Genetics and Hypertension: Is It Time to Change My Practice?

Canadian Journal of Cardiology 28 (2012) 296 –304

Review

Genetics and Hypertension: Is It Time to Change My Practice? Christian Delles, MD, FRCP, and Sandosh Padmanabhan, PhD, FRCP Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom

ABSTRACT

RÉSUMÉ

Recent advances in genotyping technology and in particular a number of large-scale genome-wide association studies have helped to unravel the genetic basis of hypertension. Although our knowledge is still far from being complete it is important to ask how genetic findings could be translated to clinical practice. In a first step we summarize the strategies to dissect the genetics of hypertension from candidate gene studies to genome-wide association studies and recent sequencing experiments. The greatest hope in this context is the development of new drugs that are based on newly discovered pathophysiological principles. We describe examples where significant therapeutic effects are achieved with agents targeting pathways that contribute only small amounts to the genetic variability of a phenotype. There are good reasons to believe that new drugs will be developed based on genetic data in hypertension. We also highlight the potential for pharmacogenetics and risk stratification. The former is not currently supported by a larger body of evidence, but well designed studies are under way. The latter needs to follow the same principles for evaluation of other novel biomarkers of cardiovascular risk and is unlikely to influence clinical practice in the next few years.

Les récentes avancées de la technologie de génotypage et, en particulier, de nombreuses études d’association pangénomiques à grande échelle ont aidé à éclaircir les bases génétiques de l’hypertension. Même si nos connaissances sont encore loin d’être complètes, il est important de s’interroger sur la manière dont les découvertes génétiques pourraient être traduites dans la pratique clinique. Dans un premier temps, nous résumons les stratégies pour disséquer la génétique de l’hypertension des études de gènes candidats aux études d’association pangénomiques et aux récentes expériences de séquençage. Le plus grand espoir dans ce contexte est la mise au point de nouveaux médicaments qui sont basés sur des principes physiopathologiques récemment découverts. Nous décrivons des exemples où des résultats thérapeutiques importants sont atteints à l’aide d’agents ciblant les voies qui contribuent que très peu à la variabilité génétique d’un phénotype. Il y a de bonnes raisons de croire que de nouveaux médicaments basés sur les données génétiques de l’hypertension seront mis au point. Nous mettons en relief le potentiel de la pharmacogénétique et de la stratification de risque. La première n’est actuellement pas soutenue par un grand nombre de preuves, mais des études bien conçues sont en cours. La seconde a besoin de suivre les mêmes principes dans l’évaluation d’autres nouveaux biomarqueurs de risque cardiovasculaire et n’est pas susceptible d’influencer la pratique clinique au cours des prochaines années.

Hypertension (HTN) is one of the most important risk factors for cardiovascular diseases. There is a direct relationship between the level of blood pressure (BP) and the risk for developing cardiovascular diseases such as coronary artery disease and stroke.1 Advances in antihypertensive therapy over the past decades have considerably reduced morbidity and mortality associated with high BP. Nevertheless, we are facing a global epidemic of HTN with the prevalence of HTN increasing not only in industrialized but even more so in developing coun-

tries.2,3 Better risk stratification and better and more targeted treatment of HTN are desperately needed. There is a clear genetic component to BP with estimated heritabilities of systolic and diastolic BP in the range of 15% to 40% and 15% to 30%, respectively.4-6 The sibling recurrent risk of HTN is in the range of 1.2 to 1.5.7 These figures are influenced by nongenetic factors including shared environment and measurement errors that explain the wide range across the literature. The continuous distribution of BP and associated cardiovascular risk in the general population suggests a complex polygenic inheritance of essential HTN.8 Some forms of secondary HTN, however, are due to mutations in single genes and their inheritance follows classic Mendelian laws.8 It is not unreasonable to believe that in a condition that is characterized by a considerable genetic component a better

Received for publication December 2, 2011. Accepted February 6, 2012. Corresponding author: Dr Christian Delles, BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, 126 University Place, Glasgow G12 8TA, Scotland, United Kingdom. Tel.: ⫹44-141-330-2749; fax: ⫹44-141-330-7394. E-mail: [email protected] See page 302 for disclosure information.

0828-282X/$ – see front matter © 2012 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.cjca.2012.02.004

Delles and Padmanabhan Genetics and Hypertension

understanding of this genetic basis could lead to better clinical management. At the same time it is fair to say that current practice in cardiovascular medicine is not directly influenced by findings from recent large-scale genetic studies.9 In this article we will briefly summarize the current strategies to unravel the genetics of HTN, illustrate some of the recent findings, and then explore the potential of genetic findings to translate into clinical medicine in HTN. Genome-Wide Approaches to Unravel the Genetics of Human Hypertension Linkage studies The first hypothesis-free approach to mapping genetic loci for BP and HTN was linkage analysis which used equally spaced microsatellite markers to test for cosegregation of a chromosomal region and a trait of interest.10 This approach while very successful in monogenic forms of HTN had limited success with essential HTN. Results from genome-wide linkage studies confirm the polygenic nature of BP control. Loci that are associated with HTN have been found on almost all chromosomes.11 The availability of data from numerous genome-wide linkage studies made it possible to conduct metaanalyses to identify the most robust signals possible. Koivukoski et al.12 analyzed 9 genome-wide scans of BP or HTN using the genome-search meta-analysis method and found susceptibility loci on chromosomes 2 (2p12-q22.1) and 3 (3p14.1q12.3). A locus on the short arm of chromosome 2 was further found to be associated with response to antihypertensive therapy in Caucasian subjects13 and to colocalize to a chromosomal region that was found to be associated with HTN in AfricanAmerican hypertensive subjects.14 Even if linkage studies have recently been replaced by genome-wide association studies (GWAS), the principles that were developed in linkage studies still inform study design, data analysis, and interpretation today. These principles include the robust evidence of a polygenic origin of HTN, the relatively small effect on BP of each single genetic variant, the required large sample sizes and excellent phenotypic quality, and the need to confirm findings by replication, meta-analysis, and functional studies. A major limitation of linkage studies was the lack of positional resolution, which necessitates follow-up finemapping and sequencing experiments to identify the causative gene. GWAS The introduction of chip-based genotyping arrays15,16 allows genotyping of a large number of genetic variants of up to 1 million single nucleotide polymorphisms (SNPs) simultaneously at reasonable costs. Further SNPs can be imputed based on the knowledge of linkage disequilibrium from the international HapMap project (http://hapmap.ncbi.nlm.nih.gov) and the 1000 Genome project (http://www.1000genomes.org). In 2007, 2 major GWAS into HTN have been reported by Levy et al.17 and the Wellcome Trust Case Control Consortium (WTCCC).18 The former was based on the Framingham Heart Study and associated BP at 2 different time points and long-term averaged BP with 100,000 polymorphic markers using the Affymetrix 100k chip (Affymetrix, Santa Clara, CA). The latter was based on hypertensive subjects from the British

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Genetics of Hypertension (BRIGHT) study that were compared with nonphenotyped general population control subjects and genotyped for 500,000 genetic markers using the Affymetrix 500k chip (Affymetrix). Both studies did not identify signals that were associated with HTN on a genome-wide level although the WTCCC study identified multiple genetic markers for other common diseases. Although both studies involved several thousand cases and controls their power to detect the small contribution of multiple genetic loci on BP was too small. The most obvious strategy to overcome this problem was to drastically increase the sample size of GWAS. The first robust signals from GWAS into HTN derive from 2 large consortia, the Global Blood Pressure Genetics (Global BPgen) and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE). The Global BPgen consortium tested 2.5 million genotyped or imputed SNPs for association with systolic or diastolic BP in 34,433 subjects of European ancestry19 and identified 8 regions with genome-wide significance. The variants were near the CYP17A1, CYP1A2, FGF5, SH2B3, MTHFR, ZNF652, and PLCD3 genes and chromosome 10 open reading frame 107 (c10orf107). CHARGE studied 2.5 million genotyped or imputed SNPs in 29,136 subjects and found significant (P ⬍4 ⫻ 10⫺7) associations with systolic BP for 13 SNPs, with diastolic BP for 20 SNPs, and with HTN for 10 SNPs.20 Meta-analysis of the data from the 2 consortia revealed genome-wide significance (P ⬍5 ⫻ 10⫺8) for ATP2B1, CYP17A1, PLEKH7, SH2B3, CACNB2, CSK-ULK3, TBX3TBX5, and ULK4 for association with systolic or diastolic BP or HTN. Following on from these exemplar studies other GWAS into HTN have been conducted in other ethnicities,21,22 in even larger sample sizes23 and using alternative strategies to select the primary study cohort.24 It is beyond the scope of this report to provide a comprehensive overview of the ever-growing number of genetic loci that have been robustly associated with BP in recent GWAS. Such comprehensive overview can be found in recent reviews9,25 and online at http://www.genome. gov. Table 1 shows some of the strengths and weaknesses of GWAS. Candidate Gene Studies Traditional candidate gene studies Studies that focus on a limited number of candidate genes can be very successful to understand the genetic components of BP variability across the population. Candidate genes are selected for their known or presumed role in the pathogenesis of HTN, and the most obvious candidate genes are components of the renin-angiotensin-aldosterone system (eg, the aldosterone synthase gene CYP11B2), signal transduction (eg, the guanine nucleotide-binding protein subunit beta-3 gene GNB3), salt and water handling (eg, the adducin-␣ gene ADD1), regulation of vascular tone (eg, the endothelial nitric oxide synthase gene NOS3), and production of or defenses against oxidative stress (eg, the cytochrome b-245 alpha polypeptide gene CYBA, which encodes the p22phox subunit of nicotinamide adenine dinucleotide [phosphate] oxidase [NAD(P)H] oxidase). Despite numerous reports on association in small and medium sized cohorts, however, there has been little evidence for a robust association of any of these

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Table 1. Candidate gene studies and GWAS: strengths and weaknesses Strengths GWAS ● GWAS are hypothesis-free and therefore unbiased. ● This enables the discovery of new susceptibility genes and pathogenetic principles based on genetic findings. ● Population-based GWAS can study all meiotic recombination events in a population at high marker density. ● GWAS detect stratifications within populations for example due to different ancestry or evolutionary events. Candidate gene studies ● Candidate genes can be chosen based on a wide range of evidence from pathophysiological considerations, data in other species, data from gene expression studies and others. ● Genotyping costs are relatively low. ● Due to low genotyping costs more weight can be put on high-fidelity phenotyping.

Weaknesses ● Large sample sizes are required to detect associations at genome-wide significance level. ● Genotyping costs are relatively high. ● Due to the required large sample sizes phenotypic quality is not in all GWAS optimal and may differ between cohorts that have been brought together. ● GWAS focus on common genetic variants and are blind to rare (private) mutations. ● Analysis of GWAS data involves robust quality control pipelines and bioinformatic methods that can handle very large datasets. ● The individual contribution of genetic variants to the BP phenotype is small. ● Most of the study designs lack power to detect these small effects. ● Inconsistency of phenotyping did not allow results to be compared or combined. ● Selection of candidate genes depended on known pathways of BP regulation precluding undiscovered pathways. ● Most of the candidate gene studies tend to be single SNP studies that are not completely informative of the variability within a gene. Additional SNP identification requires sequencing resources which were not readily accessible. ● With few exceptions studies of rare frequency variants were not done until recently. ● Current study designs preclude meaningful study of gene-gene or gene-environment interactions.

Genome-wide association studies (GWAS) examine the association of a large number of genetic variants across the whole genome with a given phenotype. Candidate gene studies examine the association of a limited number of genetic variants within a limited number of genes with a given phenotype. BP, blood pressure; SNP, single nucleotide polymorphism.

genes or SNPs within these genes with HTN in current large scale studies.26,27 The main strengths and weaknesses of candidate gene studies are listed in Table 1. Despite these limitations the candidate gene approach remains 1 of the cornerstones of studies into the genetics of HTN and has been reviewed extensively.28-34 Large-scale candidate gene studies With the advances of technology and reduced costs for genotyping large-scale candidate gene projects are possible. An example of this approach is the ITMAT/Broad/CARE Vascular Disease 50k SNP Array (IBC Chip; Illumina, San Diego, CA) that allows genotyping of about 50,000 SNPs in 2,100 cardiovascular candidate genes at relatively low costs. The large scale of these projects, however, necessitates correction for multiple tests and has an unfavourable impact on sample size and power of such studies. A recent large study in a discovery sample of 25,118 individuals from hypertensive case-control studies and general population samples with replication in a further 59,349 individuals identified and replicated a new SNP at the lymphocytespecific protein 1/troponin T type 3 locus LSP1/TNNT3 and a new SNP at the methylenetetrahydrofolate reductase-natriuretic peptide B locus MTHFR-NPPB and replicated SNPs at the angiotensinogen locus AGT and the plasma membrane calcium ATPase locus ATP2B1 that were reported previously. The study also identified 4 novel loci from combined analysis of discovery and replication sets.35 While ambulatory BP can be considered a more accurate phenotype, 2 gene-centric studies, 1 using the IBC chip and another using a custom SNP array were not any more successful at identifying loci, and the effect sizes for the SNPs were similar to those obtained from GWAS of office BP.36,37 The success of these studies to identify genetic associations in specific cohorts can be explained by the careful selection of candidate genes, so that each SNP had higher a priori chances

of being truly associated with BP than SNPs on the commonly used GWAS chips. In contrast, extracting candidate gene-specific data from genome-wide SNP chips is a less successful approach. A recent example for this strategy is a study into 160 candidate genes for BP covering 2411 SNPs in 1644 subjects of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) S3 cohort that derived from a 500k genotyping project.38 None of these SNPs remained significantly associated with BP after Bonferroni correction. The top 12 hits in 7 genes for association with BP and/or HTN (P ⬍10⫺3) failed to be replicated in independent cohorts.

Rare Variants and Sequencing Studies All of the genetic variants that have been found to be associated with HTN in GWAS have in common that their effect on BP is relatively modest in the range of 0.5 to 1 mm Hg per SNP. For example, in Global BPgen the SNP showing the strongest association with systolic BP (rs11191548, P ⫽ 7 ⫻ 10⫺24) increases systolic BP by 1.16 mm Hg per major allele.19 This relatively small effect can be explained by the fact that GWAS are insensitive to some of the genetic components of BP regulation, as rare genetic variants are not part of the panel of SNPs on the genotyping chips. Ji et al.39 therefore sequenced 3 candidate genes for HTN, SLC12A3, SLC12A1, and KCNJ1, in order to detect rare genetic variants. The candidate genes were selected due to their known role in monogenetic disorders of renal electrolyte handling that are associated with low BP, and the authors hypothesized that variants of these genes could also contribute to BP regulation in the general population. Indeed, the mean long-term systolic BP among mutation carriers was 6.3 mm Hg lower than the mean of the cohort—an effect that is far stronger than that of the signals from GWAS. Current strategies in the post GWAS era therefore focus on discovery of rare genetic variants and private mutations that can only be detected by complete sequencing of genes of inter-

Delles and Padmanabhan Genetics and Hypertension

est. This target gene-driven sequencing approach as in the study by Ji et al.39 will soon be overtaken by genome-wide sequencing studies of exons (the “exome”) and by complete resequencing of the whole genome with further advances of technology and reduced costs.40 Analysis of these large datasets will be a major challenge for bioinformatics, but the data promise to take us to the next level of understanding the genetics of HTN. How Could Genetic Information Change Clinical Practice? The progress in the discovery of new genetic loci for HTN was always accompanied by critical voices that questioned the methodologies, results, or interpretation of data. Such criticism was often the result of false or too high expectations and promises by researchers who conducted the studies. Two of the main criticisms are the lack of immediately plausible results from large-scale genotyping projects; and the low gain in knowledge and understanding relative to the enormous costs and efforts associated with modern genomics. The publication of the BRIGHT study was accompanied by an editorial by Harrap41 who asked “Where are all the blood pressure genes?” This article nicely summarized the disappointment caused by the lack of genome-wide significant results from an expensive and time-consuming effort; moreover, it confronted the apparently negative findings with the expectation that at least the most plausible candidate genes should have shown signals in the linkage analysis. What was already clear at that time,41 and what is even clearer now, is that the marker density in BRIGHT was far too low to truly cover the whole genome, that the study was underpowered to detect the small effects of common genetic variants, and that our “favourite” candidate genes do not necessarily feature strongly as the primary cause of HTN even in the more recent large-scale GWAS. The negative findings of WTCCC18 and the study by Levy et al.17 were, among others, attributed to inaccuracies in phenotyping and low marker density, respectively. Almost a decade later we find the same arguments to support skepticism about the scientific and clinical benefit of large-scale genetic studies and in particular, of GWAS. The recent discussion between Kurtz42 and Dominiczak and Munroe43 is archetypal for the contrasting views of those being against and those being supportive of further large-scale genomic projects. It is therefore important to consider how exactly better understanding of the genetic basis of HTN could translate into clinical practice. It is then possible to examine if recent advances have already fulfilled our hopes, if further work is required, or if our initial hopes were unrealistic. Already in 1998, when modern genetics was still in its early stages, Bell44 outlined the possible implications of genetic findings on clinical practice. These implications still apply in 2012; they are summarized in Table 2 and will be discussed in the following sections. Understanding the Molecular Basis of Hypertension The traditional differentiation between primary (essential) and secondary HTN is a useful clinical concept. However, the work by Ji et al.39 highlights that variants of the same genes that account for severe recessive forms of hypotension or HTN may

299 Table 2. Possible clinical implications of findings from modern genetic studies ● ● ● ● ●

Development of a new taxonomy of disease based on molecular mechanisms, not on phenotype. New drugs can be developed rationally from our understanding of pathogenesis. Drug development and utilization can be focused on disease subtypes likely to respond to treatment. Adverse effects of drugs can be avoided by genetic screening. Genetic risk factor analysis will facilitate environmental modification, screening, and therapeutic management of people before they develop symptoms. Modified from Bell.44

also involved in BP regulation in the general population. Findings from candidate gene studies for example of the aldosterone synthase gene CYP11B2,45 also demonstrate that a major cause for secondary HTN (aldosterone excess) could contribute in a more subtle way to essential HTN. Genetic studies therefore help to understand the commonalities between primary and some forms of secondary HTN and could help to develop a unifying pathophysiological concept that is based on molecular mechanisms. Such molecular concepts and a new taxonomy of disease are particularly important for essential HTN. Apart from very few and crude concepts (eg, low vs high renin HTN) virtually all patients with essential HTN are treated the same, simply because the factors that contribute to HTN in a single individual are not known. In the foreseeable future genetic studies will detect more and more facets of HTN that were previously unknown and help to better understand the pathophysiology of the condition before this knowledge will eventually be applicable to individual patients in the far longer term. The majority of genes that have been found to be associated with BP in GWAS were not originally thought to play a key role in the pathogenesis of HTN. Association signals with genes involved in calcium transport (ATP2B1) or encoding voltage-gated calcium channels (CACNB2) help us to focus on underlying mechanisms on a cellular level, and genes encoding kinases such as UNK4 or signalling molecules such as SH2B3 focus our thinking toward the regulatory pathways.20 The fact that other genes such as most of the components of the reninangiotensin-aldosterone system do not feature prominently in GWAS is in no way contradictory to the well established role of angiotensin II in HTN or the proven clinical benefit of reninangiotensin-aldosterone system blockade in the treatment of HTN, but highlights that at least common variants of these genes are not primary causes of HTN. The clinically evident alterations of the renin-angiotensin-aldosterone system could occur downstream of other primary events that are currently being detected by genetic and other molecular approaches. A prominent recent example of entirely new insights in the pathogenesis of HTN is the discovery of an association between a variant in the gene encoding uromodulin, UMOD, and HTN. This association was detected in a GWAS of extreme HTN where cases and controls were selected from the far ends of the BP distribution in the general population.24 Uromodulin, or Tamm-Horsfall protein (THP), is the most abundant protein in human urine. It is a glycosylphosphatidylinositol-anchored glycoprotein that is produced by the thick ascending limb of the loop of Henle. The UMOD gene is located on chromosome 16. Uromodulin is known to play a

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role in the defense against urinary tract infections and in the formation of kidney stones, particularly in autosomal dominant hyperuricemic nephropathy.46 Uromodulin has also been found to be involved in the progression of kidney disease and renal fibrosis,47,48 serves as a marker for chronic kidney disease,49 and consequently, variants of the UMOD gene have been found to be associated with indices of renal function,50,51 chronic kidney disease,52 and incident renal disease53 in recent GWAS. There is also evidence that uromodulin may modulate electrolyte transport in distal nephron segments54 and that the levels of urinary uromodulin are genetically determined.55 However, it was not until a GWAS specifically into HTN24 that the direct association between UMOD and HTN (ie, independent of renal function) was discovered. Detailed molecular and clinical studies to explain this association are currently under way. Another example how GWAS can inform and in some cases correct our understanding of pathophysiology is illustrated by a recent report by Ehret et al.23 The authors performed a GWAS of systolic and diastolic BP in 200,000 individuals of European descent. From 29 genome-wide significant variants a risk score was developed that was associated with HTN and related target organ damage but not with chronic kidney disease. While undoubtedly high BP is strongly associated with renal disease and particularly with renal death56 the study by Ehret et al.23 demonstrates that high BP and renal disease do not necessarily have the same molecular origin. New Therapies and Pharmacogenetic Aspects Development of novel drugs based on genetic findings Better understanding of the pathophysiology of HTN has already been achieved by recent large-scale genetic studies. From discovery of a molecular pathway to pharmaceutical targeting of this pathway and development of new therapies it will, however, take many years. It would be unrealistic to believe that the above findings will soon translate to clinical practice. We would, however, like to emphasize that this translation is very well possible and that genetic hits are ideal molecular targets for new therapies. It has been argued that the relatively small effects of genetic variants on BP in the range of 0.5 to 1 mm Hg per SNP will not make them attractive targets for drug development. This is not the case. Experiences from the development of statins are an important lesson in this context. Statins were developed in a traditional way from understanding the biochemical pathways and recognition of 3-hydroxy-3-methylglutaryl coenzyme A reductase as the key enzyme in the biosynthesis of cholesterol being responsible for familiar hypercholesterolemia by Goldstein and Brown in 1973.57 Statins (ie, inhibitors of this enzyme) lower low-density lipoprotein (LDL)-cholesterol by 40%-60%.58 In a GWAS of LDL-cholesterol, high-density lipoprotein (HDL)-cholesterol and triglycerides by Kathiresan et al.,59 35 years after the seminal paper by Goldstein and Brown in 1973,57 a SNP (rs12654264) in the HMGCR gene encoding 3-hydroxy-3-methylglutaryl coenzyme A reductase has been found to be associated (P ⫽ 1 ⫻ 10⫺20) with plasma LDLcholesterol levels. However, this was only 1 out of 7 loci that were associated with LDL-cholesterol in this report, and the

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effect size of the SNP was relatively small: each copy of the minor allele of these SNPs, including rs12654264, decreased LDL cholesterol concentrations by only 5 to 8 mg/dL.59 The situation in hyperlipidemia is not unlike that in HTN. In both conditions large numbers of genetic variants have been identified to be associated with levels of lipids or BP, but the effect size of each of these variants is very small. Nevertheless, the example of statins demonstrates that drugs that address a certain pathogenetic principle can be extremely powerful despite the relatively small effect size of a genetic variant of this principle in a GWAS. If statins were not developed in the traditional way, a thorough work-up of the GWAS signals would also have led to their discovery. It is not unreasonable to believe that such developments will take place with hits from GWAS in a number of conditions including HTN and that entirely new therapeutic principles will be developed. It should be noted that there is still a considerable time span between development of a new drug and approval for clinical use particularly in first-in-class therapies60 to which a preclinical development phase would have to be added. It would be very optimistic to believe that the new knowledge will translate into novel therapies within less than 10 years, but it would be wrong to believe that the recent genetic findings will not translate into new and better therapies at all. Pharmacogenetics There have been hopes that modern genetic studies will identify variants that predict treatment response and side effects of antihypertensive therapies. However, there are currently only very few sufficiently powered pharmacogenetic studies in HTN. Other conditions that are pathophysiologically less complex or characterized by closer relationships between gene variants and disease phenotypes are more progressed. For example, the response to clopidogrel can be predicted from CYP2C19 genotype in a clinically meaningful fashion.61 Likewise, a GWAS identified that a SNP in the gene encoding the organic anion transporter peptide OADP1B1, SLCO1B1, is associated with statin-induced myopathy.62 While the clopidogrel data have only been presented recently the SLCO1B1 data were published in 2008 and still have not translated into routine clinical practice— despite their potential to improve patient safety.63 There is evidence that interindividual variability in BP response to antihypertensive drugs has a polygenic component because the BP response shows a normal distribution.64 While most of the candidate gene studies of BP response have been small and exploratory, there is only 1 GWAS from Turner et al.65 who found that SNPs and haplotypes in lysozyme (LYZ) and YEATS domain-containing protein 4 (YEATS4) were associated with diastolic BP (DBP) response to hydrochlorothiazide. These findings are typical of GWAS studies identifying novel pathways. Risk prediction Another common claim associated with genetic studies is that they will lead to better risk prediction. In HTN this includes prediction of the odds for developing high BP but also prediction of target organ damage leading to HTN-associated morbidity and mortality. It has further been suggested that knowledge of an individual’s genetic make-up will facilitate “personalized medicine” including risk stratification and targeted preventative and therapeutic interventions.

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The complexity of BP regulation has been clearly demonstrated by the recent GWAS with their large number of genetic loci associated with BP traits. On a population basis the relatively small effect sizes of the genetic variants are relevant in face of the linear relationship between BP and target organ damage and the potential of small BP reductions leading to significant reductions in HTN-associated morbidity and mortality.1 It is, however, too early to apply these findings to individual risk prediction. An individual’s genetic fingerprint can be regarded as a biomarker and thereby competes with other established biomarkers of cardiovascular risk. A very thorough and staged translation into clinical applications as recommended for any other biomarker66 is required. With only a fraction of the genetic component of HTN being elucidated by GWAS and more information to follow from upcoming fine mapping studies, the full potential of genetics as biomarkers has not yet been unveiled. Again, we should not be discouraged by the small effect sizes of genetic variants that have been identified so far. Similarly, small differences in BP-lowering effects that were observed in large clinical trials of antihypertensive drugs do very well influence our treatment decisions in individual patients, and predicting a lifetime BP difference of few mm Hg by genetic tests would be in the same range. An interesting attempt to use the information from GWAS to calculate a genetic risk score has been undertaken recently by Ehret et al.23 Between the top and the bottom quintiles of the risk score a 4.6 mm Hg systolic and 3.0 mm Hg diastolic BP difference was detected, and the prevalence of HTN was 29% compared with 16% in the top and bottom deciles.23 The score was also associated with early and advanced target organ damage including left ventricular hypertrophy, stroke, and coronary artery disease; the absence of an association between this score with chronic kidney disease or markers of renal function has already been discussed above. The report by Ehret et al.23 is only a very first step to associate a risk score with risk or outcome with the most impressive data deriving from the comparison of extremes (quintiles and deciles), resembling a case-control study. Further prospective studies and studies into the incremental value of a genetic risk score over and above existing risk scores are necessary before such scores can be used in clinical practice. Current and Future Developments Phenotypic heterogeneity and gene-environment interactions There is growing recognition that environmental and behavioural changes interact with genetic predisposition to produce the recent increases in chronic diseases including essential HTN.67,68 The key implication of identifying gene-environment interactions is that they can suggest approaches for modifying the effects of deleterious genes by avoiding environmental exposure.68 The successful detection of gene-environment interactions is dependent on recruiting adequate sample sizes in prospective cohort studies. For genotypic and environmental prevalences of 10% and higher, 10,000 cases are needed to provide adequate power for interaction effects with a minimum detectable odds ratio ⬎2.68 The recent GWAS identifying a SNP in the 5’ end of UMOD gene is the first GWAS signal for BP that has clearly shown an environmental effect on the phenotype.24 We show a

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direct relationship between urinary uromodulin and urinary sodium excretion and dietary sodium intake, and this is supported by data from Torffvit et al.,69 who also showed that the urinary excretion of uromodulin in response to dietary sodium was exaggerated in salt-sensitive individuals. In male SpragueDawley rats an increase in dietary salt produced sustained increases in relative steady-state mRNA and protein levels of uromodulin in the kidney, suggesting that a sodium-induced increase in urinary uromodulin reflects increased intrarenal synthesis rather than increased urinary shedding.70 Our data showing lower urinary uromodulin excretion with the G-allele of rs13333226 appear to be more pronounced with low salt intake and genotype differences and blunted with high salt intake indicating a possible gene-environment interaction, where the effect of sodium load overwhelms the genotypephenotype association. This makes it easy for designing the next step in the functional characterization of gene-environment interaction which can take the form of salt intervention in a genotype-directed sample of untreated hypertensive patients. For discovering novel gene-environment interactions the only way is the expensive cohort study. We have also demonstrated in a large-scale candidate gene study that the association between genotype and phenotype is different if the definition of the phenotype varies. For example, signals that are associated with clinic BP may show no association with home BP readings and vice versa.36 Even more fundamental, signals derived from a study in men do not necessarily hold true in women, and the underlying biological differences cannot simply be adjusted for in statistical analysis.36,71 Similarly, associations between genetic variants and HTN have been found to be different in lean and obese subjects72 and again, the pathophysiological differences have to be dissected in detail rather than simply adjusting the analysis for crude measures such as body mass index.73 We therefore propose that future human genetic studies will certainly benefit from the advances in technology and the possibility to perform large-scale studies but will at the same time rely on much more accurate phenotyping and biological considerations to find relevant answers to relevant questions. The post-GWAS era Only a fraction of the phenotypic variability of BP can thus far be explained by the recently discovered common genetic polymorphisms from GWAS. In addition to the above-mentioned rare genetic variants a number of other mechanisms have been proposed to account for the “missing heritability” including regulation of transcription by noncoding RNAs, copy number variations (CNVs) and epigenetic effects. Among these, some large-scale data on CNVs are already available and will be discussed briefly. Structural variations such as CNVs (⬎1 kb) or smaller (⬍1 kb) insertion-deletion polymorphisms (indels) are hypothesized to account for some of the missing heritability. However there is very little evidence to support this, at least for common CNVs. The WTCCC study also investigated effects of common CNVs on 8 complex diseases, including HTN, but did not detect any associations for HTN.74 It is also apparent from this study that common CNVs tend to be well tagged by GWAS chips and thus it is unlikely that common CNVs contribute greatly to the missing BP and HTN heritability.74 Similar experiences were indeed made in a study of CNVs in myocardial infarction75 although for other phenotypes such as

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short stature,76 attention deficit disorder,77 and lean body mass,78 a role of CNVs to explain parts of the phenotypic variability has been demonstrated. Is It Time to Change Clinical Practice? There are over 1 billion people with high BP worldwide, and elucidation of genetic and environmental factors underlying HTN will have a major impact on the global burden of cardiovascular disease. However, any discoveries for use in clinical practice need to be evaluated with the same rigour as any new diagnostic test or drug. Gene variants can be considered as novel biomarkers and the current evidence for BP evaluated using a recent American Heart Association statement for evaluation of novel biomarkers advocates several phases of increasing stringency, analogous to the phases of development of a new drug.66 Thus, while there is early proof of concept data from GWAS, data are lacking on prospective validation, incremental value, clinical utility, clinical outcomes, and cost-effectiveness. It is likely that to fulfil all these criteria, GWAS discoveries need to be followed-up with functional dissection of pathways and prospective validation before they can be applied to general clinical practice. For personalized genetic tests, there are important social, legal, and ethical issues that need to be considered before they can be used in general clinical practice. The Food and Drug Administration is leading the way by issuing black box warnings for specific pharmacogenetic tests; it is likely that clinical practice in the future will change based on genetic data. Large-scale genetic studies of HTN continue to polarize researchers and clinicians.42,43 In part this is due to the high and sometimes unrealistic expectations associated with these studies, but also due to the enormous scale and financial implications thereof. It is very clear that the clinical implications of recent genetic discoveries is negligible at this stage, and the answer to the question, if the new information should result in a change of clinical practice, is currently “no.” Funding Sources Work in our group is supported by the European Commission’s 7th Framework Programmes EU-MASCARA, PRIORITY, and EURATRANS, and the Wellcome Trust Cardiovascular Functional Genomics Initiative (066780/Z/ 01/Z).

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Disclosures The authors have no conflicts of interest to disclose.

19. Newton-Cheh C, Johnson T, Gateva V, et al. Genome-wide association study identifies eight loci associated with blood pressure. Nat Genet 2009; 41:666-76.

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