Published online before print July 21, 2003, doi: 10.1161/01.HYP.0000084874.85653.46
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(Hypertension. 2003;42:322.)
© 2003 American Heart Association, Inc.
Scientific Contributions |
Genome-Wide Multipoint Parametric Linkage Analysis of Pulse Pressure in Large, Extended Utah Pedigrees
From Genetic Epidemiology (N.J.C.), Department of Medical Informatics; Cardiovascular Genetics (P.N.H., S.C.H.), Department of Internal Medicine; the Department of Human Genetics (S.J.H., A.M., R.M.C.); and the Department of Psychiatry (H.C.), University of Utah School of Medicine, Salt Lake City.
Correspondence to Nicola J. Camp, PhD, Genetic Epidemiology, Department of Medical Informatics, University of Utah School of Medicine, 391 Chipeta Way, Suite D, Salt Lake City, UT 84108-1206. E-mail nicki{at}genepi.med.utah.edu
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Abstract |
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High pulse pressure, a measure of arterial aging, is an important predictor of cardiovascular and general mortality. It has been suggested that the genetic etiology of pulse pressure is the same as systolic blood pressure. We performed a genome-wide, multipoint, parametric linkage analysis in 26 large, extended Utah pedigrees to locate genes affecting pulse pressure. Four parametric models were considered, including dominant and recessive modes of inheritance involving genes for high and low pulse pressure. Linkage analysis revealed 11 regions with a logarithm of the odds (LOD) >1.5, including 2 regions attaining genome-wide suggestive evidence for linkage after accounting for multiple tests. Inspecting pedigree-specific multipoint linkage evidence suggested that these 2 regions localized to 15.7 cM on chromosome 8p (LOD=2.89), between markers D8S136 and D8S1477, and 20.0 cM on chromosome 12q (LOD=2.59), between D12S1300 and D12S2070. Both regions were identified better by pulse pressure compared with equivalent analyses with systolic or diastolic blood pressure. Results for pulse pressure overlapped favorably with those of others for related blood pressure phenotypes and support the hypothesis that genes with pleiotropic effects on blood pressure phenotypes do exist, but that the genetic etiologies are not identical. In conclusion, our results suggest that pulse pressure might be of use for identifying genes involved in blood pressure phenotypes and arterial aging.
Key Words: arteries • genetics • linkage analysis • epidemiology • pulse • aging
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Introduction |
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There is mounting evidence that high pulse pressure (PP, calculated as the difference between systolic and diastolic blood pressures) is an independent and important component of risk to cardiovascular disease and mortality and might be a superior predictor to systolic blood pressure (SBP). In men >60 years, both SBP and PP were found to be predictors of cardiovascular disease,1 and high PP was found to be an independent risk factor for total and cardiovascular mortality in several studies.2–6 PP has been suggested to be superior to SBP as a predictor of carotid stenosis7 and coronary heart disease8 and was found to be superior to SBP, and independent of diastolic blood pressure (DBP), for predicting coronary heart failure.9 The superiority of PP was also suggested for predicting cardiovascular and total mortality.6
DBP first increases with age and then levels off or decreases after age 50 years, whereas SBP increases throughout life.10–13 PP therefore increases with age and is correlated with SBP. The age-dependent increase in PP (and SBP) is largely determined by the progressive stiffening of the central elastic arteries and reflects the biologic aging of the arterial system.12,14–16 PP is therefore regarded as an index of arterial aging. In the spontaneously hypertensive rat, PP has also been shown to be associated with arterial stiffness.17 This leads to the hypothesis that hypertension is due to acceleration of arterial aging18 and is a disorder of aging.19
Little is currently known of the genetic basis for PP variation in the population. There is empirical evidence to suggest that the genetic etiologies of the steady-state and pulsatile components of blood pressure are different. Genome-wide linkage analyses for both SBP and DBP do not systematically produce coincident loci of interest, although some do overlap.20–25 In the Lyon hypertensive rat, different loci are involved in the steady and pulsatile components.26 SBP and PP are both measures of the pulsatile component of blood pressure. Of interest is whether PP is a superior trait for identifying genetic loci for pulsatile blood pressure and whether the same genetics underlies SBP and PP. Thus far, only a single genome-wide linkage analysis has been performed for PP,27 which suggested a common genetic etiology for SBP and PP. This study aims to further investigate the genetic determinants for the various components of blood pressure.
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Methods |
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Study Subjects
Ninety-eight pedigrees were ascertained for early coronary heart disease deaths, early strokes, and early-onset hypertension. Most pedigrees were ascertained as relatives (4 to 7 generations) of sibships with at least 2 coronary heart disease deaths <55 years or stroke deaths <75 years. The initial sibships were identified from a state-wide registry of 140 000 death records computer-linked to genealogic records for 1.2 million Utahns.28 The remaining pedigrees were ascertained from probands from the Utah Center for Hypertension Detection and Follow-up Program. Clinical, biochemical, medication, and questionnaire variables have been previously described.29 Sitting blood pressures were measured by an automated machine that traced the blood pressure waveform onto a disk for subsequent reading (Infrasonde SR-2, Sphygmetrics, Inc); the mean of 4 measurements was used for analysis. PP was calculated as the difference between SBP and DBP and was available for 2444 individuals (Table 1). Genotyping for 1916 subjects was provided by the Mammalian Genotyping Service (set 10). Incompatibilities and genotyping errors were identified by PAP30 and PEDCHECK,31 resolved, or deleted. Markers were analyzed by using Marshfield map positions (http://research.marshfieldclinic.org/genetics). Maximum-likelihood marker-allele frequencies were calculated from the data.
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Twenty-six large, extended pedigrees were chosen from the 98 to maximize the statistical power to detect linkage under heterogeneity. The pedigrees selected were those with expected logarithm of the odds (ELOD) scores32,33 
0.5 for 1 of the 4 genetic analysis models (see Statistical Methods). These more powerful pedigrees allow for a more informative analysis under heterogeneity, because each has the potential to show both positive and negative linkage evidence. The uninformative pedigrees add "noise" with little additional power and hence, were not considered for analysis. The pedigrees analyzed ranged in size from 16 to 175 members, for whom both phenotypic and genotypic data were available for between 13 and 100 individuals (1454 total subjects). All pedigree members who participated in the study gave informed consent. The study design and protocols were approved by appropriate institutional review boards at the University of Utah.
Statistical Analyses
Phenotype
PP for unmedicated subjects was adjusted in a multiple regression model for sex, age, age2, and body mass index before linkage analysis. It has been suggested that antihypertensive drugs have direct arterial wall effects.34 For the 125 subjects taking antihypertensive medications, a PP value of 55 mm Hg was assigned for analysis, unless their observed medicated value was higher, in which case that value was used. This approach assumes that medicated individuals had a minimum PP of 55 mm Hg at the time of treatment onset. This fixed value compares well with that from other studies35,9 (53 and 62 mm Hg, respectively). In our population, 55 mm Hg corresponds to 1 SD above the population mean for unmedicated individuals after correction for sex, age, age2, and body mass index (Table 1). One hundred individuals were assigned a value of 55 mm Hg, and 25 retained their observed values. A substitution approach for managing medicated subjects has many advantages. These individuals contribute important information to the familial component of PP variance and should lead to increased power.36,37 There is no overcorrection and loss of power, which might occur when using methods such as regression to correct for medication. It remains conservative, because fixing a large number of individuals at the same value leads to a decrease in the overall phenotypic variability.
Linkage Analysis
Multipoint, quantitative, parametric analyses were performed by MCLINK, a Markov chain Monte Carlo method that uses blocked Gibbs sampling38 to estimate the multipoint inheritance vectors and that can be performed on large, extended pedigrees without any reduction in pedigree structure.39 For each of 4 genetic models, the TLOD ("theta" LOD) linkage statistic was calculated.40,41 The TLOD is a robust, multipoint linkage statistic that is a combination of multipoint and 2-point linkage paradigms. Multipoint inheritance vectors are estimated from all available marker data and are used to determine the inheritance probabilities for specific markers. A 2-point paradigm is then implemented to calculate the linkage statistic, maximized over the recombination fraction (
), hence "theta" LOD. Classic multipoint linkage analysis does not maximize over , rather =0, and is not robust to errors in the specified genetic model.42 HOMOG32 was used to calculate heterogeneity TLODs.
Genetic Models
Commingling analysis was performed to estimate genetic parameters for the parametric model. There was significant evidence that 2 normal distributions with means of 44.77 mm Hg and 59.53 mm Hg (SD=8.81 mm Hg) fit the phenotypic data better than did a single normal distribution (P<1.0x10-10). The penetrance functions were constructed on the basis of the ratio of the normal density functions, as is standard in quantitative parametric modeling. Models for high and low PP were developed, such that the "disease" allele predisposed to high or low PP, respectively. Both dominant and recessive models were considered. Gene frequencies were selected to be 0.01 for dominant models and 0.10 for recessive models.43
Significance Thresholds
Genome-wide thresholds to account for multiple testing of markers and models were calculated.44 This method extends that previously proposed for an infinitely dense marker map for a single model.45 For our data, these thresholds were 2.5 (P=3.5x10-4) for suggestive genome-wide evidence (1 false-positive across all genome-wide analyses) and 3.8 (P=1.4x10-5) for significant evidence (0.05 false-positive). In addition to these 2 thresholds, we report all linkage findings >1.5 (P=0.004) to allow for comparison with other studies.
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Results |
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Heritability and Power
The heritability of PP was estimated to be 0.25 and was highly significant (P<1.0x10-7). In the same sample, heritabilities for SBP and DBP were lower, 0.19 and 0.21, respectively, but also highly significant. All estimates were calculated with SOLAR.46
Pedigree ELODs ranged from 0.531 to 2.753. Power varied by model and was highest for the low-dominant model and lowest for the high-recessive model. The high-recessive model indicated only reasonable evidence to detect linkage signals at the 1.5 level and is not discussed further. With the assumption of no heterogeneity, the 3 remaining models indicated good power (>80%) to detect suggestive evidence for linkage, and both low models had excellent power (>95%) for significant evidence. In addition, under heterogeneity of 50%, all 3 models had at least 50% power to detect linkage signals >1.5. The low models were superior and maintained good power (>75%) to detect genome-wide suggestive evidence for linkage.
Linkage Results for PP
Table 2 shows the 11 regions on 9 chromosomes with TLOD >1.5 for PP. Two regions on chromosomes 8p and 12q were found with genome-wide suggestive evidence for linkage accounting for all multiple tests (TLOD >2.5, P<3.5x10-4). On chromosome 8p, TLOD=2.89 for marker D8S1048 at 54.28 cM and on chromosome 12q, TLOD=2.59 for marker PAH at 109.47 cM. Both signals were found for the high-dominant model.
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To test the robustness of linkage findings to the substituted value for medicated individuals, we also analyzed the data by first, excluding these individuals (recoded with unknown status) and then allowing their medicated values to be used. All linkage regions remained under both analyses, although the height of the linkage peaks varied (±0.65). In particular, the regions on chromosomes 8p and 12q remained genome-wide suggestive for linkage in all analyses (8p, 2.89 [55 mm Hg]; 2.79 [excluded] and 3.04 [medicated values]; and 12q, 2.59 (55 mm Hg); 2.59 [excluded] and 3.24 [medicated values]). In addition, a quantitative, nonparametric linkage analysis with the value of 55 mm Hg for medicated individuals was performed. No linkage results with an LOD >1.5 were found.
Localization of Genome-Wide Suggestive Regions
For localization, the regions on chromosomes 8p and 12q were investigated in a pedigree-specific manner by classic multipoint LOD analysis (=0). Pedigrees with LOD >0.588 (nominal P=0.05) were identified for each region, and multipoint LOD evidence was plotted against centimorgan position. A sum of LOD values for linked pedigrees (sumLOD) was calculated to illustrate the combined localization evidence for linked pedigrees. In each pedigree, recombinant events, which define the shared region between individuals with similar quantitative scores, can be estimated by the position at which linkage evidence decreases. We considered a drop of >0.5 LOD unit to indicate a recombination event and conservatively considered the outer marker as the recombinant position. Region sizes were estimated both by pedigree recombinant boundary positions and by the 1-LOD drop from the peak of the sumLOD. Figures 1 and 2
illustrate the pedigree-specific support for the regions on chromosomes 8p and 12q, respectively. Table 3 shows additional characteristics for both regions.
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For both regions, several linked pedigrees were identified, with no conflicting recombinants for region localization. The multipoint sumLODs were high for both regions (8p, 8.38; 12q, 5.16). Estimated region sizes were relatively large, as would be expected for a genome-wide map with an average resolution of 9.5 cM. However, the slow decrease in the pedigree LOD evidence across several markers indicated that markers were not informative in all haplotype carriers in these pedigrees, and the positions of recombinants could not be clearly pinpointed. This suggests that both regions could be narrowed by increasing marker density. With the current data, the minimum region size on chromosome 8p is 7.1 cM and on chromosome 12q is 10.3 cM, both estimated statistically from the 1-LOD drop from the sumLOD peak.
Overlap With Regions for SBP and DBP
For comparison, linkage analyses of SBP and DBP were performed. Table 4 includes results found in the current study for SBP or DBP (TLOD >1.0) in the PP regions (Table 3). Of note is that the chromosome 8p region was not identified for either SBP or DBP and that the region on chromosome 12q was substantially higher for PP (2.59 compared with 1.21 for DBP). Of the remaining 9 regions, PP scores were superior for 3 regions (+0.48 to +1.52), similar for 5 regions (-0.40 to +0.41), and inferior for 1 region on chromosome 3p (-0.49). Table 5 shows 5 regions on chromosomes 3, 4, 6, 10, and 18 that were identified for SBP or DBP (TLOD >1.5) but not by PP.
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Discussion |
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Our findings, similar to those of Atwood and colleagues,27 illustrate considerable concordance between regions identified for PP and for SBP and DBP. However, in contrast, we found that some regions were clearly identified better by PP, with 3 regions that were not identified at all with SBP or DBP (8p, 8q, and 16p). Of course, we do not know which if any of the regions are true or false-positives, so issues of power cannot be assessed by our study. However, it does suggest that these traits do not always segregate in precisely the same way and that 1 trait cannot simply be used as a proxy for another. In particular, we have identified 2 genome-wide suggestive regions for PP, localized to a 7.1 cM region and a 10.3 cM region on chromosomes 8p and 12q, respectively, that would have been overlooked had only the more standard SBP or DBP analysis been performed. The superior linkage evidence for PP in the current study might suggest that these regions contain genes more closely tied to variation in vessel stiffness.
Comparison With Published Results
We know of only 1 other genome-wide linkage analysis of PP.27 For meaningful comparison, all marker positions have been converted to those specified on the current Marshfield genetic map. Regions identified with linkage evidence >1.5 by this prior study27 were on chromosome 7 (2.04; D7S1799 at Marshfield position 113.92 cM), chromosome 8 (1.98; D8S1100 at 154.02 cM), chromosome 18 (1.95; D18S844 at 116.44 cM), chromosome 20 (1.58; D20S477 at 45.89 cM), and chromosome 21 (2.78; D21S1440 at 36.77 cM). Table 4 shows the 15 regions identified for PP (LOD >1.5) in either the current study or that of Atwood and colleagues.27 Overlapping signals between these 2 PP studies are illustrated, in addition to published findings in these locations for other blood pressure traits.
Only modest overlap was observed between the current study and that of Atwood and colleagues27 when they were compared for signals for PP alone. One region on chromosome 8q contained linkage evidence >1.5 in both the current and the Atwood27 study (1.53 and 1.98, respectively). This region on chromosome 8q appears distinct from the one strongly suggested by the current study on 8p, because the linkage evidence in both studies decreases appreciably in between and neither region appears to be merely residual linkage evidence from the other. However, the 2-point LOD scores used by Atwood and colleagues27 are not ideal for localization.
Comparison of the 15 PP regions (11 from the current study, 5 from Atwood et al,27 1 overlapping) with those published for other blood pressure traits20–24,36,47–51 are also shown in Table 4. Published linkage signals for SBP, DBP, hypertension, mean arterial pressure, postural change in SBP, and orthostatic hypotensive disorder were found to overlap with regions identified for PP. It is interesting to note that for 7 of the total 15 regions, the linkage signal was higher for PP (either in the current or the Atwood study27) by +0.17 to +1.38 LOD units compared with all other studies of blood pressure traits. However, there are difficulties in directly comparing LODs that use different linkage methods across studies,52 and this should be borne in mind.
Perspectives
Our results support the hypothesis that there are genes with pleiotropic effects on multiple blood pressure traits. However, the genetic etiologies of these traits might not be identical, and unique gene pathways might exist for the different components of blood pressure, both between and within the pulsatile and steady components. The results here suggest that PP might be useful for identifying regions and genes involved in both arterial aging and blood pressure phenotypes.
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Acknowledgments |
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This study was supported by grants HL21088, HL24855, HL44738, and AG18734. Genotyping was provided by the Mammalian Genotyping Service.
Received March 26, 2003; first decision April 22, 2003; accepted June 24, 2003.
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References |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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1. Sesso HD, Stampfer MJ, Rosner B, Hennekens CH, Gaziano JM, Manson JE, Glynn RJ. Systolic and diastolic blood pressure, pulse pressure, and mean arterial pressure as predictors of cardiovascular disease risk in men. Hypertension. 2000; 36: 801–807.
2. Madhavan S, Ooi WL, Cohen H, Alderman MH. Relation of pulse pressure and blood pressure reduction to the incidence of myocardial infarction. Hypertension. 1994; 23: 395–401.
3. Mitchell GF, Moye LA, Braunwald E, Rouleau JL, Bernstein V, Geltman EM, Flaker GC, Pfeffer MA, for the SAVE Investigators. Sphygmomanometrically determined pulse pressure is a powerful independent predictor of recurrent events after myocardial infarction in patients with impaired left ventricular function. Circulation. 1997; 96: 4254–4260.
4. Benetos A, Safar M, Rudnichi A, Smulyan H, Richard JL, Ducimetiere P, Guize L. Pulse pressure: a predictor of long-term cardiovascular mortality in a French male population. Hypertension. 1997; 30: 1410–1415.
5. Benetos A, Rudnichi A, Safar M, Guize L. Pulse pressure and cardiovascular mortality in normotensive and hypertensive subjects. Hypertension. 1998; 32: 560–564.
6. Glynn RJ, Chae CU, Guralnik JM, Taylor JO, Hennekens CH. Pulse pressure and mortality in older people. Arch Intern Med. 2000; 160: 2765–2772.
7. Franklin SS, Sutton-Tyrrell K, Belle SH, Weber MA, Kuller LH. The importance of pulsatile components of hypertension in predicting carotid stenosis in older adults. J Hypertens. 1997; 15: 1143–1150.[CrossRef][Medline] [Order article via Infotrieve]
8. Franklin SS, Khan SA, Wong ND, Larson MG, Levy D. Is pulse pressure useful in predicting risk for coronary heart Disease? the Framingham heart study. Circulation. 1999; 100: 354–360.
9. Chae CU, Pfeffer MA, Glynn RJ, Mitchell GF, Taylor JO, Hennekens CH. Increased pulse pressure and risk of heart failure in the elderly. JAMA. 1999; 281: 634–639.
10. Welton PK, He J, Klag MJ. Blood pressure in Westernized populations. In: Swales JD, ed. Textbook of Hypertension. London, UK: Blackwell Scientific Publications; 1994: 11–21.
11. Franklin SS, Gustin W 4th, Wong ND, Larson MG, Weber MA, Kannel WB, Levy D. Hemodynamic patterns of age-related changes in blood pressure: the Framingham Heart Study. Circulation. 1997; 96: 308–315.
12. Nichols WW, O’Rourke MF. McDonald’s Blood Flow in Arteries: Theoretical, Experimental and Clinical Principals, 4th ed. London/Sydney/Auckland: Arnold; 1998: 347–376.
13. Izzo JL Jr, Levy D, Black HR. Clinical advisory statement: importance of systolic blood pressure in older Americans. Hypertension. 2000; 35: 1021–1024.
14. Cooper LT, Cooke JP, Dzau VJ. The vasculopathy of aging. J Gerontol. 1994; 49: B191–B196.[CrossRef][Medline] [Order article via Infotrieve]
15. Bilato C, Crow MT. Atherosclerosis and the vascular biology of aging. Aging. 1996; 8: 221–234.[Medline] [Order article via Infotrieve]
16. O’Rourke MF, Mancia G. Arterial stiffness. J Hypertens. 1999; 17: 1–4.[Medline] [Order article via Infotrieve]
17. Safar M, Chamiot-Clerc P, Dagher G, Renaud JF. Pulse pressure, endothelium function, and arterial stiffness in spontaneously hypertensive rats. Hypertension. 2001; 38: 1416–1421.
18. Liu ZR, Ting CT, Zhu SX, Yin FC. Aortic compliance in human hypertension. Hypertension. 1989; 14: 129–136.
19. Aviv A. Hypothesis: pulse pressure and human longevity. Hypertension. 2001; 37: 1060–1066.
20. Levy D, DeStefano AL, Larson MG, O’Donnell CJ, Lifton RP, Gavras H, Cupples LA, Myers RH. 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. Hypertension. 2000; 36: 477–483.
21. Rice T, Rankinen T, Province MA, Chagnon YC, Perusse L, Borecki IB, Bouchard C, Rao DC. Genome-wide linkage analysis of systolic and diastolic blood pressure: the Quebec Family Study. Circulation. 2000; 102: 1956–1963.
22. Hsueh WC, Mitchell BD, Schneider JL, Wagner MJ, Bell CJ, Nanthakumar E, Shuldiner AR. QTL influencing blood pressure maps to the region of PPH1 on chromosome 2q31–34 in Old Order Amish. Circulation. 2000; 101: 2810–2816.
23. Atwood LD, Samollow PB, Hixson JE, Stern MP, MacCluer JW. Genome-wide linkage analysis of blood pressure in Mexican Americans. Genet Epidemiol. 2001; 20: 373–382.[CrossRef][Medline] [Order article via Infotrieve]
24. Cheng LS, Davis RC, Raffel LJ, Xiang AH, Wang N, Quinones M, Wen PZ, Toscano E, Diaz J, Pressman S, Henderson PC, Azen SP, Hsueh WA, Buchanan TA, Rotter JI. Coincident linkage of fasting plasma insulin and blood pressure to chromosome 7q in hypertensive Hispanic families. Circulation. 2001; 104: 1255–1260.
25. Ober C, Abney M, McPeek MS. The genetic dissection of complex traits in a founder population. Am J Hum Genet. 2001; 69: 1068–1079.[CrossRef][Medline] [Order article via Infotrieve]
26. Dubay C, Vincent M, Samani NJ, Hilbert P, Kaiser MA, Beressi JP, Kotelevtsev Y, Beckmann JS, Soubrier F, Sassard J, Lathrop GM. Genetic determinants of diastolic and pulse pressure map to different loci in Lyon hypertensive rats. Nat Genet. 1993; 3: 354–357.[CrossRef][Medline] [Order article via Infotrieve]
27. Atwood LD, Samollow PB, Hixson JE, Stern MP, MacCluer JW. Genome-wide linkage analysis of pulse pressure in Mexican Americans. Hypertension. 2001; 37 (pt 2): 425–428.
28. Williams RR, Hunt SC. Recruitment of members of high-risk Utah pedigrees. Controlled Clin Trials. 1987; 8: 105S–114S.[CrossRef][Medline] [Order article via Infotrieve]
29. Hunt SC, Stephenson SH, Hopkins PN, Williams RR. Predictors of an increased risk of future hypertension in Utah pedigrees: a screening analysis. Hypertension. 1991; 17: 969–976.
30. Hasstedt SJ. PAP: pedigree analysis package, V5. Salt Lake City, Utah: Department of Human Genetics, University of Utah; 2002.
31. O’Connell JR, Weeks DE. PEDCHECK: a program for identification of genotype incompatibilities in linkage analysis. Am J Hum Genet. 1998; 63: 259–266.[CrossRef][Medline] [Order article via Infotrieve]
32. Terwilliger JD, Ott J. Handbook of Genetic Linkage. Baltimore/London: Johns Hopkins University Press; 1994.
33. Ott J. Major strengths and weaknesses of the LOD score method. Adv Genet. 2001; 42: 125–132.[Medline] [Order article via Infotrieve]
34. Dart AM, Kingwell BA. Pulse pressure: a review of mechanisms and clinical relevance. J Am Coll Cardiol. 2001; 37: 975–984.
35. Cushman WC, Materson BJ, Williams DW, Reda DJ. Pulse pressure changes with six classes of antihypertensive agents in a randomized, controlled trial. Hypertension. 2001; 38: 953–957.
36. Hunt SC, Ellison RC, Atwood LD, Pankow JS, Province MA, Leppert MF. Genome scans for blood pressure and hypertension: the National Heart, Lung, and Blood Institute Family Heart Study. Hypertension. 2002; 40: 1–6.
37. Cui JS, Hopper JL, Harrap SB. Antihypertensive treatments obscure familial contributions to blood pressure variation. Hypertension. 2003; 41: 207–210.
38. Jensen CS, Kong A, Kjaerulff U. Blocking-Gibbs sampling in very large probabilistic expert systems. Int J Hum Comput Stud. 1998; 42: 647–666.[CrossRef]
39. Thomas A, Gutin A, Abkevich A, Bansal A. Multilocus linkage analysis by blocked Gibbs sampling. Stat Comput. 2000; 10: 259–269.[CrossRef]
40. Göring HH, Terwilliger JD. Linkage analysis in the presence of errors, I: complex-valued recombination fractions and complex phenotypes. Am J Hum Genet. 2000; 66: 1095–1106.[CrossRef][Medline] [Order article via Infotrieve]
41. Abkevich V, Camp NJ, Gutin A, Farnham JM, Cannon-Albright L, Thomas A. A robust multipoint linkage statistic (TLOD) for mapping complex trait loci. Genet Epidemiol. 2001; 21: 492–497.
42. Risch N, Giuffra L. Model misspecification and multipoint linkage analysis. Hum Hered. 1992; 42: 77–92.[CrossRef][Medline] [Order article via Infotrieve]
43. Pal DK, Durner M, Greenberg DA. Effect of misspecification of gene frequency on the two-point LOD score. Eur J Hum Genet. 2001; 9: 855–859.[CrossRef][Medline] [Order article via Infotrieve]
44. Camp NJ, Farnham JM. Correcting for multiple analyses in genome-wide linkage studies. Ann Hum Genet. 2001; 65 (pt 6): 577–582.[CrossRef][Medline] [Order article via Infotrieve]
45. Lander E, Kruglyak L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet. 1995; 11: 241–247.[CrossRef][Medline] [Order article via Infotrieve]
46. Almasy L, Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 1998; 62: 1198–1211.[CrossRef][Medline] [Order article via Infotrieve]
47. Xu X, Rogus JJ, Terwedow HA, Yang J, Wang Z, Chen C, Niu T, Wang B, Xu H, Weiss S, Schork NJ, Fang Z. An extreme-sib-pair genome scan for genes regulating blood pressure. Am J Hum Genet. 1999; 64: 1694–1701.[CrossRef][Medline] [Order article via Infotrieve]
48. Wu DA, Bu X, Warden CH, Shen DD, Jeng CY, Sheu WH, Fuh MM, Katsuya T, Dzau VJ, Reaven GM, Lusis AJ, Rotter JI, Chen YD. Quantitative trait locus mapping of human blood pressure to a genetic region at or near the lipoprotein lipase gene locus on chromosome 8p22. J Clin Invest. 1996; 97: 2111–2118.[Medline] [Order article via Infotrieve]
49. Allayee H, de Bruin TW, Michelle Dominguez K, Cheng LS, Ipp E, Cantor RM, Krass KL, Keulen ET, Aouizerat BE, Lusis AJ, Rotter JI. Genome scan for blood pressure in Dutch dyslipidemic families reveals linkage to a locus on chromosome 4p. Hypertension. 2001; 38: 773–778.
50. Rankinen T, An P, Rice T, Sun G, Chagnon YC, Gagnon J, Leon AS, Skinner JS, Wilmore JH, Rao DC, Bouchard C. Genomic scan for exercise blood pressure in the Health, Risk Factors, Exercise Training and Genetics (HERITAGE) Family Study. Hypertension. 2001; 38: 30–37.
51. DeStefano AL, Baldwin CT, Burzstyn M, Gavras I, Handy DE, Joost O, Martel T, Nicolaou M, Schwartz F, Streeten DH, Farrer LA, Gavras H. Autosomal dominant orthostatic hypotensive disorder maps to chromosome 18q. Am J Hum Genet. 1998; 63: 1425–1430.[CrossRef][Medline] [Order article via Infotrieve]
52. Nyholt D. All LODs are not created equal. Am J Hum Genet. 2000; 67: 282–288.[CrossRef][Medline] [Order article via Infotrieve]
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S. C. Hunt, Y. Xin, L. L. Wu, R. M. Cawthon, H. Coon, S. J. Hasstedt, and P. N. Hopkins Sodium Bicarbonate Cotransporter Polymorphisms Are Associated With Baseline and 10-Year Follow-Up Blood Pressures Hypertension, March 1, 2006; 47(3): 532 - 536. [Abstract] [Full Text] [PDF]
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S. J. Bielinski, A. I. Lynch, M. B. Miller, A. Weder, R. Cooper, A. Oberman, Y.-D. I. Chen, S. T. Turner, M. Fornage, M. Province, et al. Genome-Wide Linkage Analysis for Loci Affecting Pulse Pressure: The Family Blood Pressure Program Hypertension, December 1, 2005; 46(6): 1286 - 1293. [Abstract] [Full Text] [PDF]
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C. J. Russo, E. Melista, J. Cui, A. L. DeStefano, G. L. Bakris, A. J. Manolis, H. Gavras, and C. T. Baldwin Association of NEDD4L Ubiquitin Ligase With Essential Hypertension Hypertension, September 1, 2005; 46(3): 488 - 491. [Abstract] [Full Text] [PDF]
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 G. F. Mitchell, A. L. DeStefano, M. G. Larson, E. J. Benjamin, M.-H. Chen, R. S. Vasan, J. A. Vita, and D. Levy Heritability and a Genome-Wide Linkage Scan for Arterial Stiffness, Wave Reflection, and Mean Arterial Pressure: The Framingham Heart Study Circulation, July 12, 2005; 112(2): 194 - 199. [Abstract] [Full Text] [PDF]
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 S. J. Zieman, V. Melenovsky, and D. A. Kass Mechanisms, Pathophysiology, and Therapy of Arterial Stiffness Arterioscler Thromb Vasc Biol, May 1, 2005; 25(5): 932 - 943. [Abstract] [Full Text] [PDF]
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A. F. Dominiczak, D. Graham, M. W. McBride, N. J.R. Brain, W. K. Lee, F. J. Charchar, M. Tomaszewski, C. Delles, and C. A. Hamilton Cardiovascular Genomics and Oxidative Stress Hypertension, April 1, 2005; 45(4): 636 - 642. [Abstract] [Full Text] [PDF]
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A. L. DeStefano, M. G. Larson, G. F. Mitchell, E. J. Benjamin, R. S. Vasan, J. Li, D. Corey, and D. Levy Genome-Wide Scan for Pulse Pressure in the National Heart, Lung and Blood Institute's Framingham Heart Study Hypertension, August 1, 2004; 44(2): 152 - 155. [Abstract] [Full Text] [PDF]
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 C. A. Mein, M. J. Caulfield, R. J. Dobson, and P. B. Munroe Genetics of essential hypertension Hum. Mol. Genet., April 1, 2004; 13(90001): R169 - 175. [Abstract] [Full Text] [PDF]
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