Skip to main content

Advertisement

SpringerLink
Log in

Personalized Medicine and the Treatment of Hypertension

  • Blood Pressure Monitoring and Management (John Cockcroft, Section Editor)
  • Published:
Current Hypertension Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

The purpose of this review is to discuss the implications of personalized medicine for the treatment of hypertension, including resistant hypertension.

Recent Findings

We suggest a framework for the personalized treatment of hypertension based on the concept of a trade-off between simplicity and personalization. This framework is based on treatment strategies classified as low, medium, or high information burden personalization approaches. The extent to which a higher information burden is justified depends on the clinical scenario, particularly the ease with which the blood pressure can be controlled.

Summary

A one-size-fits-many treatment strategy for hypertension is efficacious for most people; however, a more personalized approach could be useful in patients with subtypes of hypertension that do not respond as expected to treatment. Clinicians seeing patients with unusual hypertension phenotypes should be familiar with emerging trends in personalized treatment of hypertension.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: •• Of major importance

  1. GBD 2015 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1659–724. https://doi.org/10.1016/s0140-6736(16)31679-8.

    Article  Google Scholar 

  2. Foreman KJ, Marquez N, Dolgert A, Fukutaki K, Fullman N, McGaughey M, et al. Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories. Lancet. 2018;392(10159):2052–90. https://doi.org/10.1016/s0140-6736(18)31694-5.

    Article  PubMed  PubMed Central  Google Scholar 

  3. NCD Risk Factor Collaboration. Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19.1 million participants. Lancet. 2017;389(10064):37–55. https://doi.org/10.1016/s0140-6736(16)31919-5.

    Article  Google Scholar 

  4. Forouzanfar MH, Liu P, Roth GA, Ng M, Biryukov S, Marczak L, et al. Global burden of hypertension and systolic blood pressure of at least 110 to 115 mm Hg, 1990-2015. JAMA. 2017;317(2):165–82. https://doi.org/10.1001/jama.2016.19043.

    Article  PubMed  Google Scholar 

  5. Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018;71(6):1269–324. https://doi.org/10.1161/hyp.0000000000000066.

    Article  CAS  PubMed  Google Scholar 

  6. Muntner P, Carey RM, Gidding S, Jones DW, Taler SJ, Wright JT Jr, et al. Potential US population impact of the 2017 ACC/AHA high blood pressure guideline. Circulation. 2018;137(2):109–18. https://doi.org/10.1161/circulationaha.117.032582.

    Article  PubMed  Google Scholar 

  7. Lip GY, Beevers M, Fau-beevers DG, Beevers DG. The ‘Birmingham Hypertension Square’ for the optimum choice of add-in drugs in the management of resistant hypertension. J Hum Hypertens. 1998;12(11):761–3. https://doi.org/10.1038/sj.jhh.1000688.

  8. Liu X, Byrd JB, Rodriguez CJ. Use of physician-recommended non-pharmacological strategies for hypertension control among hypertensive patients. J Clin Hypertens (Greenwich). 2018;20(3):518–27. https://doi.org/10.1111/jch.13203.

    Article  Google Scholar 

  9. Carey RM, Calhoun DA, Bakris GL, Brook RD, Daugherty SL, Dennison-Himmelfarb CR, et al. Resistant hypertension: detection, evaluation, and management: a scientific statement from the American Heart Association. Hypertension. 2018;72(5):e53–90. https://doi.org/10.1161/hyp.0000000000000084.

    Article  CAS  PubMed  Google Scholar 

  10. Daugherty SL, Powers JD, Magid DJ, Tavel HM, Masoudi FA, Margolis KL, et al. Incidence and prognosis of resistant hypertension in hypertensive patients. Circulation. 2012. https://doi.org/10.1161/circulationaha.111.068064.

  11. Byrd J, Turcu A, Auchus R. Primary aldosteronism: practical approach to diagnosis and management. Circulation. 2018;138(8):823–835. https://doi.org/10.1161/CIRCULATIONAHA.118.033597

  12. •• Williams B, MacDonald TM, Morant S, Webb DJ, Sever P, McInnes G, et al. Spironolactone versus placebo, bisoprolol, and doxazosin to determine the optimal treatment for drug-resistant hypertension (PATHWAY-2): a randomised, double-blind, crossover trial. Lancet. 2015. https://doi.org/10.1016/s0140-6736(15)00257-3 This paper defines the current state of the art with respect to treatment of resistant hypertension.

  13. Hwang AY, Dave C, Smith SM. Trends in antihypertensive medication use among US patients with resistant hypertension, 2008 to 2014. Hypertension. 2016;68(6):1349–54. https://doi.org/10.1161/hypertensionaha.116.08128.

    Article  PubMed  Google Scholar 

  14. Lonn EM, Bosch J, Lopez-Jaramillo P, Zhu J, Liu L, Pais P, et al. Blood-pressure lowering in intermediate-risk persons without cardiovascular disease. N Engl J Med. 2016;374(21):2009–20. https://doi.org/10.1056/NEJMoa1600175.

    Article  CAS  PubMed  Google Scholar 

  15. Schwalm JR, McCready T, Lamelas P, Musa H, Lopez-Jaramillo P, Yusoff K, et al. Rationale and design of a cluster randomized trial of a multifaceted intervention in people with hypertension: the Heart Outcomes Prevention and Evaluation 4 (HOPE-4) Study. Am Heart J. 2018;203:57–66. https://doi.org/10.1016/j.ahj.2018.06.004.

    Article  PubMed  Google Scholar 

  16. Rydberg DM, Mejyr S, Loikas D, Schenck-Gustafsson K, von Euler M, Malmstrom RE. Sex differences in spontaneous reports on adverse drug events for common antihypertensive drugs. Eur J Clin Pharmacol. 2018;74(9):1165–73. https://doi.org/10.1007/s00228-018-2480-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Brewster LM, Seedat YK. Why do hypertensive patients of African ancestry respond better to calcium blockers and diuretics than to ACE inhibitors and beta-adrenergic blockers? A systematic review. BMC Med. 2013;11:141. https://doi.org/10.1186/1741-7015-11-141.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Krieger EM, Drager LF, Giorgi DMA, Pereira AC, Barreto-Filho JAS, Nogueira AR, et al. Spironolactone versus clonidine as a fourth-drug therapy for resistant hypertension: the ReHOT Randomized Study (Resistant Hypertension Optimal Treatment). Hypertension. 2018;71(4):681–90. https://doi.org/10.1161/hypertensionaha.117.10662.

    Article  CAS  PubMed  Google Scholar 

  19. •• Webster R, Salam A, de Silva HA, Selak V, Stepien S, Rajapakse S, et al. Fixed low-dose triple combination antihypertensive medication vs usual care for blood pressure control in patients with mild to moderate hypertension in Sri Lanka: a randomized clinical trial. JAMA. 2018;320(6):566–79. https://doi.org/10.1001/jama.2018.10359 This paper shows that in some contexts, little personalization is required to achieve a benefit for patients.

    Article  CAS  PubMed  Google Scholar 

  20. Byrd JB. Personalized medicine and treatment approaches in hypertension: current perspectives. Integr Blood Press Control. 2016;9:59–67. https://doi.org/10.2147/ibpc.s74320.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Laragh JH, Sealey JE. The plasma renin test reveals the contribution of body sodium-volume content (V) and renin-angiotensin (R) vasoconstriction to long-term blood pressure. Am J Hypertens. 2011;24(11):1164–80. https://doi.org/10.1038/ajh.2011.171.

    Article  CAS  PubMed  Google Scholar 

  22. Funder JW, Carey RM, Mantero F, Murad MH, Reincke M, Shibata H et al. The management of primary aldosteronism: case detection, diagnosis, and treatment: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2016:jc20154061. https://doi.org/10.1210/jc.2015-4061.

  23. •• Qi Y, Wang X, Rose KL, MacDonald WH, Zhang B, Schey KL, et al. Activation of the endogenous renin-angiotensin-aldosterone system or aldosterone administration increases urinary exosomal sodium channel excretion. J Am Soc Nephrol. 2016;27(2):646–56. https://doi.org/10.1681/asn.2014111137 This paper suggests the possibility of a mass spectrometry-based approach to predicting response to mineralocorticoid receptor antagonists.

    Article  CAS  PubMed  Google Scholar 

  24. •• Bazzell BG, Rainey WE, Auchus RJ, Zocco D, Bruttini M, Hummel SL, et al. Human urinary mRNA as a biomarker of cardiovascular disease. Circ Genom Precis Med. 2018;11(9):e002213. https://doi.org/10.1161/circgen.118.002213 This paper suggests the possibility of a pharmacotranscriptomic approach to predicting response to mineralocorticoid receptor antagonists.

    Article  CAS  PubMed  Google Scholar 

  25. Bhatt DL, Kandzari DE, O’Neill WW, D’Agostino R, Flack JM, Katzen BT, et al. A controlled trial of renal denervation for resistant hypertension. N Engl J Med. 2014;370(15):1393–401. https://doi.org/10.1056/NEJMoa1402670.

    Article  CAS  PubMed  Google Scholar 

  26. Townsend RR, Mahfoud F, Kandzari DE, Kario K, Pocock S, Weber MA, et al. Catheter-based renal denervation in patients with uncontrolled hypertension in the absence of antihypertensive medications (SPYRAL HTN-OFF MED): a randomised, sham-controlled, proof-of-concept trial. Lancet. 2017;390(10108):2160–70. https://doi.org/10.1016/s0140-6736(17)32281-x.

    Article  PubMed  Google Scholar 

  27. Kandzari DE, Bohm M, Mahfoud F, Townsend RR, Weber MA, Pocock S, et al. Effect of renal denervation on blood pressure in the presence of antihypertensive drugs: 6-month efficacy and safety results from the SPYRAL HTN-ON MED proof-of-concept randomised trial. Lancet. 2018;391(10137):2346–55. https://doi.org/10.1016/s0140-6736(18)30951-6.

    Article  PubMed  Google Scholar 

  28. Azizi M, Schmieder RE, Mahfoud F, Weber MA, Daemen J, Davies J, et al. Endovascular ultrasound renal denervation to treat hypertension (RADIANCE-HTN SOLO): a multicentre, international, single-blind, randomised, sham-controlled trial. Lancet. 2018;391(10137):2335–45. https://doi.org/10.1016/s0140-6736(18)31082-1.

    Article  PubMed  Google Scholar 

  29. Rimoldi SF, Messerli FH, Bangalore S, Scherrer U. Resistant hypertension: what the cardiologist needs to know. Eur Heart J. 2015;36(40):2686–95. https://doi.org/10.1093/eurheartj/ehv392.

    Article  PubMed  Google Scholar 

  30. •• Laffin LJ, Besser SA, Alenghat FJ. A data-zone scoring system to assess the generalizability of clinical trial results to individual patients. Eur J Prev Cardiol. 2018:2047487318815967. https://doi.org/10.1177/2047487318815967 This is an innovative approach to determine how closely a patient resembles patients enrolled in the SPRINT trial.

  31. Wright JT Jr, Williamson JD, Whelton PK, Snyder JK, Sink KM, Rocco MV, et al. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med. 2015;373(22):2103–16. https://doi.org/10.1056/NEJMoa1511939.

    Article  CAS  PubMed  Google Scholar 

  32. Byrd JB, Greene CS. Data-sharing models. N Engl J Med. 2017;376(23):2305. https://doi.org/10.1056/NEJMc1705477.

    Article  PubMed  Google Scholar 

  33. Zheutlin AR, Byrd JB. Opening opportunities with open data. JACC Heart Fail. 2018;6(6):530–2. https://doi.org/10.1016/j.jchf.2017.12.019.

    Article  PubMed  Google Scholar 

  34. •• Waljee AK, Sauder K, Patel A, Segar S, Liu B, Zhang Y, et al. Machine learning algorithms for objective remission and clinical outcomes with thiopurines. J Crohns Colitis. 2017;11(7):801–10. https://doi.org/10.1093/ecco-jcc/jjx014 This paper exemplifies a new generation of research focused on predicting drug response using machine learning models trained on commonly acquired laboratory data.

    Article  PubMed  PubMed Central  Google Scholar 

  35. McDonough CW, Magvanjav O, Sa ACC, El Rouby NM, Dave C, Deitchman AN, et al. Genetic variants influencing plasma renin activity in hypertensive patients from the PEAR study (Pharmacogenomic Evaluation of Antihypertensive Responses). Circ Genom Precis Med. 2018;11(4):e001854. https://doi.org/10.1161/circgen.117.001854.

    Article  CAS  PubMed  Google Scholar 

  36. •• Sa ACC, Webb A, Gong Y, McDonough CW, Shahin MH, Datta S, et al. Blood pressure signature genes and blood pressure response to thiazide diuretics: results from the PEAR and PEAR-2 studies. BMC Med Genet. 2018;11(1):55. https://doi.org/10.1186/s12920-018-0370-x Reports the results of investigations into the pharmacogenetics of thiazide diuretics.

    Article  CAS  Google Scholar 

  37. Cooper-DeHoff RM, Johnson JA. Hypertension pharmacogenomics: in search of personalized treatment approaches. Nat Rev Nephrol. 2016;12(2):110–22. https://doi.org/10.1038/nrneph.2015.176.

    Article  CAS  PubMed  Google Scholar 

  38. Natarajan P, Young R, Stitziel NO, Padmanabhan S, Baber U, Mehran R, et al. Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting. Circulation. 2017;135(22):2091–101. https://doi.org/10.1161/circulationaha.116.024436.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Knowles JW, Ashley EA. Cardiovascular disease: the rise of the genetic risk score. PLoS Med. 2018;15(3):e1002546. https://doi.org/10.1371/journal.pmed.1002546.

    Article  PubMed  PubMed Central  Google Scholar 

  40. •• Basu S, Yudkin JS, Sussman JB, Millett C, Hayward RA. Alternative strategies to achieve cardiovascular mortality goals in China and India: a microsimulation of target- versus risk-based blood pressure treatment. Circulation. 2016;133(9):840–8. https://doi.org/10.1161/circulationaha.115.019985 Models a risk-based approach for determining individuals’ blood pressure goals, constrasting with a treat-to-target approach.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Karmali KN, Lloyd-Jones DM, van der Leeuw J, Goff DC Jr, Yusuf S, Zanchetti A, et al. Blood pressure-lowering treatment strategies based on cardiovascular risk versus blood pressure: a meta-analysis of individual participant data. PLoS Med. 2018;15(3):e1002538. https://doi.org/10.1371/journal.pmed.1002538.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Araujo A, Julious S, Senn S. Understanding variation in sets of N-of-1 trials. PLoS One. 2016;11(12):e0167167. https://doi.org/10.1371/journal.pone.0167167.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors are appreciative of engaging discussions on the topic with Dr. Martin MacKinnon, Department of Nephrology and his Complicated Hypertension Clinic nurse, Shelley Nairn, both of the Saint John Regional Hospital, and Translational Scientist, Dr. Keith Brunt. SM appreciates the professional and financial support provided by the New Brunswick Health Research Foundation (NBHRF) via grants to Dr. Keith R. Brunt and Dr. Sohrab Lutchmedial.

Author information

Authors and Affiliations

  1. CardioVascular Research New Brunswick, Saint John Regional Hospital, HHN, Saint John, Canada

    Sarah Melville

  2. IMPART Investigator Team Canada, Saint John, New Brunswick, Canada

    Sarah Melville

  3. Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan Medical School, 5570C MSRB II, 1150 West Medical Center Drive, SPC 5678, Ann Arbor, MI, 48109-5678, USA

    James Brian Byrd

Authors
  1. Sarah Melville
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. James Brian Byrd
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James Brian Byrd.

Ethics declarations

Conflict of Interest

SM has no conflict of interest to declare and is supported via funding from the New Brunswick Health Research Foundation (NBHRF) (Operating Grant: Health Research Value Demonstration Initiative [HRVDI]) provided directly to professional supervisors, Keith R. Brunt, PhD (IMPART investigator team Canada) and Sohrab Lutchmedial, MD, FRCP(C) (CardioVascular Research New Brunswick, Saint John Regional Hospital, Horizon Health Network). JBB is funded by the National Institutes of Health award 5K23HL128909.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Blood Pressure Monitoring and Management

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Melville, S., Byrd, J.B. Personalized Medicine and the Treatment of Hypertension. Curr Hypertens Rep 21, 13 (2019). https://doi.org/10.1007/s11906-019-0921-3

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s11906-019-0921-3

Keywords

Search

Navigation