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Human Molecular Genetics 2007 16(R2):R195-R202; doi:10.1093/hmg/ddm126
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Genetic basis of polygenic hypertension

Alan Y. Deng*

Research Centre, Centre hospitalier de l'Université de Montréal, Université de Montréal, Montréal, Québec, Canada

* To whom correspondence should be addressed at: Research Centre, Centre hospitalier de l'Université de Montréal (CHUM), Technopôle Angus, 2901 Rachel St. East, Room 312 Montréal, Québec H1W 4A4, Canada. Tel: +1 5148908000 ext 23614; Fax: +1 5144127638; Email: alan.deng{at}umontreal.ca

Received April 30, 2007; Accepted May 3, 2007


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 GENETIC ARCHITECTURE OF...
 ORGANIZING BP QTLS
 POTENTIAL GENES FOR ESSENTIAL...
 TRANSLATING INSIGHTS FROM ANIMAL...
 PERSPECTIVE
 REFERENCES
 
Essential hypertension is a common disorder that leads to significant morbidity and mortality; however, the underlying mechanisms have remained elusive. Recent animal model studies have uncovered a complex genetic architecture of quantitative trait loci (QTLs) for blood pressure (BP), intricate QTL–QTL interactions and powerful genome regulations that underlie polygenic hypertension. BP, a quantitative trait manifesting as a continuous variation, seems to be controlled by individual ‘monogenic’ QTLs following Mendelian inheritance. Certain QTLs are functionally organized in epistatic modules that likely participate in pathways and cascades, whereas others belong to independent modules. This understanding provides insights into probable genetic mechanisms underlying essential hypertension. Translation of gene discovery to therapy will require an integrated approach that includes experimental validation of genes in animal models and in humans.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
GENETIC ARCHITECTURE OF...
 ORGANIZING BP QTLS
 POTENTIAL GENES FOR ESSENTIAL...
 TRANSLATING INSIGHTS FROM ANIMAL...
 PERSPECTIVE
 REFERENCES
 
Chronic high blood pressure (BP), i.e. hypertension, is a major world-wide risk factor that leads to fatal cardiovascular and renal diseases (1). Most cases of hypertension have unknown etiologies and are thus classified as essential hypertension. A major challenge in hypertension research is to identify the underlying mechanisms, unfettered by compounding secondary effects. The discovery of genes, known as quantitative trait loci (QTLs) (2), contributing to BP control is considered the most direct means of achieving this objective. To assist human hypertension research, rodent models have been developed that mimic essential hypertension. They have greatly facilitated the identification of BP QTLs, and the understanding of their mode of inheritance, their impact on BP and QTL–QTL interactions. Once these interactions and regulations are understood, the findings should aid the understanding of essential hypertension.

The present review focuses on insights gained from studying inbred experimental models of polygenic hypertension, principally Dahl salt-sensitive (DSS) rats, and translating them into humans. Emphasis is placed on forging a conceptual framework concerning the genetic architecture of polygenic hypertension, and formulating mechanistic interpretations that integrate individual QTLs in vivo controlling QTL functions.


   GENETIC ARCHITECTURE OF POLYGENIC HYPERTENSION OF ANIMAL MODEL
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 ABSTRACT
 INTRODUCTION
 GENETIC ARCHITECTURE OF...
ORGANIZING BP QTLS
 POTENTIAL GENES FOR ESSENTIAL...
 TRANSLATING INSIGHTS FROM ANIMAL...
 PERSPECTIVE
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Definition of a BP QTL
For simplicity, a QTL refers to 1 locus and 1 gene (3), and thus, QTL identification is the same as gene identification for polygenic hypertension either in animal models or humans.

The most widely utilized method to define a BP QTL is that fashioned by linkage (4,5). Nevertheless, two limitations imposed by linkage are apparent, i.e. its correlative nature and the genetic heterogeneity of a study population.

First, although it yields a rapid entry point into the chromosome segments where BP QTL may reside, linkage analysis is correlative and does not demonstrate a cause–effect relationship between a chromosome segment and a BP phenotype. Despite sophisticated statistical tools and computations (6), a proof is required to establish a causal relationship between a QTL location and BP effect. Therefore, further stringent experiments are necessary and without it, the linkage outcome can only be tentative and probable.

Secondly, linkage studies are generally conducted utilizing populations derived from intercrosses of two strains with contrasting BP features (e.g. F2, backcross). Consequently, no two animals in a study population are identical. This genetic heterogeneity indicates that significant linkage attributed to a single locus may be influenced by others, and cannot be exclusively due to the locus in question. To truly demonstrate the phenotypic effect of a single locus or more precisely a single chromosome segment harboring a BP QTL, this segment has to be studied alone in isolation. Without the proof of such a study, a linkage outcome can only be regarded as provisional.

To overcome the above two limitations, congenic strains (7) are employed to affirmatively define a BP QTL, based on a cause–effect relationship between a chromosome region harboring a QTL and a BP effect, and with homogeneous individuals unique for the chromosome region in question. Pros and cons for linkage and congenic strategies has been discussed recently (3). Table 1 summarizes the BP QTLs defined by congenic strains in hypertensive rat models.


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  		Table 1. BP QTLs defined by congenic strains and based on cause-effect relationships

 
BP QTLs acting in Mendelian mode
A BP QTL seems to resemble a ‘monogenic’ determinant in two ways (1), it acts independently of another QTL and (2) it behaves in complete dominance, recessivity and/or incomplete dominance.

Each QTL alone is sufficient to influence BP, and no combination with other QTLs is necessary to demonstrate a BP effect (Table 1). Therefore, although overall BP is determined by multiple QTLs, individual component QTLs can each resemble a ‘monogenic’ trait in BP control. To support this conclusion, a number of BP QTLs exhibit complete normotensive-dominance, i.e. one copy of the normotensive allele is adequate to lower BP to the same extent as two copies (8). Thus, the strength of these alleles supports the Mendelian behavior of BP QTLs.


   ORGANIZING BP QTLS
TOP
 ABSTRACT
 INTRODUCTION
 GENETIC ARCHITECTURE OF...
 ORGANIZING BP QTLS
POTENTIAL GENES FOR ESSENTIAL...
 TRANSLATING INSIGHTS FROM ANIMAL...
 PERSPECTIVE
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Effects of BP QTLs in hypertension and normotension
Hypertensive animals possess both BP-increasing QTL and BP-decreasing QTL alleles and that the same is true for normotensive animals (9–11). Consequently, BP regulation must be viewed as a balanced equilibrium of both BP-increasing and BP-decreasing alleles at different QTLs. An obvious question to pose is: how do QTLs with opposing effects function in the entire physiological system to set chronic BP? Etiologically, how does an organism reconcile this contradiction and eventually tilt towards either hypertension or normotension, while both BP-increasing and BP-decreasing QTLs are active in its genome? Do BP-increasing and decreasing alleles merely cancel each other out in a simple 1+(–1)=0 fashion, or do more complex interactions exist?

QTL–QTL epistatic interactions
The best example of epistasis is illustrated by the study of interactions between two adjacent QTLs, C10QTL1 and C10QTL4, whose chromosome intervals are refined almost to experimental limits (12). A total of 16 and 10 genes or undefined loci (Locs), respectively, reside in each QTL interval. Because of this fine congenic resolution, the possibility has been minimized that more than one QTL can exist in each of the two QTL intervals. The epistatic hierarchy between the two QTLs is not clear, however, as their BP effects are indistinguishable.

The hierarchical relationship between two epistatic QTLs is exemplified by the interaction of two QTLs on Chr 3. One QTL possesses a BP-lowering effect (i.e. –BP QTL) and the other shows a BP-raising effect (i.e. +BP QTL) (11). When combined, their BP effects were intuitively expected to cancel each other out, but their actual combined BP effect was to decrease BP to the same extent as that of –BP QTL alone. This fact indicates that –BP QTL acts epistatically to +BP QTL. Because of it, the epistatic hierarchy between them can be established as –BP QTL>+BP QTL.

Classification of BP QTLs according to epistatic modules
Epistatic interactions dictate that the BP effects of multiple QTLs that act epistatically to one another cannot exceed that of a single QTL alone (12). This functional interplay effectively places a ‘ceiling’ that solves the dilemma of QTL redundancy and accounts for the non-cumulative nature of QTL–QTL relationships in the overall determination of BP. The QTL that stands higher on an epistatic hierarchy (e.g. –BP QTL) overrides the effect of a BP QTL lower on the same hierarchy (e.g. +BP QTL). As such, one can resolve, at least in part, the paradoxical phenomenon of how LEW remains normotensive while carrying BP-increasing QTL alleles, and how DSS remains hypertensive while carrying BP-decreasing QTL alleles.

Figure 1 attempts to construct a probable mechanistic hierarchy among some QTLs.


Figure 1
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  		Figure 1. Preliminary assemblage of BP QTLs in DSS rats according to epistatic modules. The proposed scheme is simplified and does not include shunts, bifurcations and/or compensatory pathways/cascades (p/cs). Module refers to an epistatic module. p/c1 (or module 1) is based on the results published in (11), p/c2 (module 2) and p/c3 (module 3) are based on the results published in (12), p/c4 (module 4) and p/c5 (module 5) are based on the results published in (42) and p/c6 (module 6) is based on the results published in (15). It is known that modules 2 and 3 are distinct, as are modules 4 and 5. It is not clear what the relationships among certain modules are. For example, module 1 may belong to either of the remaining five modules or may be independent. Module 2 is separate from module 3, but may belong to either of the remaining four modules, or may be separate. Similar logical explanations apply to the relationships between the rest of the possible modules. ? indicates that a p/c may or may not be separate from the others. Only the epistatic hierarchy between –BP QTL and +BP QTL in module 1 is defined. Epistatic hierarchies between or among QTLs in the remaining possible modules are not known. Arrows and precursors in a p/c only indicate the general directions and products generated. They do not signify consecutive steps nor the number of steps nor where exactly in a P/C that the step is. There could be an undefined number of steps between two precursors. ‘+’ and ‘–’ signs indicate that the QTL alleles of LEW possess BP-raising and BP-lowering effects, respectively. BP, blood pressure.

 
Mechanistically, –BP QTL1 and +BP QTL (11) could be involved in a common, yet, hierarchical pathway/cascade (p/c). Each could participate in one of the sequential steps leading to the final BP determination (as in p/c1 in Fig. 1). Because phenotypic differences are distinguishable between –BP QTL and +BP QTL (11) and with the former being epistatic to the latter, –BP QTL would function in the latter part of p/c1. The rest of the QTLs can be modularized according to their known epistatic relationships (Fig. 1).

The mechanistic scheme presented in Figure 1 serves as a basic building block and entry point onto which all BP QTLs can be integrally assembled. To achieve this objective, ‘double’ congenic combinations are needed between two QTLs from a representative of each epistatic module. If they act epistatically, they can be catalogued into the same modular p/c; if not, they belong to a different modular p/c.

QTLs demonstrating additive BP effects
The effects of some QTL combinations are additive, not epistatic. For example, C2QTL2 and C2QTL3 act additively, i.e. the two QTLs augment the effect of each other. In this case, each QTL could use separate yet parallel p/cs, i.e. p/c4 and p/c5 (Fig. 1), and when combined, C2QTL2 and C2QTL3 can cause the additive effect.


   POTENTIAL GENES FOR ESSENTIAL HYPERTENSION
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 ABSTRACT
 INTRODUCTION
 GENETIC ARCHITECTURE OF...
 ORGANIZING BP QTLS
 POTENTIAL GENES FOR ESSENTIAL...
TRANSLATING INSIGHTS FROM ANIMAL...
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The molecular mechanisms underlying certain rare monogenic forms of hyper-and hypo-tension have been discovered (13,14), but little progress has been made in identifying genes and the mechanisms underlying essential hypertension. A major stumbling block lies in the fact that numerous interacting QTLs can influence the same phenotype and multiple QTLs are involved in overall BP determination. BP QTLs can be controlled by a regulatory system(s) (15). Added to this genetic complexity are inherent limitations, such as genetic heterogeneity, phenotyping variability, sampling bias, disparity in model assumption and environmental complications in all human investigations of essential hypertension. Moreover, the research in human essential hypertension is limited to drawing conclusions based on correlative results. No experimental manipulations are permissible so that a cause–effect relationship tantamount to creating a congenic strain can be established in human studies.

General principles, pros and cons associated with resources in combination with specific tools in essential hypertension have been extensively reviewed, discussed (16–26) and will not be reiterated here. Data from direct (i.e. association of genes) and indirect (i.e. genome-wide linkage) approaches (27) have yielded clues to potential candidate genes and chromosome regions containing QTLs for essential hypertension. The results of recent genomic scans are presented elsewhere (17–19,21–24) and will not be discussed further. Although genome-wide association studies accompanied by study replications have been adopted to detect susceptibility loci for complex diseases (28,29), their use in essential hypertension research is yet to bear fruit.

Assuming that a gene of interest is causal, but not simply a marker gene, to BP control, the candidate gene in question should be associated with essential hypertension. On the basis of this assumption, a multitude of association studies has been performed on candidate genes. By and large, these genes belong to five physiological classes, i.e. renin–angiotensin–aldosterone system, sodium volume, adrenergic, vascular and metabolic systems (16). Table 2 summarizes results of meta-analysis (2,26,30) on candidate genes for essential hypertension.


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  		Table 2. Meta-analyses of chromosome regions and candidate genes

 

   TRANSLATING INSIGHTS FROM ANIMAL MODELS TO HUMANS
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 ORGANIZING BP QTLS
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Recent experimental studies have suggested molecular pathways and conceptual frame-works for BP QTLs of polygenic hypertension. They may be translated into the understanding of essential hypertension in several ways.

First, the discovery of molecular basis for individual BP QTLs may be applied to comprehending the patho-physiology of essential hypertension. For example, {alpha}-ADDUCIN (ADD1) was originally discovered in the Milan polygenic model and later was employed to perform association studies in essential hypertension (31). ADD1 may cause hypertension by enhancing tubular sodium absorption. Another BP QTL is tentatively identified as 11ß-hydroxylase (Cyp11b1) in Dahl rats (32), despite limited association studies of CYP11B1 conducted in essential hypertension (33).

Secondly, conceptual insights gained from animal model studies of polygenic hypertension may be translated into the understanding of essential hypertension. One recurring finding throughout the world in essential hypertension research has been that while one gene or a chromosome region is associated with or linked to essential hypertension in some populations, it is not so associated or linked in others (Table 2). This ‘inconsistency’ has branded overall genetic research ‘conflicting’ or ‘inconclusive’ (16,22). The genes shown in Table 2 seem to accentuate this conflict. However, the seeming ‘conflict’ may be attributed, at least partially, to population specificity (34,35) and the genetic mechanism can be explained from the insights gained in animal studies of polygenic hypertension.

Because a defect in one QTL in an epistatic module (Fig. 1) can be sufficient to alter BP, one hypertensive individual representing a specific population may have an alteration in one QTL, and another hypertensive individual representing another population may have an alteration in an entirely different QTL in the same epistatic module. Consequently, both individuals are hypertensive, but their underlying genetic bases are different. Moreover, a defect in a QTL higher on an epistatic hierarchy can mask QTL effects lower on the same pathway/cascade. When analyzing the function of a QTL in association with BP in human studies, a lack of an effect could also be due to the influence of another gene downstream in the epistatic hierarchy.

Another translatable insight from animal models of polygenic hypertension to essential hypertension is that major BP QTL effects can be obscured by genetic heterogeneity. The prevailing dogma is that BP is a quantitative and polygenic trait, and therefore, each QTL may possess only a ‘minor’ effect on overall BP and a combination of more than one QTLs might be required to reach a threshold that produces a phenotypic effect. This reasoning has been used to rationalize why no ‘major’ QTLs have been detected in population-based studies (18,22). Contrary to this observation, almost all the QTLs proved by a cause–effect relationship have major effects on BP (Table 1). One QTL alone is sufficient to alter BP and not conditional to the impact of other QTLs in trans to exhibit such an effect (Table 1). Not only that, a single dominant allele of a QTL is enough to exert such a major BP effect comparable with that of two alleles (8).

With so dramatic a consequence, why then, has no study unearthed a major BP QTL in humans (36), even in isolated populations (22)? The answer probably lies in inherent limitations imposed by human genetic analyses. Similar to linkage analysis performed in an outbred animal population (37), genetic heterogeneity dilutes the effect from a single BP QTL and compounds it with QTL–QTL interactions and genome regulation (15). Even in linkage analysis involving inbred animals and a uniform environment, QTLs with major effects such as C18QTL1 (i.e. 48%) (15) manifested only a minor effect (7.5%) (38). It was only after C18QTL was isolated from the rest of the LEW genome that the true magnitude of its effect could be seen. Therefore, genetic heterogeneity itself is sufficient to explain the lack of detection of a ‘major’ BP QTL in human studies.


   PERSPECTIVE
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There are challenges ahead in identifying QTLs at the molecular level in both animal models and humans, in understanding functional hierarchy among QTLs, in elucidating genomic regulatory mechanisms controlling QTL functions and in comprehending gene–environment and gene–gender interactions and epigenetic effects on BP control.

First, the QTL identification in animal models will need to integrate mutational implications of a given gene for 1 QTL (i.e. by gene profiling and mutation screenings) with functional validation (i.e. via fine congenic resolution, transgenesis and/or gene targeting) (3). Once a QTL has been identified at the molecular level, a direct translation of patho-physiological mechanisms into essential hypertension may be realized.

Secondly, while a BP QTL can be implicated by correlation via associating a gene in a human population and even in a replicated population with essential hypertension using the most powerful statistical tools (26), the validity of the candidate gene may need to be authenticated in an appropriate animal model via e.g. fine congenic resolution, transgenesis and/or gene targeting.

Thirdly, it is informative to elucidate regulatory mechanisms or to identify ‘hypertension suppressors’ that seem capable of overriding functions of BP QTLs (15) Two types of genetic factors can be such a ‘hypertension suppressor’, (a) one (or several) of the BP QTLs themselves and (b) one (or several) of genes other than BP QTLs. If a BP QTL can be such a hypertension ‘suppressor’, combining a BP QTL with another by congenic strains in double and/or multiple combinations may provide some insights. If the ‘suppressor(s)’ is a gene other than a BP QTL, it is necessary to isolate the chromosome segment(s) that harbors it (them) first, and then, to carry out its molecular identification.

Finally, gene–environment interactions, epigenetic factors, gene–gender interactions, aging effects and salt sensitivity that can influence the development of hypertension need to be addressed (39–41).


   ACKNOWLEDGEMENTS
 
The author thanks Dr J. Michael Wyss for thorough editing of the manuscript, Drs J. Lavoie, Z. Pausova and M. Abrahamowicz for helpful comments, Ovid Da Silva for his editorial assistance and the Canadian Institutes of Health Research for financial support.

Conflict of Interest statement. None declared.


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 TRANSLATING INSIGHTS FROM ANIMAL...
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