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Use of Biomarkers in the Evaluation and Treatment of Hypertensive Patients

  • Resistant Hypertension (E Pimenta, Section Editor)
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Abstract

The current definition of hypertension is based on blood pressure values, and blood pressure also drives treatment decisions, is the most important treatment monitoring tool and helps estimating risk of hypertension-related organ damage. In an era of precision medicine, additional biomarkers are needed in the diagnosis and management of patients with hypertension. In this review, we outline the areas in which functional, imaging and circulating biomarkers could help in a more individualised definition of hypertension and associated risk. We will cover biomarkers for diagnosis; of pathophysiology and prediction of hypertension; response to treatment, organ damage; and to monitor treatment. A clear focus is on the vasculature, the heart and the kidneys, whereas we see a need to further develop biomarkers of cerebral function in order to diagnose cognition deficits and monitor changes in cognition in the future to support addressing the growing burden of hypertension-associated vascular dementia.

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References

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

  1. Lawes CM, Vander Hoorn S, Rodgers A, International Society of H. Global burden of blood-pressure-related disease, 2001. Lancet. 2008;371:1513–8.

    Article  PubMed  Google Scholar 

  2. Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005;365:217–23.

    Article  PubMed  Google Scholar 

  3. Chow CK, Teo KK, Rangarajan S, Islam S, Gupta R, Avezum A, et al. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA. 2013;310:959–68.

    Article  CAS  PubMed  Google Scholar 

  4. Wang TJ, Vasan RS. Epidemiology of uncontrolled hypertension in the United States. Circulation. 2005;112:1651–62.

    Article  PubMed  Google Scholar 

  5. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89–95. This NIH Working Group statement provides the most commonly used definitions of biomarkers for research and clinical practice.

    Article  Google Scholar 

  6. James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, 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. 2014;311:507–20.

    Article  CAS  PubMed  Google Scholar 

  7. Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Bohm M, 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). J Hypertens. 2013;31:1281–357.

    Article  CAS  PubMed  Google Scholar 

  8. Shimamoto K, Ando K, Fujita T, Hasebe N, Higaki J, Horiuchi M, et al. The Japanese society of hypertension guidelines for the management of hypertension (JSH 2014). Hypertens Res. 2014;37:253–390.

    Article  PubMed  CAS  Google Scholar 

  9. Mancia G, Verdecchia P. Clinical value of ambulatory blood pressure: evidence and limits. Circ Res. 2015;116:1034–45.

    Article  CAS  PubMed  Google Scholar 

  10. Rothwell PM, Howard SC, Dolan E, O’Brien E, Dobson JE, Dahlof B, et al. Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet. 2010;375:895–905.

    Article  PubMed  Google Scholar 

  11. Webb AJ, Fischer U, Mehta Z, Rothwell PM. Effects of antihypertensive-drug class on interindividual variation in blood pressure and risk of stroke: a systematic review and meta-analysis. Lancet. 2010;375:906–15.

    Article  CAS  PubMed  Google Scholar 

  12. Neisius U, Bilo G, Taurino C, McClure JD, Schneider MP, Kawecka-Jaszcz K, et al. Association of central and peripheral pulse pressure with intermediate cardiovascular phenotypes. J Hypertens. 2012;30:67–74.

    Article  CAS  PubMed  Google Scholar 

  13. Herbert A, Cruickshank JK, Laurent S, Boutouyrie P, Reference Values for Arterial Measurements C. Establishing reference values for central blood pressure and its amplification in a general healthy population and according to cardiovascular risk factors. Eur Heart J. 2014;35:3122–33.

    Article  PubMed  Google Scholar 

  14. Mitchell GF. Central pressure should not be used in clinical practice. Artery Res. 2015;9:8–13.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Sharman JE. Central pressure should be used in clinical practice. Artery Res. 2015;9:1–7.

    Article  Google Scholar 

  16. Williams B, Lacy PS, Thom SM, Cruickshank K, Stanton A, Collier D, et al. Differential impact of blood pressure-lowering drugs on central aortic pressure and clinical outcomes: principal results of the Conduit Artery Function Evaluation (CAFE) study. Circulation. 2006;113:1213–25.

    Article  CAS  PubMed  Google Scholar 

  17. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R, Prospective Studies C. 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. 2002;360:1903–13.

    Article  PubMed  Google Scholar 

  18. Group SR, Wright Jr JT, Williamson JD, Whelton PK, Snyder JK, Sink KM, et al. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med. 2015;373:2103–16. The SPRINT Trial provides evidence for the benefit of treatment to lower blood pressure goals than currently recommended in clinical guidelines. Some patients are, however, intolerant to aggressive blood pressure lowering therapy, and biomarkers may have the potential to identify such patients.

    Article  CAS  Google Scholar 

  19. Cushman WC, Whelton PK, Fine LJ, Wright Jr JT, Reboussin DM, Johnson KC, et al. SPRINT trial results: latest news in hypertension management. Hypertension. 2016;67:263–5.

    CAS  PubMed  Google Scholar 

  20. Brunstrom M, Carlberg B. Effect of antihypertensive treatment at different blood pressure levels in patients with diabetes mellitus: systematic review and meta-analyses. BMJ. 2016;352:i717.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Tinetti ME, Han L, Lee DS, McAvay GJ, Peduzzi P, Gross CP, et al. Antihypertensive medications and serious fall injuries in a nationally representative sample of older adults. JAMA Intern Med. 2014;174:588–95.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Padmanabhan S, Caulfield M, Dominiczak AF. Genetic and molecular aspects of hypertension. Circ Res. 2015;116:937–59. This review provides a comprehensive overview of the genetics of hypertension and highlights the relationship between genetic findings and dysregulated pathophysiological pathways.

    Article  CAS  PubMed  Google Scholar 

  23. Padmanabhan S, Melander O, Hastie C, Menni C, Delles C, Connell JM, et al. Hypertension and genome-wide association studies: combining high fidelity phenotyping and hypercontrols. J Hypertens. 2008;26:1275–81.

    Article  CAS  PubMed  Google Scholar 

  24. Hubner N, Wallace CA, Zimdahl H, Petretto E, Schulz H, Maciver F, et al. Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nat Genet. 2005;37:243–53.

    Article  CAS  PubMed  Google Scholar 

  25. Marques FZ, Campain AE, Tomaszewski M, Zukowska-Szczechowska E, Yang YH, Charchar FJ, et al. Gene expression profiling reveals renin mRNA overexpression in human hypertensive kidneys and a role for microRNAs. Hypertension. 2011;58:1093–8.

    Article  CAS  PubMed  Google Scholar 

  26. Marques FZ, Charchar FJ. microRNAs in essential hypertension and blood pressure regulation. Adv Exp Med Biol. 2015;888:215–35.

    Article  PubMed  Google Scholar 

  27. Marques FZ, Romaine SP, Denniff M, Eales J, Dormer J, Garrelds IM et al. Signatures of miR-181a on renal transcriptome and blood pressure. Mol Med. 2015.

  28. Menni C, Graham D, Kastenmuller G, Alharbi NH, Alsanosi SM, McBride M, et al. Metabolomic identification of a novel pathway of blood pressure regulation involving hexadecanedioate. Hypertension. 2015;66:422–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lindsey ML, Mayr M, Gomes AV, Delles C, Arrell DK, Murphy AM, et al. Transformative impact of proteomics on cardiovascular health and disease: a scientific statement from the American heart association. Circulation. 2015;132:852–72.

    Article  CAS  PubMed  Google Scholar 

  30. Carty DM, Schiffer E, Delles C. Proteomics in hypertension. J Hum Hypertens. 2013;27:211–6.

    Article  CAS  PubMed  Google Scholar 

  31. Carty DM, Siwy J, Brennand JE, Zurbig P, Mullen W, Franke J, et al. Urinary proteomics for prediction of preeclampsia. Hypertension. 2011;57:561–9.

    Article  CAS  PubMed  Google Scholar 

  32. Myers JE, Tuytten R, Thomas G, Laroy W, Kas K, Vanpoucke G, et al. Integrated proteomics pipeline yields novel biomarkers for predicting preeclampsia. Hypertension. 2013;61:1281–8.

    Article  CAS  PubMed  Google Scholar 

  33. Hall JE, Granger JP, do Carmo JM, da Silva AA, Dubinion J, George E, et al. Hypertension: physiology and pathophysiology. Compr Physiol. 2012;2:2393–442.

    PubMed  Google Scholar 

  34. Krum H, Schlaich M, Whitbourn R, Sobotka PA, Sadowski J, Bartus K, et al. Catheter-based renal sympathetic denervation for resistant hypertension: a multicentre safety and proof-of-principle cohort study. Lancet. 2009;373:1275–81.

    Article  PubMed  Google Scholar 

  35. Grassi G, Mark A, Esler M. The sympathetic nervous system alterations in human hypertension. Circ Res. 2015;116:976–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. 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;370:1393–401.

    Article  CAS  PubMed  Google Scholar 

  37. Dorr O, Liebetrau C, Mollmann H, Gaede L, Troidl C, Haidner V, et al. Brain-derived neurotrophic factor as a marker for immediate assessment of the success of renal sympathetic denervation. J Am Coll Cardiol. 2015;65:1151–3.

    Article  CAS  PubMed  Google Scholar 

  38. Currie G, Delles C, Touyz RM, Staessen JA, Dominiczak AF, Jennings GL, et al. A woman with treatment-resistant hypertension. Hypertension. 2016;67:243–50.

    CAS  PubMed  Google Scholar 

  39. Titze J. Sodium balance is not just a renal affair. Curr Opin Nephrol Hypertens. 2014;23:101–5.

    Article  CAS  PubMed  Google Scholar 

  40. Jantsch J, Schatz V, Friedrich D, Schroder A, Kopp C, Siegert I, et al. Cutaneous Na+ storage strengthens the antimicrobial barrier function of the skin and boosts macrophage-driven host defense. Cell Metab. 2015;21:493–501.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Linz P, Santoro D, Renz W, Rieger J, Ruehle A, Ruff J, et al. Skin sodium measured with (2)(3)Na MRI at 7.0 T. NMR Biomed. 2015;28:54–62.

    CAS  PubMed  Google Scholar 

  42. Kopp C, Linz P, Dahlmann A, Hammon M, Jantsch J, Muller DN, et al. 23Na magnetic resonance imaging-determined tissue sodium in healthy subjects and hypertensive patients. Hypertension. 2013;61:635–40.

    Article  CAS  PubMed  Google Scholar 

  43. Hammon M, Grossmann S, Linz P, Kopp C, Dahlmann A, Janka R, et al. 3 Tesla (23)Na magnetic resonance imaging during aerobic and anaerobic exercise. Acad Radiol. 2015;22:1181–90.

    Article  PubMed  Google Scholar 

  44. Dahlmann A, Dorfelt K, Eicher F, Linz P, Kopp C, Mossinger I, et al. Magnetic resonance-determined sodium removal from tissue stores in hemodialysis patients. Kidney Int. 2015;87:434–41. This clinical imaging study provides evidence for increased storage of sodium in patients with end-stage renal failure and that sodium can be removed by haemodialysis. Together with the paper by Kopp et al (reference 42), there is now evidence for dysregulated whole body sodium storage in hypertension and associated diseases.

    Article  CAS  PubMed  Google Scholar 

  45. Feihl F, Liaudet L, Levy BI, Waeber B. Hypertension and microvascular remodelling. Cardiovasc Res. 2008;78:274–85.

    Article  CAS  PubMed  Google Scholar 

  46. Laurent S, Boutouyrie P. The structural factor of hypertension: large and small artery alterations. Circ Res. 2015;116:1007–21.

    Article  CAS  PubMed  Google Scholar 

  47. Burger D, Schock S, Thompson CS, Montezano AC, Hakim AM, Touyz RM. Microparticles: biomarkers and beyond. Clin Sci (Lond). 2013;124:423–41.

    Article  CAS  Google Scholar 

  48. Helbing T, Olivier C, Bode C, Moser M, Diehl P. Role of microparticles in endothelial dysfunction and arterial hypertension. World J Cardiol. 2014;6:1135–9.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Amabile N, Cheng S, Renard JM, Larson MG, Ghorbani A, McCabe E, et al. Association of circulating endothelial microparticles with cardiometabolic risk factors in the Framingham Heart Study. Eur Heart J. 2014;35:2972–9.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Zu L, Ren C, Pan B, Zhou B, Zhou E, Niu C, et al. Endothelial microparticles after antihypertensive and lipid-lowering therapy inhibit the adhesion of monocytes to endothelial cells. Int J Cardiol. 2016;202:756–9.

    Article  PubMed  Google Scholar 

  51. Campello E, Spiezia L, Radu CM, Dhima S, Visentin S, Valle FD, et al. Circulating microparticles in umbilical cord blood in normal pregnancy and pregnancy with preeclampsia. Thromb Res. 2015;136:427–31.

    Article  CAS  PubMed  Google Scholar 

  52. Salem M, Kamal S, El Sherbiny W, Abdel Aal AA. Flow cytometric assessment of endothelial and platelet microparticles in preeclampsia and their relation to disease severity and Doppler parameters. Hematology. 2015;20:154–9.

    Article  PubMed  Google Scholar 

  53. Jankowski V, Vanholder R, van der Giet M, Tolle M, Karadogan S, Gobom J, et al. Mass-spectrometric identification of a novel angiotensin peptide in human plasma. Arterioscler Thromb Vasc Biol. 2007;27:297–302.

    Article  CAS  PubMed  Google Scholar 

  54. Salem S, Jankowski V, Asare Y, Liehn E, Welker P, Raya-Bermudez A, et al. Identification of the vasoconstriction-inhibiting factor (VIF), a potent endogenous cofactor of angiotensin II acting on the angiotensin II type 2 receptor. Circulation. 2015;131:1426–34. This paper and a previous paper from this group (Jankowski et al, reference 53) demonstrate how unbiased screening approaches such as mass spectrometry can lead to the identification of novel vasoactive factors that could serve as biomarkers of hypertension.

    Article  CAS  PubMed  Google Scholar 

  55. Tenderenda-Banasiuk E, Wasilewska A, Filonowicz R, Jakubowska U, Waszkiewicz-Stojda M. Serum copeptin levels in adolescents with primary hypertension. Pediatr Nephrol. 2014;29:423–9.

    Article  PubMed  Google Scholar 

  56. Santillan MK, Santillan DA, Scroggins SM, Min JY, Sandgren JA, Pearson NA, et al. Vasopressin in preeclampsia: a novel very early human pregnancy biomarker and clinically relevant mouse model. Hypertension. 2014;64:852–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Yeung EH, Liu A, Mills JL, Zhang C, Mannisto T, Lu Z, et al. Increased levels of copeptin before clinical diagnosis of preelcampsia. Hypertension. 2014;64:1362–7.

    Article  CAS  PubMed  Google Scholar 

  58. Montezano AC, Dulak-Lis M, Tsiropoulou S, Harvey A, Briones AM, Touyz RM. Oxidative stress and human hypertension: vascular mechanisms, biomarkers, and novel therapies. Can J Cardiol. 2015;31:631–41.

    Article  PubMed  Google Scholar 

  59. Holterman CE, Thibodeau JF, Towaij C, Gutsol A, Montezano AC, Parks RJ, et al. Nephropathy and elevated BP in mice with podocyte-specific NADPH oxidase 5 expression. J Am Soc Nephrol. 2014;25:784–97.

    Article  CAS  PubMed  Google Scholar 

  60. Hamilton CA, Miller WH, Al-Benna S, Brosnan MJ, Drummond RD, McBride MW, et al. Strategies to reduce oxidative stress in cardiovascular disease. Clin Sci (Lond). 2004;106:219–34.

    Article  CAS  Google Scholar 

  61. Redon J, Oliva MR, Tormos C, Giner V, Chaves J, Iradi A, et al. Antioxidant activities and oxidative stress byproducts in human hypertension. Hypertension. 2003;41:1096–101.

    Article  CAS  PubMed  Google Scholar 

  62. Wenzel U, Turner JE, Krebs C, Kurts C, Harrison DG, Ehmke H. Immune mechanisms in arterial hypertension. J Am Soc Nephrol. 2016;27:677–86.

    Article  PubMed  Google Scholar 

  63. Hage FG. C-reactive protein and hypertension. J Hum Hypertens. 2014;28:410–5.

    Article  CAS  PubMed  Google Scholar 

  64. Feig DI. Serum uric acid and the risk of hypertension and chronic kidney disease. Curr Opin Rheumatol. 2014;26:176–85.

    Article  CAS  PubMed  Google Scholar 

  65. Verdecchia P, Schillaci G, Reboldi G, Santeusanio F, Porcellati C, Brunetti P. Relation between serum uric acid and risk of cardiovascular disease in essential hypertension. The PIUMA study. Hypertension. 2000;36:1072–8.

    Article  CAS  PubMed  Google Scholar 

  66. Viazzi F, Garneri D, Leoncini G, Gonnella A, Muiesan ML, Ambrosioni E, et al. Serum uric acid and its relationship with metabolic syndrome and cardiovascular risk profile in patients with hypertension: insights from the I-DEMAND study. Nutr Metab Cardiovasc Dis. 2014;24:921–7.

    Article  CAS  PubMed  Google Scholar 

  67. Zoccali C, Mallamaci F. Uric acid, hypertension, and cardiovascular and renal complications. Curr Hypertens Rep. 2013;15:531–7.

    Article  CAS  PubMed  Google Scholar 

  68. Soletsky B, Feig DI. Uric acid reduction rectifies prehypertension in obese adolescents. Hypertension. 2012;60:1148–56.

    Article  CAS  PubMed  Google Scholar 

  69. MacIsaac RL, Salatzki J, Higgins P, Walters MR, Padmanabhan S, Dominiczak AF, et al. Allopurinol and cardiovascular outcomes in adults with hypertension. Hypertension. 2016;67:535–40. This study is based on a large clinical dataset and provides “real life” evidence for the role of uric acid for long-term risk in patients with hypertension.

    CAS  PubMed  Google Scholar 

  70. Zhang W, Wang L, Chen Y, Tang F, Xue F, Zhang C. Identification of hypertension predictors and application to hypertension prediction in an urban han Chinese population: a longitudinal study, 2005-2010. Prev Chronic Dis. 2015;12:E184.

    PubMed  PubMed Central  Google Scholar 

  71. Wang TJ, Gona P, Larson MG, Levy D, Benjamin EJ, Tofler GH, et al. Multiple biomarkers and the risk of incident hypertension. Hypertension. 2007;49:432–8.

    Article  CAS  PubMed  Google Scholar 

  72. Yao L, Folsom AR, Pankow JS, Selvin E, Michos ED, Alonso A, et al. Parathyroid hormone and the risk of incident hypertension: the atherosclerosis risk in communities study. J Hypertens. 2016;34:196–203.

    Article  CAS  PubMed  Google Scholar 

  73. McEvoy JW, Chen Y, Nambi V, Ballantyne CM, Sharrett AR, Appel LJ, et al. High-sensitivity cardiac troponin t and risk of hypertension. Circulation. 2015;132:825–33. This paper from the Atherosclerosis Risk in Communities (ARIC) Study demonstrates that increased levels of hs-cTnT are associated with incident hypertension and could identify patients who may benefit from early intensive monitoring and preventative intervention.

    Article  CAS  PubMed  Google Scholar 

  74. Mandel EI, Forman JP, Curhan GC, Taylor EN. Plasma bicarbonate and odds of incident hypertension. Am J Hypertens. 2013;26:1405–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Yang T, Chu CH, Bai CH, You SL, Chou YC, Hwang LC, et al. Uric acid concentration as a risk marker for blood pressure progression and incident hypertension: a Chinese cohort study. Metabolism. 2012;61:1747–55.

    Article  CAS  PubMed  Google Scholar 

  76. Arnlov J, Pencina MJ, Nam BH, Meigs JB, Fox CS, Levy D, et al. Relations of insulin sensitivity to longitudinal blood pressure tracking: variations with baseline age, body mass index, and blood pressure. Circulation. 2005;112:1719–27.

    Article  PubMed  CAS  Google Scholar 

  77. Paynter NP, Sesso HD, Conen D, Otvos JD, Mora S. Lipoprotein subclass abnormalities and incident hypertension in initially healthy women. Clin Chem. 2011;57:1178–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Kunutsor SK, Apekey TA, Steur M. Vitamin D and risk of future hypertension: meta-analysis of 283,537 participants. Eur J Epidemiol. 2013;28:205–21.

    Article  CAS  PubMed  Google Scholar 

  79. Julius S, Nesbitt SD, Egan BM, Weber MA, Michelson EL, Kaciroti N, et al. Feasibility of treating prehypertension with an angiotensin-receptor blocker. N Engl J Med. 2006;354:1685–97.

    Article  CAS  PubMed  Google Scholar 

  80. Luders S, Schrader J, Berger J, Unger T, Zidek W, Bohm M, et al. The PHARAO study: prevention of hypertension with the angiotensin-converting enzyme inhibitor ramipril in patients with high-normal blood pressure: a prospective, randomized, controlled prevention trial of the German Hypertension League. J Hypertens. 2008;26:1487–96.

    Article  PubMed  CAS  Google Scholar 

  81. Buhler FR, Bolli P, Kiowski W, Erne P, Hulthen UL, Block LH. Renin profiling to select antihypertensive baseline drugs. Renin inhibitors for high-renin and calcium entry blockers for low-renin patients. Am J Med. 1984;77:36–42.

    Article  CAS  PubMed  Google Scholar 

  82. 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;386:2059–68. This clinical trial provides evidence for blood pressure-lowering effects of spironolactone in resistant hypertension and that the magnitude of effect is related to activation of the renin-angiotensin-aldosterone system.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Krzesinski P, Gielerak GG, Kowal JJ. A “patient-tailored” treatment of hypertension with use of impedance cardiography: a randomized, prospective and controlled trial. Med Sci Monit. 2013;19:242–50.

    Article  PubMed  PubMed Central  Google Scholar 

  84. Fadl Elmula FE, Rebora P, Talvik A, Salerno S, Miszkowska-Nagorna E, Liu X, et al. A randomized and controlled study of noninvasive hemodynamic monitoring as a guide to drug treatment of uncontrolled hypertensive patients. J Hypertens. 2015;33:2534–45.

    Article  CAS  PubMed  Google Scholar 

  85. Fox CS, Hall JL, Arnett DK, Ashley EA, Delles C, Engler MB, et al. Future translational applications from the contemporary genomics era: a scientific statement from the American Heart Association. Circulation. 2015;131:1715–36.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Gong Y, McDonough CW, Beitelshees AL, El Rouby N, Hiltunen TP, O’Connell JR, et al. PTPRD gene associated with blood pressure response to atenolol and resistant hypertension. J Hypertens. 2015;33:2278–85.

    Article  CAS  PubMed  Google Scholar 

  87. Padmanabhan S, Wallace C, Munroe PB, Dobson R, Brown M, Samani N, et al. Chromosome 2p shows significant linkage to antihypertensive response in the British Genetics of Hypertension Study. Hypertension. 2006;47:603–8.

    Article  CAS  PubMed  Google Scholar 

  88. Turner ST, Boerwinkle E, O’Connell JR, Bailey KR, Gong Y, Chapman AB, et al. Genomic association analysis of common variants influencing antihypertensive response to hydrochlorothiazide. Hypertension. 2013;62:391–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Devereux RB, Pickering TG, Alderman MH, Chien S, Borer JS, Laragh JH. Left ventricular hypertrophy in hypertension. Prevalence and relationship to pathophysiologic variables. Hypertension. 1987;9:II53–60.

    CAS  PubMed  Google Scholar 

  90. Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L, et al. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension. 2001;37:1236–41.

    Article  CAS  PubMed  Google Scholar 

  91. Vlachopoulos C, Xaplanteris P, Aboyans V, Brodmann M, Cifkova R, Cosentino F, et al. The role of vascular biomarkers for primary and secondary prevention. A position paper from the European Society of Cardiology Working Group on peripheral circulation: Endorsed by the Association for Research into Arterial Structure and Physiology (ARTERY) Society. Atherosclerosis. 2015;241:507–32.

    Article  CAS  PubMed  Google Scholar 

  92. Flammer AJ, Anderson T, Celermajer DS, Creager MA, Deanfield J, Ganz P, et al. The assessment of endothelial function: from research into clinical practice. Circulation. 2012;126:753–67.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Harazny JM, Ritt M, Baleanu D, Ott C, Heckmann J, Schlaich MP, et al. Increased wall:lumen ratio of retinal arterioles in male patients with a history of a cerebrovascular event. Hypertension. 2007;50:623–9.

    Article  CAS  PubMed  Google Scholar 

  94. Delles C, Michelson G, Harazny J, Oehmer S, Hilgers KF, Schmieder RE. Impaired endothelial function of the retinal vasculature in hypertensive patients. Stroke. 2004;35:1289–93.

    Article  CAS  PubMed  Google Scholar 

  95. Lind L, Siegbahn A, Hulthe J, Elmgren A. C-reactive protein and e-selectin levels are related to vasodilation in resistance, but not conductance arteries in the elderly: the prospective investigation of the Vasculature in Uppsala Seniors (PIVUS) study. Atherosclerosis. 2008;199:129–37.

    Article  CAS  PubMed  Google Scholar 

  96. Wykretowicz J, Guzik P, Krauze T, Marciniak R, Komarnicki M, Piskorski J, et al. Fibrinogen and d-dimer in contrasting relation with measures of wave reflection and arterial stiffness. Scand J Clin Lab Invest. 2012;72:629–34.

    Article  CAS  PubMed  Google Scholar 

  97. Yasmin, McEniery CM, Wallace S, Mackenzie IS, Cockcroft JR, Wilkinson IB. C-reactive protein is associated with arterial stiffness in apparently healthy individuals. Arterioscler Thromb Vasc Biol. 2004;24:969–74.

    Article  CAS  PubMed  Google Scholar 

  98. John S, Jacobi J, Delles C, Schlaich MP, Alter O, Schmieder RE. Plasma soluble adhesion molecules and endothelium-dependent vasodilation in early human atherosclerosis. Clin Sci (Lond). 2000;98:521–9.

    Article  CAS  Google Scholar 

  99. Husi H, Van Agtmael T, Mullen W, Bahlmann FH, Schanstra JP, Vlahou A, et al. Proteome-based systems biology analysis of the diabetic mouse aorta reveals major changes in fatty acid biosynthesis as potential hallmark in diabetes mellitus-associated vascular disease. Circ Cardiovasc Genet. 2014;7:161–70.

    Article  CAS  PubMed  Google Scholar 

  100. Levy D, Garrison RJ, Savage DD, Kannel WB, Castelli WP. Prognostic implications of echocardiographically determined left ventricular mass in the Framingham Heart Study. N Engl J Med. 1990;322:1561–6.

    Article  CAS  PubMed  Google Scholar 

  101. Schmieder RE, Schlaich MP, Klingbeil AU, Martus P. Update on reversal of left ventricular hypertrophy in essential hypertension (a meta-analysis of all randomized double-blind studies until December 1996). Nephrol Dial Transplant. 1998;13:564–9.

    Article  CAS  PubMed  Google Scholar 

  102. Devereux RB, Wachtell K, Gerdts E, Boman K, Nieminen MS, Papademetriou V, et al. Prognostic significance of left ventricular mass change during treatment of hypertension. JAMA. 2004;292:2350–6.

    Article  CAS  PubMed  Google Scholar 

  103. Okin PM, Devereux RB, Jern S, Kjeldsen SE, Julius S, Nieminen MS, et al. Regression of electrocardiographic left ventricular hypertrophy during antihypertensive treatment and the prediction of major cardiovascular events. JAMA. 2004;292:2343–9.

    Article  CAS  PubMed  Google Scholar 

  104. Sciarretta S, Ferrucci A, Ciavarella GM, De Paolis P, Venturelli V, Tocci G, et al. Markers of inflammation and fibrosis are related to cardiovascular damage in hypertensive patients with metabolic syndrome. Am J Hypertens. 2007;20:784–91.

    Article  CAS  PubMed  Google Scholar 

  105. Bricca G, Lantelme P. Natriuretic peptides: ready for prime-time in hypertension? Arch Cardiovasc Dis. 2011;104:403–9.

    Article  PubMed  Google Scholar 

  106. Phelan D, Watson C, Martos R, Collier P, Patle A, Donnelly S, et al. Modest elevation in BNP in asymptomatic hypertensive patients reflects sub-clinical cardiac remodeling, inflammation and extracellular matrix changes. PLoS One. 2012;7:e49259.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Welsh P, Hart C, Papacosta O, Preiss D, McConnachie A, Murray H, et al. Prediction of cardiovascular disease risk by cardiac biomarkers in 2 United Kingdom cohort studies: does utility depend on risk thresholds for treatment? Hypertension. 2016;67:309–15.

    CAS  PubMed  Google Scholar 

  108. Kuznetsova T, Mischak H, Mullen W, Staessen JA. Urinary proteome analysis in hypertensive patients with left ventricular diastolic dysfunction. Eur Heart J. 2012;33:2342–50. In this study, a novel biomarker based on urinary peptidomic profiles has been found to be associated with left ventricular diastolic dysfunction and risk of developing heart failure. This biomarker is attractive as it identifies patients at risk and provides insight into the pathophysiology of heart failure at an early stage of the disease.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Shlipak MG, Matsushita K, Arnlov J, Inker LA, Katz R, Polkinghorne KR, et al. Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med. 2013;369:932–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Gillis KA, McComb C, Foster JE, Taylor AH, Patel RK, Morris ST, et al. Inter-study reproducibility of arterial spin labelling magnetic resonance imaging for measurement of renal perfusion in healthy volunteers at 3 Tesla. BMC Nephrol. 2014;15:23.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Prasad PV, Edelman RR, Epstein FH. Noninvasive evaluation of intrarenal oxygenation with BOLD MRI. Circulation. 1996;94:3271–5.

    Article  CAS  PubMed  Google Scholar 

  112. Textor SC, Glockner JF, Lerman LO, Misra S, McKusick MA, Riederer SJ, et al. The use of magnetic resonance to evaluate tissue oxygenation in renal artery stenosis. J Am Soc Nephrol. 2008;19:780–8.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Currie G, McKay G, Delles C. Biomarkers in diabetic nephropathy: present and future. World J Diabetes. 2014;5:763–76.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Pena MJ, Jankowski J, Heinze G, Kohl M, Heinzel A, Bakker SJ, et al. Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes. J Hypertens. 2015;33:2123–32.

    Article  CAS  PubMed  Google Scholar 

  115. Good DM, Zurbig P, Argiles A, Bauer HW, Behrens G, Coon JJ, et al. Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Mol Cell Proteomics. 2010;9:2424–37.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Lindhardt M, Persson F, Currie G, Pontillo C, Beige J, Delles C, et al. Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention of early diabetic nephRopathy in TYpe 2 diabetic patients with normoalbuminuria (PRIORITY): essential study design and rationale of a randomised clinical multicentre trial. BMJ Open. 2016;6:e010310. This paper describes the design of the first large-scale multicentre-stratified RCT based on a novel urinary peptidomic biomarker. Such studies will provide the ultimate evidence for the usefulness of biomarkers in clinical practice.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Sierra C, Coca A, Schiffrin EL. Vascular mechanisms in the pathogenesis of stroke. Curr Hypertens Rep. 2011;13:200–7.

    Article  CAS  PubMed  Google Scholar 

  118. Dahlof B, Devereux RB, Kjeldsen SE, Julius S, Beevers G, de Faire U, et al. Cardiovascular morbidity and mortality in the Losartan Intervention For Endpoint reduction in hypertension study (LIFE): a randomised trial against atenolol. Lancet. 2002;359:995–1003.

    Article  CAS  PubMed  Google Scholar 

  119. Hughes TM, Sink KM. Hypertension and its role in cognitive function: current evidence and challenges for the future. Am J Hypertens. 2016;29:149–57.

    Article  PubMed  Google Scholar 

  120. Kherada N, Heimowitz T, Rosendorff C. Antihypertensive therapies and cognitive function: a review. Curr Hypertens Rep. 2015;17:79.

    Article  PubMed  CAS  Google Scholar 

  121. Scuteri A, Tesauro M, Guglini L, Lauro D, Fini M, Di Daniele N. Aortic stiffness and hypotension episodes are associated with impaired cognitive function in older subjects with subjective complaints of memory loss. Int J Cardiol. 2013;169:371–7.

    Article  PubMed  Google Scholar 

  122. Prins ND, Scheltens P. White matter hyperintensities, cognitive impairment and dementia: an update. Nat Rev Neurol. 2015;11:157–65.

    Article  PubMed  Google Scholar 

  123. Kitagawa K. Cerebral blood flow measurement by PET in hypertensive subjects as a marker of cognitive decline. J Alzheimers Dis. 2010;20:855–9.

    PubMed  Google Scholar 

  124. Pase MP, Himali JJ, Mitchell GF, Beiser A, Maillard P, Tsao C, et al. Association of aortic stiffness with cognition and brain aging in young and middle-aged adults: the Framingham Third Generation Cohort Study. Hypertension. 2016;67:513–9. The association between systemic changes in large artery structure and function and cognition is demonstrated in this paper. It provides a link between the cerebral microcirculation and systemic large arteries that are both subject to damage by high blood pressure and could also interact with each other directly.

    CAS  PubMed  Google Scholar 

  125. Yau PL, Hempel R, Tirsi A, Convit A. Cerebral white matter and retinal arterial health in hypertension and type 2 diabetes mellitus. Int J Hypertens. 2013;2013:329602.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Li Y, Sun Y, Li J, Wang Z, Lin Y, Tang L, et al. Changes of ubiquitin C-terminal hydrolase-L1 levels in serum and urine of patients with white matter lesions. J Neurol Sci. 2015;357:215–21.

    Article  CAS  PubMed  Google Scholar 

  127. Tchalla AE, Wellenius GA, Travison TG, Gagnon M, Iloputaife I, Dantoine T, et al. Circulating vascular cell adhesion molecule-1 is associated with cerebral blood flow dysregulation, mobility impairment, and falls in older adults. Hypertension. 2015;66:340–6. This study provides first evidence that biomarkers could be used to predict side effects (impaired cerebral perfusion, falls) in patients treated with antihypertensive agents.

    Article  CAS  PubMed  Google Scholar 

  128. Thomopoulos C, Parati G, Zanchetti A. Effects of blood pressure lowering on outcome incidence in hypertension. 1. Overview, meta-analyses, and meta-regression analyses of randomized trials. J Hypertens. 2014;32:2285–95.

    Article  CAS  PubMed  Google Scholar 

  129. Xie X, Atkins E, Lv J, Bennett A, Neal B, Ninomiya T, et al. Effects of intensive blood pressure lowering on cardiovascular and renal outcomes: updated systematic review and meta-analysis. Lancet. 2016;387:435–43.

    Article  PubMed  Google Scholar 

  130. Yoshida S, Takeuchi T, Kotani T, Yamamoto N, Hata K, Nagai K, et al. Infliximab, a TNF-alpha inhibitor, reduces 24-h ambulatory blood pressure in rheumatoid arthritis patients. J Hum Hypertens. 2014;28:165–9.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

Our work is supported by collaborative project grants from the European Commission “EU-MASCARA” (grant agreement 278249), “sysVASC” (grant agreement 603288), “HOMAGE” (grant agreement 305507) and “PRIORITY” (grant agreement 279277). Icons in the figure were made by Freepik from www.flaticon.com.

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Correspondence to Christian Delles.

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Drs. Currie and Delles declare no conflicts of interest.

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This article is part of the Topical Collection on Resistant Hypertension

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Currie, G., Delles, C. Use of Biomarkers in the Evaluation and Treatment of Hypertensive Patients. Curr Hypertens Rep 18, 54 (2016). https://doi.org/10.1007/s11906-016-0661-6

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