Review Article | Published:

Hypertension pharmacogenomics: in search of personalized treatment approaches

Nature Reviews Nephrology volume 12, pages 110122 (2016) | Download Citation

Abstract

Cardiovascular and renal diseases are associated with many risk factors, of which hypertension is one of the most prevalent. Worldwide, blood pressure control is only achieved in 50% of those treated for hypertension, despite the availability of a considerable number of antihypertensive drugs from different pharmacological classes. Although many reasons exist for poor blood pressure control, a likely contributor is the inability to predict to which antihypertensive drug an individual is most likely to respond. Hypertension pharmacogenomics and other 'omics' technologies have the potential to identify genetic signals that are predictive of response or adverse outcome to particular drugs, and guide selection of hypertension treatment for a given individual. Continued research in this field will enhance our understanding of how to maximally deploy the various antihypertensive drug classes to optimize blood pressure response at the individual level. This Review summarizes the available literature on the most convincing genetic signals associated with antihypertensive drug responses and adverse cardiovascular outcomes. Future research in this area will be facilitated by enhancing collaboration between research groups through consortia such as the International Consortium for Antihypertensives Pharmacogenomics Studies, with the goal of translating replicated findings into clinical implementation.

Key points

  • Hypertension is an important, modifiable risk factor for cardiovascular and kidney disease

  • Rates of blood pressure control are substantially below the desired levels globally, with many factors contributing to poor blood pressure control

  • Pharmacogenomics and other 'omics' approaches could help to identify useful biomarkers for a more personalized or precision approach to antihypertensive treatment strategies

  • Validating and replicating antihypertensive pharmacogenomics signals will require large sample sizes and will probably not yield a single signal with a large effect size, but rather multiple signals with small effect sizes

  • As technology continues to evolve and genetic and other 'omics' data become available from collaborative studies, identification of biomarkers of blood pressure response might be possible

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References

  1. 1.

    et al. Heart disease and stroke statistics — 2015 update: a report from the American Heart Association. Circulation 131, e29–e322 (2015).

  2. 2.

    , & US trends in prevalence, awareness, treatment, and control of hypertension, 1988–2008. JAMA 303, 2043–2050 (2010).

  3. 3.

    et al. Global burden of hypertension: analysis of worldwide data. Lancet 365, 217–223 (2005).

  4. 4.

    et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380, 2224–2260 (2012).

  5. 5.

    WHO Press Release. Adherence to long-term therapies: evidence for action .

  6. 6.

    et al. Effects of blood pressure reduction in mild hypertension: a systematic review and meta-analysis. Ann. Intern. Med. 162, 184–191 (2014).

  7. 7.

    et al. Blood pressure-lowering treatment based on cardiovascular risk: a meta-analysis of individual patient data. Lancet 384, 591–598 (2014).

  8. 8.

    Blood Pressure Lowering Treatment Trialists' Collaboration. Effects of ACE inhibitors, calcium antagonists, and other blood-pressure-lowering drugs: results of prospectively designed overviews of randomised trials. Lancet 356, 1955–1964 (2000).

  9. 9.

    SHEP Cooperative Research Group. Prevention of stroke by antihypertensive drug treatment in older persons with isolated systolic hypertension. JAMA 265, 3255–3264 (1991).

  10. 10.

    et al. Treatment of hypertension in patients 80 years of age or older. N. Engl. J. Med. 358, 1887–1898 (2008).

  11. 11.

    , , , & Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet 360, 1903–1913 (2002).

  12. 12.

    , , , & Elevated blood pressure and risk of end-stage renal disease in subjects without baseline kidney disease. Arch. Intern. Med. 165, 923–928 (2005).

  13. 13.

    , & Global burden of blood-pressure-related disease, 2001. Lancet 371, 1513–1518 (2008).

  14. 14.

    , , & Trends in antihypertensive medication use and blood pressure control among United States adults with hypertension: the National Health And Nutrition Examination Survey, 2001 to 2010. Circulation 126, 2105–2114 (2012).

  15. 15.

    & Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988–2000. JAMA 290, 199–206 (2003).

  16. 16.

    et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 311, 507–520 (2014).

  17. 17.

    et al. The seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. JAMA 289, 2560–2572 (2003).

  18. 18.

    et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the task force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur. Heart J. 34, 2159–2219 (2013).

  19. 19.

    American Diabetes Association. Standards of medical care in diabetes — 2014. Diabetes Care 37, S14–S80 (2014).

  20. 20.

    et al. Single-drug therapy for hypertension in men — a comparison of six antihypertensive agents with placebo. N. Engl. J. Med. 328, 914–921 (1993).

  21. 21.

    & Choice of first antihypertensive: simple as ABCD? Am. J. Hypertens. 20, 923–927 (2007).

  22. 22.

    et al. Hydrochlorothiazide and atenolol combination antihypertensive therapy: effects of drug initiation order. Clin. Pharmacol. Ther. 86, 533–539 (2009).

  23. 23.

    , , , & The role of plasma renin activity, age, and race in selecting effective initial drug therapy for hypertension. Am. J. Hypertens. 26, 957–964 (2013).

  24. 24.

    et al. Renin, angiotensin and aldosterone system in pathogenesis and management of hypertensive vascular disease. Am. J. Med. 52, 633–652 (1972).

  25. 25.

    et al. Plasma renin activity predicts blood pressure responses to β-blocker and thiazide diuretic as monotherapy and add-on therapy for hypertension. Am. J. Hypertens. 23, 1014–1022 (2010).

  26. 26.

    & CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenetics Research Network. PharmGKB

  27. 27.

    et al. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. Clin. Pharmacol. Ther. 94, 317–323 (2013).

  28. 28.

    et al. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C9 and VKORC1 genotypes and warfarin dosing. Clin. Pharmacol. Ther. 90, 625–629 (2011).

  29. 29.

    et al. The Clinical Pharmacogenetics Implementation Consortium guideline for SLCO1B1 and simvastatin-induced myopathy: 2014 update. Clin. Pharmacol. Ther. 96, 423–428 (2014).

  30. 30.

    et al. Emerging roles for pharmacists in clinical implementation of pharmacogenomics. Pharmacotherapy 34, 1102–1112 (2014).

  31. 31.

    et al. Clinical pharmacogenetics implementation: approaches, successes, and challenges. Am. J. Med. Genet. C Semin. Med. Genet. 166, 56–67 (2014).

  32. 32.

    & Genetics of resistant hypertension: a novel pharmacogenomics phenotype. Curr. Hypertens. Rep. 17, 583 (2015).

  33. 33.

    & NEDD4-2 and salt-sensitive hypertension. Curr. Opin. Nephrol. Hypertens. 24, 111–116 (2015).

  34. 34.

    et al. Renal tubular NEDD4-2 deficiency causes NCC-mediated salt-dependent hypertension. J. Clin. Invest. 123, 657–665 (2013).

  35. 35.

    et al. Association of NEDD4L ubiquitin ligase with essential hypertension. Hypertension 46, 488–491 (2005).

  36. 36.

    et al. A functional variant of NEDD4L is associated with hypertension, antihypertensive response, and orthostatic hypotension. Hypertension 54, 796–801 (2009).

  37. 37.

    , , , & Genetic variation in NEDD4L, an epithelial sodium channel regulator, is associated with cardiovascular disease and cardiovascular death. J. Hypertens. 32, 294–299 (2014).

  38. 38.

    , , & Polymorphism in NEDD4L is associated with increased salt sensitivity, reduced levels of P-renin and increased levels of Nt-proANP. PLoS ONE 2, e432 (2007).

  39. 39.

    et al. A functional variant of the NEDD4L gene is associated with beneficial treatment response with β-blockers and diuretics in hypertensive patients. J. Hypertens. 29, 388–395 (2011).

  40. 40.

    et al. Association of variants in NEDD4L with blood pressure response and adverse cardiovascular outcomes in hypertensive patients treated with thiazide diuretics. J. Hypertens. 31, 698–704 (2013).

  41. 41.

    & Cardiovascular pharmacogenomics of adrenergic receptor signaling: clinical implications and future directions. Clin. Pharmacol. Ther. 89, 366–378 (2011).

  42. 42.

    & S49G and R389G polymorphisms of the β1-adrenergic receptor influence signaling via the cAMP-PKA and ERK pathways. Physiol. Genom. 45, 1186–1192 (2013).

  43. 43.

    et al. Association of hypertension drug target genes with blood pressure and hypertension in 86,588 individuals. Hypertension 57, 903–910 (2011).

  44. 44.

    et al. Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure. Nat. Genet. 43, 1005–1011 (2011).

  45. 45.

    et al. Loci influencing blood pressure identified using a cardiovascular gene-centric array. Hum. Mol. Genet. 22, 1663–1678 (2013).

  46. 46.

    et al. β1-adrenergic receptor polymorphisms and antihypertensive response to metoprolol. Clin. Pharmacol. Ther. 74, 44–52 (2003).

  47. 47.

    et al. β1-adrenergic receptor polymorphisms influence the response to metoprolol monotherapy in patients with essential hypertension. Clin. Pharmacol. Ther. 80, 23–32 (2006).

  48. 48.

    et al. Associations between ADRB1 and CYP2D6 gene polymorphisms and the response to β-blocker therapy in hypertension. J. Int. Med. Res. 43, 424–434 (2015).

  49. 49.

    et al. Association of common polymorphisms in β1-adrenergic receptor with antihypertensive response to carvedilol. J. Cardiovasc. Pharmacol. 64, 306–309 (2014).

  50. 50.

    , , , & The gain-of-function G389R variant of the β1-adrenoceptor does not influence blood pressure or heart rate response to β-blockade in hypertensive subjects. Clin. Sci. (Lond.) 99, 233–238 (2000).

  51. 51.

    et al. β1-adrenergic receptor gene polymorphisms and response to β 1-adrenergic receptor blockade in patients with essential hypertension. Clin. Cardiol. 27, 347–350 (2004).

  52. 52.

    et al. β-adrenergic receptor gene polymorphisms and β-blocker treatment outcomes in hypertension. Clin. Pharmacol. Ther. 84, 715–721 (2008).

  53. 53.

    et al. β1- and β2-adrenergic receptor gene variation, β-blocker use and risk of myocardial infarction and stroke. Am. J. Hypertens. 21, 290–296 (2008).

  54. 54.

    et al. Prevention of atrial fibrillation by bucindolol is dependent on the β1389 Arg/Gly adrenergic receptor polymorphism. JACC Heart Fail. 1, 338–344 (2013).

  55. 55.

    , , , & Adrenergic receptor polymorphisms and prevention of ventricular arrhythmias with bucindolol in patients with chronic heart failure. Circ. Arrhythm. Electrophysiol. 6, 137–143 (2013).

  56. 56.

    et al. A polymorphism within a conserved β1-adrenergic receptor motif alters cardiac function and β-blocker response in human heart failure. Proc. Natl Acad. Sci. USA 103, 11288–11293 (2006).

  57. 57.

    et al. Genomic association analysis suggests chromosome 12 locus influencing antihypertensive response to thiazide diuretic. Hypertension 52, 359–365 (2008).

  58. 58.

    et al. Association of chromosome 12 locus with antihypertensive response to hydrochlorothiazide may involve differential YEATS4 expression. Pharmacogenom. J. 13, 257–263 (2013).

  59. 59.

    et al. Genomic association analysis of common variants influencing antihypertensive response to hydrochlorothiazide. Hypertension 62, 391–397 (2013).

  60. 60.

    et al. TET2 and CSMD1 genes affect SBP response to hydrochlorothiazide in never-treated essential hypertensives. J. Hypertens. 33, 1301–1309 (2015).

  61. 61.

    , , , & Association between a polymorphism in the G protein β3 subunit gene and lower renin and elevated diastolic blood pressure levels. Hypertension 32, 510–513 (1998).

  62. 62.

    , , & C825T polymorphism of the G protein β3-subunit and antihypertensive response to a thiazide diuretic. Hypertension 37, 739–743 (2001).

  63. 63.

    et al. Interactions between five candidate genes and antihypertensive drug therapy on blood pressure. Pharmacogenom. J. 6, 22–26 (2006).

  64. 64.

    et al. The thiazide-sensitive Na+-Cl cotransporter gene, C1784T, and adrenergic receptor-β3 gene, T727C, may be gene polymorphisms susceptible to the antihypertensive effect of thiazide diuretics. Hypertens. Res. 27, 821–833 (2004).

  65. 65.

    et al. An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J. Clin. Invest. 86, 1343–1346 (1990).

  66. 66.

    et al. Effects of ACE and ADD1 gene polymorphisms on blood pressure response to hydrochlorothiazide: a meta-analysis. Int. J. Clin. Pharmacol. Ther. 51, 718–724 (2013).

  67. 67.

    et al. Hydrochlorothiazide efficacy and polymorphisms in ACE, ADD1 and GNB3 in healthy, male volunteers. Eur. J. Clin. Pharmacol. 62, 195–201 (2006).

  68. 68.

    et al. Polymorphisms of α-adducin and salt sensitivity in patients with essential hypertension. Lancet 349, 1353–1357 (1997).

  69. 69.

    et al. α-adducin 460Trp allele is associated with erythrocyte Na transport rate in North Sardinian primary hypertensives. Hypertension 39, 357–362 (2002).

  70. 70.

    et al. The role of α-adducin polymorphism in blood pressure and sodium handling regulation may not be excluded by a negative association study. Hypertension 34, 649–654 (1999).

  71. 71.

    et al. ACE and α-adducin polymorphism as markers of individual response to diuretic therapy. Hypertension 41, 398–403 (2003).

  72. 72.

    , , & Effects of endothelial nitric oxide synthase, α-adducin, and other candidate gene polymorphisms on blood pressure response to hydrochlorothiazide. Am. J. Hypertens. 16, 834–839 (2003).

  73. 73.

    et al. The influence of the α-adducin G460W polymorphism and angiotensinogen M235T polymorphism on antihypertensive medication and blood pressure. Eur. J. Hum. Genet. 14, 860–866 (2006).

  74. 74.

    et al. G-protein-coupled receptor kinase 4 polymorphisms and blood pressure response to metoprolol among African Americans: sex-specificity and interactions. Am. J. Hypertens. 22, 332–338 (2009).

  75. 75.

    et al. G protein receptor kinase 4 polymorphisms: β-blocker pharmacogenetics and treatment-related outcomes in hypertension. Hypertension 60, 957–964 (2012).

  76. 76.

    et al. G-protein receptor kinase 4 polymorphism and response to antihypertensive therapy. Clin. Chem. 60, 1543–1548 (2014).

  77. 77.

    et al. Common variants of the G protein-coupled receptor type 4 are associated with human essential hypertension and predict the blood pressure response to angiotensin receptor blockade. Pharmacogenom. J. .

  78. 78.

    et al. Pharmacogenomics of hypertension: a genome-wide, placebo-controlled cross-over study, using four classes of antihypertensive drugs. J. Am. Heart Assoc. 4, e001521 (2015).

  79. 79.

    et al. A core promoter variant of angiotensinogen gene and interindividual variation in response to angiotensin-converting enzyme inhibitors. J. Renin Angiotensin Aldosterone Syst. 15, 540–546 (2014).

  80. 80.

    et al. Angiotensinogen gene polymorphisms: relationship to blood pressure response to antihypertensive treatment: results from the Swedish Irbesartan Left Ventricular Hypertrophy Investigation vs Atenolol (SILVHIA) trial. Am. J. Hypertens. 17, 8–13 (2004).

  81. 81.

    et al. Molecular basis of human hypertension: role of angiotensinogen. Cell 71, 169–180 (1992).

  82. 82.

    , , , & Association of angiotensinogen (M235T) gene polymorphism with blood pressure lowering response to angiotensin converting enzyme inhibitor (Enalapril). J. Pharm. Pharm. Sci. 15, 399–406 (2012).

  83. 83.

    et al. Contribution of angiotensin I converting enzyme gene polymorphism and angiotensinogen gene polymorphism to blood pressure regulation in essential hypertension. Am. J. Hypertens. 11, 174–183 (1998).

  84. 84.

    et al. Common genetic variations of the renin–angiotensin–aldosterone system and response to acute angiotensin I-converting enzyme inhibition in essential hypertension. J. Hypertens. 28, 771–779 (2010).

  85. 85.

    et al. Pharmacogenomic association of nonsynonymous SNPs in SIGLEC12, A1BG, and the selectin region and cardiovascular outcomes. Hypertension 62, 48–54 (2013).

  86. 86.

    , , , & Follow-up of a major linkage peak on chromosome 1 reveals suggestive QTLs associated with essential hypertension: GenNet study. Eur. J. Hum. Genet. 17, 1650–1657 (2009).

  87. 87.

    et al. KCNMB1 genotype influences response to verapamil SR and adverse outcomes in the INternational VErapamil SR/Trandolapril STudy (INVEST). Pharmacogenet. Genom. 17, 719–729 (2007).

  88. 88.

    et al. Liver X receptor α gene polymorphisms and variable cardiovascular outcomes in patients treated with antihypertensive therapy: results from the INVEST-GENES study. Pharmacogenet. Genom. 21, 333–340 (2011).

  89. 89.

    et al. Pharmacogenetic associations of MMP9 and MMP12 variants with cardiovascular disease in patients with hypertension. PLoS ONE 6, e23609 (2011).

  90. 90.

    et al. Pharmacogenetic association of NOS3 variants with cardiovascular disease in patients with hypertension: the GenHAT study. PLoS ONE 7, e34217 (2012).

  91. 91.

    et al. Pharmacogenetic association of the NPPA T2238C genetic variant with cardiovascular disease outcomes in patients with hypertension. JAMA 299, 296–307 (2008).

  92. 92.

    et al. Gene panels to help identify subgroups at high and low risk of coronary heart disease among those randomized to antihypertensive treatment: the GenHAT study. Pharmacogenet. Genom. 22, 355–366 (2012).

  93. 93.

    et al. Interaction between polymorphisms in the renin–angiotensin-system and angiotensin-converting enzyme inhibitor or β-blocker use and the risk of myocardial infarction and stroke. Pharmacogenom. J. 8, 400–407 (2008).

  94. 94.

    et al. Genetic variation in the renin–angiotensin system, use of renin–angiotensin system inhibitors and the risk of myocardial infarction. J. Renin Angiotensin Aldosterone Syst. 12, 208–214 (2011).

  95. 95.

    et al. Diuretic therapy, the α-adducin gene variant, and the risk of myocardial infarction or stroke in persons with treated hypertension. JAMA 287, 1680–1689 (2002).

  96. 96.

    et al. Antihypertensive therapy, the α-adducin polymorphism, and cardiovascular disease in high-risk hypertensive persons: the Genetics of Hypertension-Associated Treatment Study. Pharmacogenom. J. 7, 112–122 (2007).

  97. 97.

    et al. α-adducin polymorphism associated with increased risk of adverse cardiovascular outcomes: results from GENEtic Substudy of the INternational VErapamil SR-trandolapril STudy (INVEST-GENES). Am. Heart J. 156, 397–404 (2008).

  98. 98.

    et al. Effect of ACE insertion/deletion and 12 other polymorphisms on clinical outcomes and response to treatment in the LIFE study. Pharmacogenet. Genom. 20, 77–85 (2010).

  99. 99.

    et al. Interaction between the Gly460Trp α-adducin gene variant and diuretics on the risk of myocardial infarction. J. Hypertens. 27, 61–68 (2009).

  100. 100.

    et al. Pharmacometabolomics reveals racial differences in response to atenolol treatment. PLoS ONE 8, e57639 (2013).

  101. 101.

    et al. Is diabetes mellitus-linked amino acid signature associated with β-blocker-induced impaired fasting glucose? Circ. Cardiovasc. Genet. 7, 199–205 (2014).

  102. 102.

    King's College London. Ancestry and biological Informative Markers for stratification of HYpertension: the AIM HY study. Research Councils UK , (2015).

  103. 103.

    , , & mRNA transcript diversity creates new opportunities for pharmacological intervention. Mol. Pharmacol. 81, 620–630 (2012).

  104. 104.

    et al. Treatment of hypertension in patients with coronary artery disease: a scientific statement from the American Heart Association, American College of Cardiology, and American Society of Hypertension. Circulation 60, 753–764 (2015).

  105. 105.

    et al. Estimation of the warfarin dose with clinical and pharmacogenetic data. N. Engl. J. Med. 360, 753–764 (2009).

  106. 106.

    et al. Assessment of the value of a genetic risk score in improving the estimation of coronary risk. Atherosclerosis 222, 456–463 (2012).

  107. 107.

    et al. A blood pressure genetic risk score is a significant predictor of incident cardiovascular events in 32,669 individuals. Hypertension 61, 987–994 (2013).

  108. 108.

    et al. Multilocus genetic risk scores for coronary heart disease prediction. Arterioscler. Thromb. Vasc. Biol. 33, 2267–2272 (2013).

  109. 109.

    et al. Multilocus genetic risk score associates with ischemic stroke in case-control and prospective cohort studies. Stroke 45, 394–402 (2014).

  110. 110.

    et al. Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke. Stroke 45, 2856–2862 (2014).

  111. 111.

    & Therapy: PCSK9 inhibitors for treating familial hypercholesterolaemia. Nat. Rev. Endocrinol. 11, 8–9 (2015).

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Acknowledgements

R.M.C.-D. has received grant funding from NIH, NIGMS U01 GM074492 and U01 GM092586; and NIH, NHGRI U01 HG007269. J.A.J. has received grant funding from NIH, NIGMS U01 GM074492; NIH, NHGRI U01 HG007269, and NIH, NINDS R01 NS073346 and FDA U01 FD005235.

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  1. Department of Pharmacotherapy and Translational Research and Division of Cardiovascular Medicine, Colleges of Pharmacy and Medicine, University of Florida, PO Box 100484, 1600 SW Archer Road, Gainesville, Florida 32610–0484, USA.

    • Rhonda M. Cooper-DeHoff
    •  & Julie A. Johnson

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Both authors researched data for the article, made substantial contributions to planning the review, shared in the writing of the article and reviewed or edited the manuscript before and after submission.

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The authors declare no competing financial interests.

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Correspondence to Julie A. Johnson.

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https://doi.org/10.1038/nrneph.2015.176

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