harrap Antihypertensive Treatments Obscure Familial Contributions to Blood Pressure Variation Hypertension, February 1, 2003; 41(2): 207 - 210. [Abstract] [Full Text] [PDF]
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 D. Gordon, M. B. Corwin, C. S. Mellersh, E. A. Ostrander, and J. Ott Establishing Appropriate Genome-Wide Significance Levels for Canine Linkage Analyses J. Hered., January 1, 2003; 94(1): 1 - 7. [Abstract] [Full Text] [PDF]
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G. Engstrom, L. Janzon, G. Berglund, P. Lind, L. Stavenow, B. Hedblad, and F. Lindgarde Blood Pressure Increase and Incidence of Hypertension in Relation to Inflammation-Sensitive Plasma Proteins Arterioscler Thromb Vasc Biol, December 1, 2002; 22(12): 2054 - 2058. [Abstract] [Full Text] [PDF]
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C. Barlassina, C. Lanzani, P. Manunta, and G. Bianchi Genetics of Essential Hypertension: From Families to Genes J. Am. Soc. Nephrol., November 1, 2002; 13(90003): S155 - 164. [Abstract] [Full Text]
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R. S. Cooper, A. Luke, X. Zhu, D. Kan, A. Adeyemo, C. Rorimi, N. Bouzekri, and R. Ward Genome Scan Among Nigerians Linking Blood Pressure to Chromosomes 2, 3, and 19 Hypertension, November 1, 2002; 40(5): 629 - 633. [Abstract] [Full Text] [PDF]
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T. A. Kotchen, U. Broeckel, C. E. Grim, P. Hamet, H. Jacob, M. L. Kaldunski, J. M. Kotchen, N. J. Schork, P. J. Tonellato, and A. W. Cowley Jr Identification of Hypertension-Related QTLs in African American Sib Pairs Hypertension, November 1, 2002; 40(5): 634 - 639. [Abstract] [Full Text] [PDF]
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M. Tomaszewski, N. J.R. Brain, F. J. Charchar, W. Y.S. Wang, B. Lacka, S. Padmanabahn, J. S. Clark, N. H. Anderson, H. V. Edwards, E. Zukowska-Szczechowska, et al. Essential Hypertension and {beta}2-Adrenergic Receptor Gene: Linkage and Association Analysis Hypertension, September 1, 2002; 40(3): 286 - 291. [Abstract] [Full Text] [PDF]
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S. C. Hunt, R. C. Ellison, L. D. Atwood, J. S. Pankow, M. A. Province, and M. F. Leppert Genome Scans for Blood Pressure and Hypertension: The National Heart, Lung, and Blood Institute Family Heart Study Hypertension, July 1, 2002; 40(1): 1 - 6. [Abstract] [Full Text] [PDF]
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K. Kristjansson, A. Manolescu, A. Kristinsson, T. Hardarson, H. Knudsen, S. Ingason, G. Thorleifsson, M. L. Frigge, A. Kong, J. R. Gulcher, et al. Linkage of Essential Hypertension to Chromosome 18q Hypertension, June 1, 2002; 39(6): 1044 - 1049. [Abstract] [Full Text] [PDF]
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H. Zimdahl, T. Kreitler, C. Gosele, D. Ganten, and N. Hubner Conserved Synteny in Rat and Mouse for a Blood Pressure QTL on Human Chromosome 17 Hypertension, June 1, 2002; 39(6): 1050 - 1052. [Abstract] [Full Text] [PDF]
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 B. Swynghedauw Susceptibility-conferring polymorphic genotypes in cardiovascular multifactorial syndromes Eur. Heart J., February 2, 2002; 23(4): 271 - 273. [Full Text] [PDF]
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P. A. Doris Hypertension Genetics, Single Nucleotide Polymorphisms, and the Common Disease:Common Variant Hypothesis Hypertension, February 1, 2002; 39(2): 323 - 331. [Abstract] [Full Text] [PDF]
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 S-Y Wu, C S J Fann, Y-S Jou, J-W Chen, and W-H Pan Association between markers in chromosomal region 17q23 and young onset hypertension: a TDT study J. Med. Genet., January 1, 2002; 39(1): 42 - 44. [Full Text] [PDF]
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S. Francke, M. Manraj, C. Lacquemant, C. Lecoeur, F. Lepretre, P. Passa, A. Hebe, L. Corset, S. L. K. Yan, S. Lahmidi, et al. A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16p13 and replicates linkage with the metabolic syndrome on 3q27 Hum. Mol. Genet., November 1, 2001; 10(24): 2751 - 2765. [Abstract] [Full Text] [PDF]
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M. R. Garrett, X. Zhang, O. I. Dukhanina, A. Y. Deng, and J. P. Rapp Two Linked Blood Pressure Quantitative Trait Loci on Chromosome 10 Defined by Dahl Rat Congenic Strains Hypertension, October 1, 2001; 38(4): 779 - 785. [Abstract] [Full Text] [PDF]
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 F. H. Wilson, S. Disse-Nicodeme, K. A. Choate, K. Ishikawa, C. Nelson-Williams, I. Desitter, M. Gunel, D. V. Milford, G. W. Lipkin, J.-M. Achard, et al. Human Hypertension Caused by Mutations in WNK Kinases Science, August 10, 2001; 293(5532): 1107 - 1112. [Abstract] [Full Text] [PDF]
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 S. B. Harrap and S. Petrou Utility of genetic approaches to common cardiovascular diseases Am J Physiol Heart Circ Physiol, July 1, 2001; 281(1): H1 - H6. [Full Text] [PDF]
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T. Rankinen, P. An, T. Rice, G. Sun, Y. C. Chagnon, J. Gagnon, A. S. Leon, J. S. Skinner, J. H. Wilmore, D. C. Rao, et al. Genomic Scan for Exercise Blood Pressure in the Health, Risk Factors, Exercise Training and Genetics (HERITAGE) Family Study Hypertension, July 1, 2001; 38(1): 30 - 37. [Abstract] [Full Text] [PDF]
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F. C. Luft and A. Busjahn Peaks and Valleys Hypertension, July 1, 2001; 38(1): 38 - 40. [Full Text] [PDF]
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 N. Padmanabhan, S. Padmanabhan, and J. M. Connell Genetic basis of cardiovascular disease -- the renin-angiotensin-aldosterone system as a paradigm Journal of Renin-Angiotensin-Aldosterone System, December 1, 2000; 1(4): 316 - 324. [PDF]
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R. N. Re On the Sequencing of the Human Genome Hypertension, October 1, 2000; 36(4): 469 - 470. [Full Text] [PDF]
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S. B. HARRAP, Z. Y. H. WONG, M. STEBBING, A. LAMANTIA, and M. BAHLO Blood pressure QTLs identified by genome-wide linkage analysis and dependence on associated phenotypes Physiol Genomics, February 28, 2002; 8(2): 99 - 105. [Abstract] [Full Text] [PDF]
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