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(Hypertension. 2004;44:695.)
© 2004 American Heart Association, Inc.

Scientific Contributions

Mapping the Genetic Determinants of Hypertension, Metabolic Diseases, and Related Phenotypes in the Lyon Hypertensive Rat

Marijo Bilusic; Alain Bataillard; Michael R. Tschannen; Li Gao; Nadia E. Barreto; Madeleine Vincent; Tao Wang; Howard J. Jacob; Jean Sassard; Anne E. Kwitek

From the Department of Physiology (M.B., M.R.T., L.G., N.E.B., H.J.J., A.E.K.), the Human and Molecular Genetics Center (M.B., M.R.T., L.G., N.E.B., T.W., H.J.J., A.E.K.), and the Division of Biostatistics (T.W.), Medical College of Wisconsin, Milwaukee, and the Faculte de Pharmacie-Université Lyon 1 (A.B., M.V., J.S.), Lyon, France.

Correspondence to Anne E Kwitek, PhD, HMGC/Department of Physiology, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI 53226. E-mail akwitek{at}mcw.edu

	Abstract

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The complex nature of hypertension makes identifying the pathophysiology and its genetic contributions a challenging task. One powerful approach for the genetic dissection of blood pressure regulation is studying inbred rat models of hypertension, as they provide natural allele variants but reduced heterogeneity (both genetic and etiologic). Furthermore, the detailed physiologic studies to which the rat is amenable allow for the determination of intermediate phenotypes. We have performed a total genome scan in offspring of an F₂ intercross between the Lyon hypertensive (LH) and Lyon normotensive rat strains to identify linkage of anthropometric, blood pressure, renal, metabolic, and endocrine phenotypes. Quantitative trait locus (QTL) regions involved in blood pressure regulation, end-stage organ damage, body and organ weight, and lipid metabolism in the LH rat were identified on chromosomes 1, 2, 3, 5, 7, 10, 13, and 17, with 2 phenotypes associated with the metabolic syndrome identified on chromosomes 1 and 17. Regions on chromosomes 2, 13, and 17 were revealed to be important for blood pressure regulation. Regions on chromosome 17 were found to significantly contribute to both metabolic homeostasis and blood pressure regulation; 2 aggregates of a total of 23 QTLs were identified, including several "intermediate phenotypes." These intermediate phenotypes may be used as closer surrogates to the mechanisms leading to hypertension and metabolic dysfunction in the LH rat.

Key Words: genetics • linkage analysis • metabolism • hypertension, genetic • rats, inbred strains • cardiovascular diseases

	Introduction

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Human essential hypertension and associated cardiovascular diseases are multifactorial disorders with a complex etiology, resulting from the interaction between multiple genes and environmental factors. Despite development of new genetic and genomic technologies, the genetic determinants of multifactorial disorders remain unclear. The study of animal models in discovering pathophysologic and genetic determinants of polygenetic disorders such as hypertension provides a platform of reduced heterogeneity. Currently, there exist several different genetically hypertensive rat and mouse selection models.¹ Numerous linkage studies in rats have shown that each rat chromosome contains at least 1 blood pressure (BP) quantitative trait locus (QTL; http://rgd.mcw.edu/qtls).

The Lyon hypertensive (LH) rat has many features common to the human metabolic syndrome, a group of metabolic risk factors including central obesity, atherogenic dyslipidemia, elevated BP, insulin resistance or glucose intolerance, and prothrombotic and proinflamatory states.² Interestingly, a control strain, the Lyon normotensive (LN) rat, has been simultaneously derived from a common ancestor of the LH; the LN is genetically quite similar to the LH (85% identical based on characterization of 4328 microsatellite markers; data not shown) but phenotypically very distinct. Compared with the LN, LH rats have mild salt-sensitive hypertension and reduced life span; significantly increased body and heart weight; increased levels of cholesterol, phospholipids, and triglycerides; increased insulin-glucose ratio (albeit without true insulin resistance); and significantly decreased levels of plasma and kidney renin and prorenin concentrations, serum aldosterone concentration, and serum Ca²⁺.^3,4 An initial linkage study in an F₂ intercross between the LH and LN was previously published by Dubay et al,⁵ reporting multiple independent genetic determinants involved in the regulation of BP (systolic, diastolic, and pulse pressure). Significant linkage was determined between diastolic BP and a marker associated with the renin (Ren) gene on chromosome 13 and between pulse pressure and the carboxypeptidase B (Cbp1) gene (D2Wox15) on chromosome 2. In a second study, Vincent et al⁴ determined that hypertension in the LH rat is a recessive trait, independent of body weight, and is associated with some metabolic disorders (particularly cosegregation with increased cholesterol and, to a lesser degree, with insulin levels).

Since those studies were performed, many new genetic markers have been developed as well as whole-genome genetic, RH, and sequence maps of the laboratory rat.^6–8 Additionally, other authors^9,10 reported overlapping BP QTL regions (particularly on rat chromosomes 2 and 13) in different F₂ intercrosses. This prompted us to extend the genetic linkage study in the offspring from the same F₂ intercross previously studied, including several additional phenotypic measurements.^4,5 In the current study, a genome-wide linkage analysis was performed for anthropometric, BP, renal, metabolic, and endocrine phenotypes measured in F₂ male rats to elucidate the genetic factors underlying not only BP regulation but also end-organ damage and metabolic impairment. In addition, we evaluated correlations between overlapping QTLs to identify intermediate phenotypes that could be used as better surrogates of BP.

	Methods

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Animals and Phenotyping Protocol
All animals were derived and housed as previously described, and protocols were performed according to institutional guidelines.^4,5 Direct BP measurement was performed on 327 conscious, nonrestrained male rats at 29 to 31 weeks of age with our computerized technique.⁵ The day after BP recording, the rats were killed by decapitation between 8 AM and noon. The right tibia was dissected, and its length was measured as an index of body length. Blood was collected in sodium-EDTA (1.6 mg/mL blood) for lipid determination and in heparin (20 U/mL blood) for insulin and glucose determination as described.⁴

Genotyping Protocol
Genomic DNA was extracted from the spleen by standard methods.⁷ The samples were collected in Lyon, France, and sent to the Medical College of Wisconsin, Milwaukee, for genotyping. The rats were genotyped by using radioactively labeled primers as previously described.⁷

Mapping and Statistical Analysis
Initially, we performed a total genome scan with genotypes of 187 simple sequence length polymorphisms corresponding to 1 marker every 8 centimorgans (cM) in the 92 most phenotypically divergent and informative F₂ animals, targeting 14 phenotypes that represent each phenotype group.¹¹ Linkage analysis and QTL identification were performed with MapMaker/EXP and MapMaker/QTL, respectively.^12,13 Before the linkage analysis, all markers were tested for conformity with Hardy-Weinberg equilibrium. Furthermore, the distributions of the phenotypes were tested for normality with a Kolmogorov-Smirnov test. Traits failing to meet the requirements of normality were transformed by either square root or logarithmic transformation and retested for normality. Phenotypes with a normal distribution were subject to parametric linkage analysis. Traits that were not normally distributed were subjected to nonparametric linkage analysis on original nontransformed data.¹⁴ For the parametric linkage test, suggestive and significant log of the odds (LOD) thresholds of 2.8 and 4.3 were accepted, respectively. For the nonparametric analysis, a threshold of significance was determined at a z score 3.5.¹⁵ In a previous study from our laboratory that reported on a similar-size F₂ population and 3 times the number of measured phenotypes, permutation testing found that these thresholds are appropriate.¹⁶ After a preliminary analysis had identified suggestive QTL, we genotyped all 327 animals in the QTL regions at a higher resolution (5 to 7 cM). We chose additional markers from existing reference maps (genetic and radiation hybrid maps) publicly available from the Rat Genome Database (http://rgd.mcw.edu). MapMaker was again used to confirm and better define the QTL intervals.

Phenotypes passing the initial normality testing may still not be normally distributed, given a specific QTL genotype as previous linkage analysis assumed. Therefore, in addition to the genetic linkage study stated earlier, nonparametric (Kruskal-Wallis) tests were also applied for markers on chromosome 17 to determine whether the marker genotypes were associated with BP phenotypes (with the use of SAS; SAS Institute). This nonparametric marker analysis may further reduce the false-positive error. Multiple marker analysis was additionally implemented for markers within each identified QTL on chromosome 17 to distinguish markers with significant partial contribution to a targeted phenotype conditional on the other markers within the region.¹⁷ Correlation coefficients between the traits were determined by Pearson’s correlation or Spearman rank-order correlation (SigmaStat version 2.03, SPSS Inc).

	Results

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The combined results of the parametric and nonparametric linkage analyses are summarized in Table 1 and Figure I (available online at www.hypertensionaha.org). The genome was calculated to be 1420.2 cM long, and marker coverage through the genome in our study averaged 7.9 cM. The calculated size of the genome is consistent with previous estimates and a published map (1509 cM; Jacob et al¹⁸), albeit somewhat shorter. This discrepancy in length is likely because of the high amount of genetic similarity between LH and LN rats, leading to a paucity of polymorphic markers, particularly at the ends of some chromosomes (eg, 6 and 20). Of the 71 phenotypes measured in the F₂ population, 42 traits were normally distributed, either before or after transformation, and were analyzed parametrically. The parametric linkage analysis identified 41 QTLs for 22 phenotypes; of these 41 QTLs, 19 had an LOD score 4.3 (significant linkage), and 22 QTLs had LOD scores 2.8 (suggestive linkage) based on Lander and Kruglyak criteria.^12,14 The remaining 29 traits were analyzed nonparametrically by MapMaker/QTL; an additional 20 QTLs for 13 traits were identified with a z score 3.5. A complete list of all QTLs in our study is presented in Table 1. Overall, a total of 61 QTLs were mapped to 8 different chromosomes (1, 2, 3, 5, 7, 10, 13, and 17), with QTL clusters on chromosomes 1 and 17 having 6 or more phenotypes mapped to the same genetic region.

View this table: [in this window] [in a new window]   TABLE 1. Mapped QTLs, Separated by Phenotype Group

To simplify presentation of our results, we classified our phenotypes into 3 major groups by function (Table 1 and Figure I, available online at http://www.hypertensionaha.org): group 1, body weight, body size, and organ weight (body weight before and after surgery, kidney and heart weights, adjusted organ weights, tibia length); group 2, BP (systolic, diastolic, mean, and pulse pressure); and group 3, blood biochemistry and hormones (cholesterol, triglycerides, phospholipids, insulin, insulin-glucose ratio, corticosterone, and creatinine).

Interestingly, almost all traits from group 1 (14 of 15) mapped to chromosome 1, within a common interval spanning 40 cM (Figure 1). The overlapping 1-LOD-unit support intervals (95% confidence interval [CI]) for this cluster lies between markers D1Rat140 and D1Rat188, with D1Rat278 as the peak marker. Most of the traits from group 1 that mapped within this cluster are highly correlated; only creatinine, corticosterone, and pulse pressure appear to be independent (data not shown).

View larger version (35K): [in this window] [in a new window]   Physical map of chromosome (Chr) 17 with all mapped QTLs. From left to right, Physical map of chromosome 17 with markers and distances in megabases (Mb). Bars denote 95% CIs for the QTL positions on the genetic map. A QTL was considered "mapped" when its LOD score was 2.8 in parametric analysis (solid line) or when its z score was 3.5 in nonparametric analysis (dashed line). Horizontal lines represent QTL peaks. Numbers in parenthesis represent LOD scores. Cluster 1 included traits from group 1; cluster 2 included traits from groups 2 and 3. For definitions of each phenotype, see Table 1. (QTL number is the same as in Table 1). *Significant QTL (LOD score >4.3). BW indicates body weight; RKW, right kidney weight; LKW, left kidney weight; Tib, tibia; LVW, left ventricular weight; SBP, systolic blood pressure; DBP, diastolic blood pressure; Cr, creatinine; PP, pulse pressure; Ch, cholesterol; HDL, high density lipoprotein; VLDL, very low density lipoprotein; Tr, triglycerides; Ph, phospholipids; Ins, insulin; IG, insulin/glycemia ratio. All other abbreviations are as defined in text.

Surprisingly, chromosome 17 harbors loci contributing to the majority of phenotypes in our study (24 of a total of 36 mapped, 66.6%), which make this chromosome extremely important in the LH rat. We found 2 major clusters of QTLs on chromosome 17. The first cluster contains QTLs from group 1 (very similar to the aggregation on chromosome 1), spanning 35 cM between D17Rat2 and D17Mit1 with the peak marker D17Rat94. The second cluster contains QTLs from groups 2 and 3, partially overlaps with the first 1, and spans the interval from D17Rat94 to D17Rat151, with D17Rat98 and D17Rat32 as peak markers. The second cluster harbors multiple QTLs for BP, blood biochemistry, and hormone levels (groups 2 and 3) and has a genetic interval spanning 40 cM, which makes this area particularly important in the dissection of features of the metabolic syndrome in the LH rat.

In addition to MapMaker linkage analysis, nonparametric (Kruskal-Wallis) tests were performed on markers on chromosome 17 to determine whether the marker genotypes were associated with BP phenotypes. The nonparametric tests are valid even when a phenotype is not normally distributed according to the 3 marker genotypes at a marker locus. Therefore, it may provide more robust results than MapMaker analysis. Similarly significant associations were detected at markers D17Rat94, D17Rat102, D17Rat17, D17Rat98, D17Mit12, D17Rat32, and D17Rat58, at a significance level of P<0.0001 in the nonparametric test. A multiple marker analysis was also implemented on chromosome 17 to detect markers that contribute more variation than the others. Two markers, D17Rat17 and D17Rat151, showed significance, whereas results for D17Rat98 and D17Rat32 were not completely clear owing to strong colinearity. Correlation analyses for traits on chromosome 17 (Figure II, available online) confirmed previously reported analyses that multiple QTLs/genes affect trait variability in the LH rat.⁴ For instance, at D17Rat94, the peak marker in the first QTL cluster on chromosome 17, there is a significant correlation in LH rats between body weight and both kidney and heart weight (P<0.0001). However, we did not find a strong correlation between body weight and either BP or metabolic traits. Interestingly, at the peak marker for the second QTL cluster (D17Rat32), we found a strong correlation between mean arterial pressure and total cholesterol, HDL cholesterol, LDL cholesterol, and total phospholipids (P=0.01 to <0.0001), making them intermediate phenotypes in LH rats according to criteria presented by Jacob and Kwitek.¹⁹ Despite overall correlation between cardiac hypertrophy and BP, we did not find a significant correlation between BP and cardiac hypertrophy at the peak marker for the BP QTL (D17Rat32), suggesting that in LH rats, different loci influence BP regulation and ventricular hypertrophy.

	Discussion

Top Abstract Introduction Methods Results Discussion References

 
This study presents a genetic map of QTLs involving hypertension, organ hypertrophy, and metabolic function in the LH rat strain. More genetic markers have been used to increase the power of QTL detection and improve the accuracy of mapping. We have identified 3 major chromosomes (2, 13, and 17) that are important for BP regulation in the LH strain and a cluster of anthropometric phenotypes on chromosome 1. All BP QTLs (systolic, diastolic, and mean BP) overlapped within their 95% CIs on those chromosomes. The QTL on chromosome 13 confirmed a previously reported linkage between diastolic BP and a microsatellite marker close to renin.⁵ In addition to the QTL for BP on chromosome 13, we also colocalized kidney renin concentration. Interestingly, plasma renin concentration mapped to chromosome 5, indicating a possible role of a gene(s) in this QTL in the regulation of the renin-angiotensin system.

Our genome scan could not replicate the QTL for pulse pressure, as previously mapped by Dubay et al⁵ However, using single-marker analysis at a microsatellite associated with the Cbp1 gene, we did find linkage for pulse pressure, confirming the findings reported by Dubay et al,⁵ albeit with a lower LOD score (4.72 versus 7.0). The possible explanation for the inconsistency in results is a significant deviation in the allele frequencies from Hardy-Weinberg equilibrium at the Cbp1 locus reported by Dubay et al,⁵ likely because of incomplete isogeneity in the LH and LN rats at the time of the cross; this deviation likely resulted in our difficulties in the creation of the genetic map and in the interval mapping, which was not previously confounded in 2-point linkage analysis.

Interestingly, numerous mapping studies in different rat strains have demonstrated QTLs overlapping our clusters on chromosomes 1 and 17 with similar phenotypes (Table 2). The identification of QTLs for related phenotypes in different strains gives further indication of the general importance of these regions in hypertension, end-organ damage, and metabolic disease in the laboratory rat.

View this table: [in this window] [in a new window]   TABLE 2. QTLs in Other F2 Intercrosses Overlapping QTLs in the LHx LN

The present study evaluated the genetic basis of the association of hypertension with metabolic disorders in LH rats (elevated total cholesterol, elevated LDL, and plasma insulin level) as previously reported.⁴ Correlation analyses confirmed that BP and cardiac hypertrophy are under the influence of different genetic determinants, despite some weakly positive correlations found by Vincent et al,⁴ but concordant with the findings of Lindpaintner et al²⁰ in stroke-prone spontaneously hypertensive rats.

In a cluster of QTLs on chromosome 17, we mapped several metabolic traits, such as total cholesterol, HDL cholesterol, triglycerides, VLDL triglycerides, phospholipids, insulin, and the plasma insulin-glucose ratio. We identified them as "intermediate phenotypes" because (1) they are mapped to the same genomic interval, (2) the same (LH) allele at that QTL showed a strong correlation with BP phenotypes, and (3) they are known to play a role in the pathogenesis of atherosclerosis and hypertension.²¹ Because these traits are easily measured in humans, they may be useful "intermediate phenotypes" of essential hypertension. Dysfunction or dysregulation of those genes may lead to the onset of hypertension and some symptoms of the metabolic syndrome, such as hyperlipidemia, obesity, and increased insulin levels. However, we cannot exclude the possibility that similar and related phenotypes are regulated by genes located close to each other in the genome, ie, a functional gene cassette. Therefore, it is possible that fine mapping may reveal different genetic factors for some of the clustered phenotypes.

Comparing our results with previously published QTLs for BP and related traits in different rat models,¹ we found that our QTLs for systolic, diastolic, and mean BP on chromosome 2 (peak marker D2rat270) contained the gene for the angiotensin II receptor 1b (Agtr1b), an interesting candidate gene for further follow-up. In the LH rat strain, chromosome 17 contains QTLs for the majority of the measured traits. Other studies have reported BP QTLs in the same region in 3 different F₂ intercrosses (Table 2).^22–33 We found that the angiotensin receptor 1a gene (Atr1a) is in this putative QTL region. All published heart weight/hypertrophy QTLs on chromosome 17 harbor a common interesting candidate gene, Drd1a (dopamine receptor 1a).^22–33 Overall, these results may demonstrate that rat chromosome 17 harbors major gene(s) involved in BP regulation as well as those involved in the regulation of major metabolic pathways and body homeostasis in LH rats.

Perspectives
The genetic regions described in our study, particularly those on chromosome 17, will be especially interesting for future studies through construction of consomic and congenic animals and expression studies of candidate genes. Furthermore, we found that the majority of chromosome 17 is well conserved between LH and LN rats; determining haplotypes in these strains could further facilitate narrowing of the QTL interval and identification of candidate genes for further follow-up in human populations.

	Acknowledgments

 
This work was supported by National Institutes of Health grant 5 UO 1 HL 54508.

Received July 13, 2004; first decision August 2, 2004; accepted August 31, 2004.

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