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(Circulation. 2000;102:1956.)
© 2000 American Heart Association, Inc.

Clinical Investigation and Reports

Genome-Wide Linkage Analysis of Systolic and Diastolic Blood Pressure

The Québec Family Study

Treva Rice, PhD; Tuomo Rankinen, PhD; Michael A. Province, PhD; Yvon C. Chagnon, PhD; Louis Pérusse, PhD; Ingrid B. Borecki, PhD; Claude Bouchard, PhD; D. C. Rao, PhD

From the Division of Biostatistics (T. Rice, M.A.P., I.B.B., D.C.R.) and Departments of Genetics (I.B.B., D.C.R.) and Psychiatry (D.C.R.), Washington University School of Medicine, St Louis, Mo; Physical Activity Sciences Laboratory, Laval University, Québec, Canada (Y.C.C., L.P.); and Pennington Biomedical Research Center, Baton Rouge, La (T. Rankinen, C.B.).

Correspondence to Treva Rice, PhD, Division of Biostatistics, Washington University School of Medicine, Box 8067, 660 S Euclid Ave, St Louis, MO 63110. E-mail treva{at}wubios.wustl.edu

	Abstract

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Background—Blood pressure (BP), an important risk factor for coronary heart disease, is a complex trait with multiple genetic etiologies. While some loci affecting BP variation are known (eg, angiotensinogen), there are likely to be novel signals that can be detected with a genome scan approach.

Methods and Results—A genome-wide scan was performed in 125 random and 81 obese families participating in the Québec Family Study. A multipoint variance-components linkage analysis of 420 markers (353 microsatellites and 67 restriction fragment length polymorphisms) revealed several signals (P<0.0023) for systolic BP on 1p (D1S551, ATP1A1), 2p (D2S1790, D2S2972), 5p (D5S1986), 7q (D7S530), 8q (CRH), and 19p (D19S247). Suggestive evidence (0.0023<P<0.01) was found on 3q, 10p, 12p, 14q, and 22q. The results were encouraging for HSD3B1 (P<0.03), AGT (P<0.03), ACE (P<0.02), and adipsin (P<0.005) but null with regard to other candidates (eg, renin, and glucocorticoid and adrenergic receptors).

Conclusions—Multiple linkage regions support the notion that risk for hypertension is due to multiple (ie, oligogenic) susceptibility loci. Comparisons across the complete, random, and obese samples suggest that some regions are specific to BP and others may involve obesity (eg, pleiotropy, epistasis, or gene-environment interaction). Some of these areas harbor known candidates. Others involve novel regions, some of which replicate previous reports and provide a focus for future studies to identify novel genes that influence interindividual variation in BP.

Key Words: hypertension • blood pressure • genetics • coronary disease

	Introduction

Top Abstract Introduction Methods Results Discussion References

 
Blood pressure (BP) is an important risk factor for coronary heart disease¹ and is a complex trait that is heritable, with polygenic and/or familial environmental factors accounting for 30% to 70% of the trait variance.^{2 3 4 5} Although there are a few examples of single-gene defects leading to hypertension,⁶ the etiology for the majority of cases may involve multiple quantitative trait loci (QTLs) that confer susceptibility to hypertension and may interact with other genes and/or environmental conditions affecting the underlying physiological mechanisms (ie, oligogenic or multigenic).

Most previous BP explorations were limited to candidate gene approaches^{1 6 7} that can confirm the effects of known genes. However, it is likely that there remain additional unknown QTL regions that can be detected with genome-wide scan approaches. Only two such studies^{8 9} have been reported. In the current study, we use multipoint variance-components linkage methods to conduct a genome-wide linkage analysis in random and obese families of the Québec Family Study.

	Methods

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The Québec Family Study (see Reference ¹⁰ for details) phase 2 data consist of 180 complex families. Approximately half of these are considered a random sample because they were not selected for BP or obesity levels. For the remaining families (obese sample), 1 or more members were required to have a body mass index (BMI) 32 kg/m². After complex families were reorganized as simple nuclear units (ie, parents and offspring) and subjects taking antihypertensive medication were excluded, a total of 679 individuals (445 random and 234 obese) from 206 families (125 random and 81 obese) with complete phenotypic data at phase 2 remained.

BP was measured early in the morning in a 2-hour fasted state with a mercury sphygmomanometer and stethoscope (American Heart Association recommendations¹¹ ). A first reading was taken after a 10-minute rest, followed by additional readings at 2-minute delays. The mean of 2 consecutive measurements that were <10 mm Hg apart on both BPs was used; <1% of subjects required >2 readings to meet the criteria. BP was determined at the point when the Korotkoff sounds became audible (systolic BP, SBP) and when they ceased (diastolic BP, DBP). A test-retest study on 61 subjects yielded intraclass reliability coefficients of 0.93 and 0.91 for SBP and DBP, respectively.¹² BMI was measured as weight (kg)/height (m²).

BP measures were adjusted for the effects of sex, generation, and age by means of stepwise multiple regression.¹³ In summary, a BP phenotype was regressed on up to a 3rd degree polynomial in age (separately within age and sex groups). Only significant terms (5% level) were retained (ie, the model did not need to be saturated). The residual from this regression (or the raw score if no age terms were significant) was then standardized to zero mean and unit variance and constituted the analysis variable (SBP1 and DBP1). Similarly, a second set of BP variables was constructed by removing the effects of BMI and the polynomial in age (SBP2 and DBP2).

Polymerase chain reaction conditions and genotyping methods are fully outlined in a report by Chagnon et al.¹⁴ Automatic DNA sequencers from LICOR were used to detect the polymerase chain reaction products, and genotypes were scored automatically with the software SAGA. Incompatibilities of Mendelian inheritance were checked, and markers showing incompatibilities were regenotyped completely (<10% were retyped). Microsatellite markers were selected mainly from the Marshfield panel version 8a, as were some candidate genes for obesity and comorbidities. Map locations (Kosambi distance in centimorgans, cM) were taken mainly from the Location Data Base of Southampton, UK (http://cedar.genetics. soton.ac.uk) and other sources for a few markers (published papers and the Marshfield Institute map [http://www.marshmed.org/genetics]).

Linkage analysis was performed with a multipoint variance components model in SEGPATH.^{15 16} Under this model, a phenotype is influenced by the additive effects of a trait locus (g), a residual familial background modeled as a pseudopolygenic component (G_R), and a residual nonfamilial component (r). The effects of the trait locus and the pseudopolygenic component on the phenotype represent the heritabilities h²_g and h²_r, respectively. Allele sharing probabilities (at each marker location for each sibpair) were used as input data for the linkage component of the SEGPATH model. These multipoint probabilities were derived with the use of the program MAPMAKER/SIBS.¹⁷ Other parameters in the model include spouse (u) and additional sibling (b) resemblance and the mean and variance in the offspring.

The linkage hypothesis is tested by restricting the trait locus heritability to be zero. A likelihood ratio test contrasts the null hypothesis (h²_g=0) with the alternative (h²_g estimated). The difference in -2 ln L (minus twice the log likelihood) between the null and alternate hypotheses is asymptotically distributed as a 50:50 mixture of a ₁² and a point mass at zero, and the probability value is one-half of that associated with the ² value.¹⁸ The logarithm of odds (lod) score is (²/[2 · log_e10]). The -level judging the significance of the lod score (P<0.0023) represents one false-positive per scan for experiments involving 400 markers.¹⁹ Analyses were conducted separately for each of the random, obese, and combined subsamples.

	Results

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A total of 420 markers (353 microsatellite and 67 restriction fragment length polymorphisms, RFLPs) were used. The mean heterozygosity was 0.75 (range 0.32 to 0.94) and the average spacing between markers was 7.95 cM (1 interval was 25 cM and 5 were between 20 to 22 cM, with all others <20 cM). The overall length of the genetic map was 3063 cM. Family structure information is given in Table 1.

View this table: [in this window] [in a new window]   Table 1. Family Structures

Means and standard deviations for age, BMI, SBP, and DBP are given in Table 2, separately by sample, sex, and generation groups. Mean group differences were compared by means of standard errors (ie, means are significantly different if the difference is greater than twice the standard error). The mean BMI is higher in the obese as compared with the random sample, as expected. There are sample differences for age in mothers and sons, and mean BP is higher in obese daughters. Some generation and sex differences were also noted.

View this table: [in this window] [in a new window]   Table 2. Sample Sizes1 and Statistics

For covariate adjustments (SBP1 and DBP1), age was a significant predictor for SBP in middle-aged men (age accounted for 10.7% of the variance) and women (age²=12.8%) and older men (age³=18.7%) and women (age=36.6%). Age was significant for DBP only in middle-aged men (age=15.0%) and women (age³=11.8%). Age was not significant in the remaining groups for either BP. For SBP2, the combined effects of age and BMI accounted for 12.7%, 26.4%, and 27.9% of the variance in younger, middle-aged, and older men, respectively, and 10.5%, 29.8%, and 38.6% in women, respectively. Similarly, for DBP2 the combined effects accounted for 7.5%, 30.8%, and 8.6% of the variance in men, respectively, and 12.7%, 24.2%, and 0% in women, respectively,

Complete linkage results are available at http://www.circulationaha.org in tabular form. A summary of lod scores >1.0 and associated probability values is given in Table 3. There are regions on chromosomes 1 and 2 (Figure 1), 5 and 7 (Figure 2), and 8 and 19 (Figure 3) yielding good (P<0.0023) to suggestive (0.0023<P<0.01) linkage. With few exceptions, linkages are confined to SBP, adjustment for BMI has the greatest effect on the evidence at markers D1S551 and D19S247, and results are stronger in the combined sample.

View this table: [in this window] [in a new window]   Table 3. Summary of lod Scores >1

View this table: [in this window] [in a new window]   Table 3A. Continued

View larger version (42K): [in this window] [in a new window]   Figure 1. Detailed lod score plot for promising linkage regions on chromosomes 1 and 2 for complete (upper), random (middle), and obese (lower) samples. Marker definitions: LEPR indicates leptin receptor (5 polymorphisms, CTTT form shown); ATP1A1, ATPase-1; HSD3B1, 3ß-hydroxy-delta 5-steroid dehydrogenase; ATP1B1 and ATP1A2, ATPase-ß1 and -2; AT3, antithrombin 3; REN, renin; AGT, angiotensinogen (2 polymorphisms, including M235T); APOB, apolipoprotein B; and IRS1, insulin receptor substrate 1.

View larger version (40K): [in this window] [in a new window]   Figure 2. Detailed lod score plot for promising linkage regions on chromosomes 5 and 7 for complete (upper), random (middle), and obese (lower) samples. See Figure 1 for further details. Marker definitions: GRL indicates glucocorticoid receptor; ADRB4, adrenergic ß2 receptor; NPY, neuropeptide Y; IGFBP3 and IBFBP1, insulin-like growth factor–binding proteins 3 and 1; CD3, thrombospondin receptor (antigen); LEP, leptin, murine obesity homologue; EPO, erythropoietin; and NOS3, nitric oxide synthase 3.

View larger version (34K): [in this window] [in a new window]   Figure 3. Detailed lod score plot for promising linkage regions on chromosomes 8 and 19 for complete (upper), random (middle), and obese (lower) samples. Marker definitions: LPL indicates lipoprotein lipase; ADRB3, adrenergic ß3 receptor; CRH, corticotropin-releasing hormone; INSR, insulin receptor; LDLR, LDL receptor; EPOR, erythropoietin receptor; LIPE, hormone-sensitive lipase; APOE, apolipoprotein E; and GYS1, glycogen synthase.

	Discussion

Top Abstract Introduction Methods Results Discussion References

 
The primary purpose of the current study was to conduct a genome scan for QTLs affecting BP variation. Although a few hypertension candidate genes were included in this panel of >400 markers spanning the genome, this was not intended as a candidate gene study. Rather, this was considered an experimental design for detecting multiple and perhaps novel genomic regions affecting BP variation. Because the effects of novel QTLs for BP are likely to be low to moderate, more liberal criteria (P<0.0023) than that suggested by Lander and Kruglyak²⁰ were adopted, as recommended by Rao and Province.¹⁹ Factors affecting this power include realistically sized samples and modest to moderate effect sizes. Although these liberal criteria maximize the detection of genes, an increased reliance on replication is needed to confirm "true" signals. Following these recommendations,¹⁹ the current study yields several results of interest on chromosomes 1, 2, 5, 7, 8, and 19, with the strongest evidence on 2p, 5p, and 7q involving replication and/or probability value <0.001.

On chromosome 1p22.3-p13.1, good evidence was obtained for 3 markers (LEPR, D1S551, and ATP1A1). Comparisons across samples and adjustment schemes (Figure 1) suggest two peaks, one near D1S551 (1p22.3-p22.1) and another near ATP1A1 (1p13.1). The D1S551 peak is higher before BMI adjustment and is detected in the combined and obese samples. The ATP1A1 peak is not affected by the adjustment and is stronger in the complete and random samples. This pattern suggests that there could be (1) two QTLs for BP in this region, one mediated by body size (D1S551) and the other primarily for BP (ATP1A1); or (2) a single QTL that is localized slightly differently between samples. That is, localization can vary simply as a function of the informativeness of the phenotype and marker. Investigating this region with a denser marker map should help resolve this issue. ATP1A1 is a hypertension candidate in salt-sensitive Dahl rats.²¹ Another candidate in the region, HSD3B1 (0.028<P<0.034), is a key enzyme in the steroid biosynthetic pathway, and other enzymes in this path (CYP11B1 and CYP11B2 on 8q) may be responsible for inherited forms of hypertension and hypotension, including glucocorticoid-suppressible hyperaldosteronism.⁶ CYP11B1 (not typed) is <6 cM downstream from the CRH locus (8q21.11, P<0.001) (Figure 3). Whether the 8q result is specific to CYP or to peripheral hemodynamic effects of corticotropin-releasing hormones²² may be resolved with a denser map. A suggestive area on 1q (D1S3462, P<0.01) is located within the AGT locus (3' region), which also had nominal probability values (0.026 to 0.049).

A 20-cM region of 2p11.1-q12.3 (D2S1790, D2S2972, and D2S121) in the combined and random samples produced good results for SBP (Figure 1), and promising results (0.01<P<0.02) were seen 14 to 54 cM upstream at D2S405, D2S441, and D2S2114 (2p22.1-2p12) for DBP. D2S1790 was reportedly linked to SBP in a genome-wide scan of Mexican American families (L. Atwood, personal communication), and D2S441 replicates a report in the GENOA network.⁸ Slightly larger lod scores are obtained for D2S1790 and D2S2972 after BMI adjustment in the combined sample, whereas the differences are less noticeable in the random sample. This pattern suggests that the effect of a QTL in this region may be moderated by obesity. Given that there are no known candidates in this region and that there is replication across studies, this area warrants further investigation with more dense mapping techniques.

There was linkage evidence for chromosome 7 markers D7S530 and D7S2195 (7q-32.1 to 7q36.1) in both the random and complete samples (Figure 2). BMI adjustment did not affect the results. In further support of a QTL in this region, a marker not typed in the current study (D7S1804) but <5 cM from D7S530 was reported in Mexican American families (L. Atwood, personal communication). Moreover, D7S2195 was linked to BP in Chinese sibships.⁹ Since there are no strong candidates in this region, and given the support across studies, this area warrants further investigation.

A relatively strong result in the complete and random samples is on 5p15.2-p12 (D5S807, D5S2845, D5S1986, and D5S1470), with a peak lod score (2.80) at D5S1986 (Figure 2). This signal may be independent of obesity because BMI adjustment did not affect results. Linkage was also noted on chromosome 19p13.3 (D19S247) in the complete sample (Figure 3). Less than 2 cM upstream, the results for the adipsin locus were suggestive. The signal is reduced after adjusting for BMI, suggesting that obesity may play a role in the QTL effect on BP. No candidates were typed in these regions, and no replications with other studies were found.

Several other suggestive or promising results for SBP (see Table 3) were on chromosomes 3q13.31-3q26.32 (D3S3045 and D3S2427), 10p14 (D10S2325), 12p13.33 (D12S372), and 14q11.2-14q12 (D14S283 and D14S1280) and for DBP on 22q13.1-22q13.2 (D22S685, D22S445, and D22S274). These regions were not replicated in previous genome scans. Typed RFLPs that were not suggestive (in addition, those in Figures 1 to 3) include FABP3 (1p), FABP2 (4q), ADRA2A (10q), IGF2 (11p), GNB3 (12p), IGF1 (12q), and IGF1R (15q). Although no suggestive results were obtained on chromosome 17, the probability values were nominal (0.02>P>0.01) in the region of 17q21.33-17q21.2 (D17S1301 and ACE, <10 cM apart). The NOS2 loci (not typed) are upstream of D17S1301 and were reported to cosegregate with BP in Dahl salt-sensitive rats.²³ Moreover, the human homologue of the hereditary hypertensive rat at D17S934 and near the ACE locus was significantly linked with hypertension in humans.^{24 25} The current study supports these reports for 17q but suggests the magnitude of the effect in this sample may be quite small.

In summary, there is good linkage evidence for several markers. Although there are no strong candidates in two of these regions (2p and 7q), support across studies lends credibility to these findings and indicates that further investigation is needed to identify possible new QTLs. In addition to these novel genomic regions, results for some known candidates were supportive, including ACE (17q), adipsin (19p), AGT (1q), ATP1A1 and HSD3B1 (1p), and CRH (8q). Moreover, the study design allowed for inferences to be drawn regarding the QTL interactions with obesity on BP. For example, the effect of some of these QTLs may be primarily on BP and independent of obesity (1p [ATP1A1], 7q, 5p), whereas the effect of others (1p [D1S3462], 2p, 19p) may be mediated by obesity (eg, pleiotropy, epistasis, or gene-environment interaction). These results support the hypothesis that multiple QTLs influence BP variation, and further study involving dense mapping is indicated in two novel regions on 2p and 7q.

	Acknowledgments

 
This work was partly supported by National Institutes of Health grants GM-28719 and HD-18281 and MRC of Canada grants GR-15187 and MT-13960. C. Bouchard is partly supported by the George A. Bray Chair in Nutrition.

Received April 13, 2000; revision received May 30, 2000; accepted May 30, 2000.

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				S. Charron, C. Duong, A. Menard, J. Roy, V. Eliopoulos, R. Lambert, and A. Y. Deng Epistasis, Not Numbers, Regulates Functions of Clustered Dahl Rat Quantitative Trait Loci Applicable to Human Hypertension Hypertension, December 1, 2005; 46(6): 1300 - 1308. [Abstract] [Full Text] [PDF]

				X. Bao, P. J. Mills, B. K. Rana, J. E. Dimsdale, N. J. Schork, D. W. Smith, F. Rao, M. Milic, D. T. O'Connor, and M. G. Ziegler Interactive Effects of Common {beta}2-Adrenoceptor Haplotypes and Age on Susceptibility to Hypertension and Receptor Function Hypertension, August 1, 2005; 46(2): 301 - 307. [Abstract] [Full Text] [PDF]

				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]

				W. Chen, S. Li, S. R Srinivasan, E. Boerwinkle, and G. S. Berenson Autosomal Genome Scan for Loci Linked to Blood Pressure Levels and Trends Since Childhood: The Bogalusa Heart Study Hypertension, May 1, 2005; 45(5): 954 - 959. [Abstract] [Full Text] [PDF]

				P. Meneton, X. Jeunemaitre, H. E. de Wardener, and G. A. Macgregor Links Between Dietary Salt Intake, Renal Salt Handling, Blood Pressure, and Cardiovascular Diseases Physiol Rev, April 1, 2005; 85(2): 679 - 715. [Abstract] [Full Text] [PDF]

				P. Duggal, A. P. Klein, K. E. Lee, S. K. Iyengar, R. Klein, J. E. Bailey-Wilson, and B. E. K. Klein A Genetic Contribution to Intraocular Pressure: The Beaver Dam Eye Study Invest. Ophthalmol. Vis. Sci., February 1, 2005; 46(2): 555 - 560. [Abstract] [Full Text] [PDF]

				M. de Lange, T. D. Spector, and T. Andrew Genome-Wide Scan for Blood Pressure Suggests Linkage to Chromosome 11, and Replication of Loci on 16, 17, and 22 Hypertension, December 1, 2004; 44(6): 872 - 877. [Abstract] [Full Text] [PDF]

				L. Koivukoski, S. A. Fisher, T. Kanninen, C. M. Lewis, F. von Wowern, S. Hunt, S. L.R. Kardia, D. Levy, M. Perola, T. Rankinen, et al. Meta-analysis of genome-wide scans for hypertension and blood pressure in Caucasians shows evidence of susceptibility regions on chromosomes 2 and 3 Hum. Mol. Genet., October 1, 2004; 13(19): 2325 - 2332. [Abstract] [Full Text] [PDF]

				S.-J. Wu, F.-T. Chiang, W. J. Chen, P.-H. Liu, K.-L. Hsu, J.-J. Hwang, L.-P. Lai, J.-L. Lin, C.-D. Tseng, and Y.-Z. Tseng Three single-nucleotide polymorphisms of the angiotensinogen gene and susceptibility to hypertension: single locus genotype vs. haplotype analysis Physiol Genomics, April 13, 2004; 17(2): 79 - 86. [Abstract] [Full Text] [PDF]

				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]

				F. von Wowern, K. Bengtsson, U. Lindblad, L. Rastam, and O. Melander Functional Variant in the {alpha}2B Adrenoceptor Gene, a Positional Candidate on Chromosome 2, Associates With Hypertension Hypertension, March 1, 2004; 43(3): 592 - 597. [Abstract] [Full Text] [PDF]

				R. A. Barkley, A. Chakravarti, R. S. Cooper, R. C. Ellison, S. C. Hunt, M. A. Province, S. T. Turner, A. B. Weder, E. Boerwinkle, and on behalf of the Family Blood Pressure Program Positional Identification of Hypertension Susceptibility Genes on Chromosome 2 Hypertension, February 1, 2004; 43(2): 477 - 482. [Abstract] [Full Text] [PDF]

				R. J. F. Loos, P. T. Katzmarzyk, D. C. Rao, T. Rice, A. S. Leon, J. S. Skinner, J. H. Wilmore, T. Rankinen, and C. Bouchard Genome-Wide Linkage Scan for the Metabolic Syndrome in the HERITAGE Family Study J. Clin. Endocrinol. Metab., December 1, 2003; 88(12): 5935 - 5943. [Abstract] [Full Text] [PDF]

				N. J. Camp, P. N. Hopkins, S. J. Hasstedt, H. Coon, A. Malhotra, R. M. Cawthon, and S. C. Hunt Genome-Wide Multipoint Parametric Linkage Analysis of Pulse Pressure in Large, Extended Utah Pedigrees Hypertension, September 1, 2003; 42(3): 322 - 328. [Abstract] [Full Text] [PDF]

				F. von Wowern, K. Bengtsson, C. M. Lindgren, M. Orho-Melander, F. Fyhrquist, U. Lindblad, L. Rastam, C. Forsblom, T. Kanninen, P. Almgren, et al. A genome wide scan for early onset primary hypertension in Scandinavians Hum. Mol. Genet., August 15, 2003; 12(16): 2077 - 2081. [Abstract] [Full Text] [PDF]

				M. Gong, H. Zhang, H. Schulz, Y.-A. Lee, K. Sun, S. Bahring, F. C. Luft, P. Nurnberg, A. Reis, K. Rohde, et al. Genome-wide linkage reveals a locus for human essential (primary) hypertension on chromosome 12p Hum. Mol. Genet., June 1, 2003; 12(11): 1273 - 1277. [Abstract] [Full Text] [PDF]