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Biomarkers in heart failure: the past, current and future

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Abstract

Despite the enhanced knowledge of the pathophysiology of heart failure (HF), it still remains a serious syndrome with substantial morbidity, mortality, and frequent hospitalizations. These are due to the current improvements in other cardiovascular diseases (like myocardial infarction), the aging population, and growing prevalence of comorbidities. Biomarker-guided management has brought a new dimension in prognostication, diagnosis, and therapy options. Following the recommendation of natriuretic peptides (B-type natriuretic peptide and N-terminal-proBNP), many other biomarkers have been thoroughly studied to reflect different pathophysiological processes (such as fibrosis, inflammation, myocardial injury, and remodeling) in HF and some of them (like cardiac troponins, soluble suppression of tumorigenesis-2, and galectin 3) have subsequently been recommended to aid in the diagnosis and prognostication in HF. Consequently, multi-marker approach has also been approved owing to the varied nature of HF syndrome. In this review, we discussed the guidelines available for HF biomarkers, procedures for evaluating novel markers, and the utilities of both emerging and established biomarkers for risk stratification, diagnosis, and management of HF in the clinics. We later looked at how the rapidly emerging field—OMICs, can help transform HF biomarkers discoveries and establishment.

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References

  1. Benjamin EJ et al (2017) Heart disease and stroke statistics-2017 update: a report from the American Heart Association. Circulation 135(10):e146–e603

    Article  PubMed  PubMed Central  Google Scholar 

  2. McMurray JJ et al (2012) ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2012: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2012 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association (HFA) of the ESC. Eur Heart J 33(14):1787–1847

    Article  PubMed  Google Scholar 

  3. GBD 2013 Mortality and Causes of Death Collaborators (2015) Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 385(9963):117–171

    Article  Google Scholar 

  4. Ponikowski P et al (2014) Heart failure: preventing disease and death worldwide. Esc Heart Failure 1(1):4

    Article  PubMed  Google Scholar 

  5. Yancy CW et al (2013) ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 62(16):e147–e239

    Article  PubMed  Google Scholar 

  6. Ponikowski P et al (2016) ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 37(27):2129–2200

    Article  PubMed  Google Scholar 

  7. Ahmad T et al (2012) Novel biomarkers in chronic heart failure. Nat Rev Cardiol 9(6):347–359

    Article  CAS  PubMed  Google Scholar 

  8. Biomarkers Definitions Working Group (2001) Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69(3):89–95

    Article  Google Scholar 

  9. Vasan RS (2006) Biomarkers of cardiovascular disease: molecular basis and practical considerations. Circulation 113(19):2335–2362

    Article  PubMed  Google Scholar 

  10. Maisel AS, Choudhary R (2012) Biomarkers in acute heart failure—state of the art. Nat Rev Cardiol 9(8):478–490

    Article  CAS  PubMed  Google Scholar 

  11. Lindenfeld J et al (2010) HFSA 2010 Comprehensive Heart Failure Practice Guideline. J Card Fail 16(6):e1–e194

  12. Yancy CW et al (2017) 2017 ACC/AHA/HFSA focused update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure. A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society of America. Circulation 70(6):776–803

    Google Scholar 

  13. Braunwald E (2008) Biomarkers in heart failure. N Engl J Med 358(20):2148–2159

    Article  CAS  PubMed  Google Scholar 

  14. Hlatky MA et al (2011) Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation 119(17):2408–2416

    Article  Google Scholar 

  15. Morrow DA, Lemos JAD (2007) Benchmarks for the assessment of novel cardiovascular biomarkers. Circulation 115(8):949–952

    Article  PubMed  Google Scholar 

  16. van Kimmenade RR, Januzzi JL Jr (2012) Emerging biomarkers in heart failure. Clin Chem 58(1):127–138

    Article  PubMed  CAS  Google Scholar 

  17. Tang WH et al (2008) National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines: clinical utilization of cardiac biomarker testing in heart failure. Clin Biochem 41(4–5):210–221

    Article  CAS  PubMed  Google Scholar 

  18. Gaggin HK, Jr JJ (2013) Biomarkers and diagnostics in heart failure. Biochim Biophys Acta 1832(12):2442–2450

    Article  CAS  PubMed  Google Scholar 

  19. Iwanaga Y et al (2006) B-type natriuretic peptide strongly reflects diastolic wall stress in patients with chronic heart failure: comparison between systolic and diastolic heart failure. J Am Coll Cardiol 47(4):742–748

    Article  CAS  PubMed  Google Scholar 

  20. Wang TJ et al (2012) Prognostic utility of novel biomarkers of cardiovascular stress: the Framingham Heart Study. Circulation 126(13):1596–1604

    Article  CAS  PubMed  Google Scholar 

  21. Daniels LB et al (2008) Use of natriuretic peptides in pre-participation screening of college athletes. Int J Cardiol 124(3):411–414

    Article  PubMed  Google Scholar 

  22. Maisel AS et al (2002) Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure. N Engl J Med 347(3):161–167

    Article  CAS  PubMed  Google Scholar 

  23. Januzzi JL Jr et al (2006) Utility of amino-terminal pro-brain natriuretic peptide testing for prediction of 1-year mortality in patients with dyspnea treated in the emergency department. Arch Intern Med 166(3):315–320

    Article  CAS  PubMed  Google Scholar 

  24. Januzzi JL Jr (2012) The role of natriuretic peptide testing in guiding chronic heart failure management: review of available data and recommendations for use. Arch Cardiovasc Dis 105(1):40–50

    Article  PubMed  Google Scholar 

  25. Krupicka J, Janota T, Hradec J (2013) Natriuretic peptides in heart failure. Cor Et Vasa 55(4):e370–e376

    Article  Google Scholar 

  26. Pang PS et al (2012) The role of natriuretic peptides: from the emergency department throughout hospitalization. Congestive Heart Fail 18(s1):S5–S8

    Article  CAS  Google Scholar 

  27. Michtalik HJ et al (2011) Acute changes in N-terminal pro-B-type natriuretic peptide during hospitalization and risk of readmission and mortality in patients with heart failure. Am J Cardiol 107(8):1191–1195

    Article  CAS  PubMed  Google Scholar 

  28. Shah RV et al (2012) Mid-regional pro-atrial natriuretic peptide and pro-adrenomedullin testing for the diagnostic and prognostic evaluation of patients with acute dyspnoea. Eur Heart J 33(17):2197–2205

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Troughton RW et al (2014) Effect of B-type natriuretic peptide-guided treatment of chronic heart failure on total mortality and hospitalization: an individual patient meta-analysis. Eur Heart J 35(23):1559–1567

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Januzzi JL Jr et al (2011) Use of amino-terminal pro-B-type natriuretic peptide to guide outpatient therapy of patients with chronic left ventricular systolic dysfunction. J Am Coll Cardiol 58(18):1881–1889

    Article  CAS  PubMed  Google Scholar 

  31. Shah MR et al (2011) The STARBRITE trial: a randomized, pilot study of B-type natriuretic peptide-guided therapy in patients with advanced heart failure. J Card Fail 17(8):613–621

    Article  PubMed  Google Scholar 

  32. Weiner RB et al (2013) Improvement in structural and functional echocardiographic parameters during chronic heart failure therapy guided by natriuretic peptides: mechanistic insights from the ProBNP Outpatient Tailored Chronic Heart Failure (PROTECT) study. Eur J Heart Fail 15(3):342–351

    Article  CAS  PubMed  Google Scholar 

  33. Richards M et al (2013) Atrial fibrillation impairs the diagnostic performance of cardiac natriuretic peptides in dyspneic patients: results from the BACH Study (Biomarkers in ACute Heart Failure). JACC Heart Fail 1(3):192–199

    Article  PubMed  Google Scholar 

  34. Felker GM et al (2017) Effect of natriuretic peptide-guided therapy on hospitalization or cardiovascular mortality in high-risk patients with heart failure and reduced ejection fraction: a randomized clinical trial. JAMA 318(8):713–720

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Mark L et al (2013) Natriuretic peptide-based screening and collaborative care for heart failure: the STOP-HF randomized trial. JAMA:the Journal of the American Medical Association 310(1):66–74

    Article  Google Scholar 

  36. Martin H et al (2013) PONTIAC (NT-proBNP selected prevention of cardiac events in a population of diabetic patients without a history of cardiac disease): a prospective randomized controlled trial. J Am Coll Cardiol 62(15):1365–1372

    Article  Google Scholar 

  37. Wollert KC, Kempf T, Wallentin L (2017) Growth differentiation factor 15 as a biomarker in cardiovascular disease. Clin Chem 63(1):140–151

    Article  CAS  PubMed  Google Scholar 

  38. Peake BF et al (2017) Growth differentiation factor 15 mediates epithelial mesenchymal transition and invasion of breast cancers through IGF-1R-FoxM1 signaling. Oncotarget 8(55):94393–94406

    Article  PubMed  PubMed Central  Google Scholar 

  39. Boulogne M et al (2017) Inflammation versus mechanical stretch biomarkers over time in acutely decompensated heart failure with reduced ejection fraction. Int J Cardiol 226:53–59

    Article  CAS  PubMed  Google Scholar 

  40. Zimmers TA et al (2006) Growth differentiation factor-15: induction in liver injury through p53 and tumor necrosis factor-independent mechanisms. J Surg Res 130(1):45–51

    Article  CAS  PubMed  Google Scholar 

  41. Kempf T et al (2006) The transforming growth factor-beta superfamily member growth-differentiation factor-15 protects the heart from ischemia/reperfusion injury. Circ Res 98(3):351–360

    Article  CAS  PubMed  Google Scholar 

  42. Berezin AE (2016) Prognostication in different heart failure phenotypes: the role of circulating biomarkers. J Circ Biomark 5:6

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Sharma A et al (2017) Utility of growth differentiation factor-15, a marker of oxidative stress and inflammation, in chronic heart failure: insights from the HF-ACTION study. JACC Heart Fail 5(10):724–734

    Article  PubMed  PubMed Central  Google Scholar 

  44. Brown DA et al (2002) Concentration in plasma of macrophage inhibitory cytokine-1 and risk of cardiovascular events in women: a nested case-control study. Lancet 359(9324):2159–2163

    Article  CAS  PubMed  Google Scholar 

  45. Kempf T et al (2007) Prognostic utility of growth differentiation factor-15 in patients with chronic heart failure. J Am Coll Cardiol 50(11):1054–1060

    Article  CAS  PubMed  Google Scholar 

  46. Xiong Y et al (2017) Long-acting MIC-1/GDF15 molecules to treat obesity: evidence from mice to monkeys. Sci Transl Med 9(412):eaan8732

    Article  PubMed  CAS  Google Scholar 

  47. Bonaca MP et al (2011) Growth differentiation factor-15 and risk of recurrent events in patients stabilized after acute coronary syndrome: observations from PROVE IT-TIMI 22. Arterioscler Thromb Vasc Biol 31(1):203–210

    Article  CAS  PubMed  Google Scholar 

  48. Nils N et al (2008) Growth differentiation factor-15 in idiopathic pulmonary arterial hypertension. Am J Respir Crit Care Med 178(5):534–541

    Article  CAS  Google Scholar 

  49. Mareike L et al (2008) Growth differentiation factor-15 for prognostic assessment of patients with acute pulmonary embolism. Am J Respir Crit Care Med 177(9):1018

    Article  CAS  Google Scholar 

  50. Thomas M et al (2015) Association of the biomarkers soluble ST2, galectin-3 and growth-differentiation factor-15 with heart failure and other non-cardiac diseases. Clin Chim Acta 445:155–160

    Article  CAS  Google Scholar 

  51. Jr JJ et al (2007) Measurement of the interleukin family member ST2 in patients with acute dyspnea: results from the PRIDE (Pro-Brain Natriuretic Peptide Investigation of Dyspnea in the Emergency Department) study. Digest World Core Med J 50(7):607–613

    Google Scholar 

  52. Mueller T et al (2008) Increased plasma concentrations of soluble ST2 are predictive for 1-year mortality in patients with acute destabilized heart failure. Clin Chem 54(4):752–756

    Article  CAS  PubMed  Google Scholar 

  53. Broch K et al (2012) Soluble ST2 is associated with adverse outcome in patients with heart failure of ischaemic aetiology. Eur J Heart Fail 14(3):268

    Article  CAS  PubMed  Google Scholar 

  54. Binas D et al (2018) The prognostic value of sST2 and galectin-3 considering different aetiologies in non-ischaemic heart failure. Open Heart 5(1):e000750

    Article  PubMed  PubMed Central  Google Scholar 

  55. O'Meara E et al (2018) Independent prognostic value of serum soluble ST2 measurements in patients with heart failure and a reduced ejection fraction in the PARADIGM-HF trial (prospective comparison of ARNI with ACEI to determine impact on global mortality and morbidity in heart failure). Circ Heart Fail 11(5):e004446

    CAS  PubMed  Google Scholar 

  56. Mueller T, Jaffe AS (2015) Soluble ST2—analytical considerations. Am J Cardiol 115(7 Suppl):8b–21b

    Article  PubMed  Google Scholar 

  57. Ueland T et al (2011) Galectin-3 in heart failure: high levels are associated with all-cause mortality. Int J Cardiol 150(3):361–364

    Article  PubMed  Google Scholar 

  58. Ho JE et al (2012) Galectin-3, a marker of cardiac fibrosis, predicts incident heart failure in the community. J Am Coll Cardiol 60(14):1249–1256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Leone M, Iacoviello M (2016) The predictive value of plasma biomarkers in discharged heart failure patients: role of galectin-3. Minerva Cardioangiol 64(2):181–194

    PubMed  Google Scholar 

  60. Shah KS, Maisel AS (2014) Novel biomarkers in heart failure with preserved ejection fraction. Heart Fail Clin 10(3):471–479

    Article  PubMed  Google Scholar 

  61. Meijers WC et al (2015) Biomarkers and low risk in heart failure. Data from COACH and TRIUMPH. Eur J Heart Fail 17(12):1271–1282

    Article  CAS  PubMed  Google Scholar 

  62. Yu L et al (2013) Genetic and pharmacological inhibition of galectin-3 prevents cardiac remodeling by interfering with myocardial fibrogenesis. Circ Heart Fail 6(1):107–117

    Article  CAS  PubMed  Google Scholar 

  63. Weir RA et al (2013) Response to letter regarding article. Galectin-3 and cardiac function in survivors of acute myocardial infarction. Circ Heart Fail 6(4):e58

    Article  PubMed  Google Scholar 

  64. Srivatsan V, George M, Shanmugam E (2015) Utility of galectin-3 as a prognostic biomarker in heart failure: where do we stand? Eur J Prev Cardiol 22(9):1096–1110

    Article  PubMed  Google Scholar 

  65. Hartupee J, Mann DL (2013) Positioning of inflammatory biomarkers in the heart failure landscape. J Cardiovasc Transl Res 6(4):485–492

    Article  PubMed  Google Scholar 

  66. Mantel A et al (2017) Association between rheumatoid arthritis and risk of ischemic and nonischemic heart failure. J Am Coll Cardiol 69(10):1275–1285

    Article  PubMed  Google Scholar 

  67. Pye M, Rae AP, Cobbe SM (1990) Study of serum C-reactive protein concentration in cardiac failure. Br Heart J 63(4):228–230

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zwaka TP, Hombach V, Torzewski J (2001) C-reactive protein-mediated low density lipoprotein uptake by macrophages: implications for atherosclerosis. Circulation 103(9):1194–1197

    Article  CAS  PubMed  Google Scholar 

  69. Van Tassell BW et al (2014) Effects of interleukin-1 blockade with anakinra on aerobic exercise capacity in patients with heart failure and preserved ejection fraction (from the D-HART pilot study). Am J Cardiol 113(2):321–327

    Article  PubMed  CAS  Google Scholar 

  70. Nursyamsiah, Hasan R (2018) High-sensitivity c-reactive protein (hs-CRP) value with 90 days mortality in patients with heart failure. IOP Conference Series: Earth and Environmental Science 125:012124

    Article  Google Scholar 

  71. Li X et al (2014) GW25-e3420 plasma NT pro-BNP, hs-CRP and big-ET levels at admission as prognostic markers of survival in hospitalized patients with dilated cardiomyopathy: a single-center cohort study. BMC Cardiovasc Disord 64(16):67

    Article  CAS  Google Scholar 

  72. Kjekshus J, Apetrei E, Barrios V, Böhm M, Cleland JG, Cornel JH, Dunselman P, Fonseca C, Goudev A, Grande P, Gullestad L, Hjalmarson A, Hradec J, Jánosi A, Kamenský G, Komajda M, Korewicki J, Kuusi T, Mach F, Mareev V, McMurray JJ, Ranjith N, Schaufelberger M, Vanhaecke J, van Veldhuisen DJ, Waagstein F, Wedel H, Wikstrand J, CORONA Group (2008) Rosuvastatin in older patients with systolic heart failure. Int J Clin Pract 62(1):1–1

    Google Scholar 

  73. Bonaca MP, Morrow DA (2008) Defining a role for novel biomarkers in acute coronary syndromes. Clin Chem 54(9):1424–1431

    Article  CAS  PubMed  Google Scholar 

  74. Mann DL (2011) The emerging role of innate immunity in the heart and vascular system: for whom the cell tolls. Circ Res 108(9):1133–1145

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Anker SD, Von HS (2004) Inflammatory mediators in chronic heart failure: an overview. Heart 90(4):464

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Chow SL et al (2017) Role of biomarkers for the prevention, assessment, and management of heart failure: a scientific statement from the American Heart Association. Circulation 135(22):e1054

    Article  CAS  PubMed  Google Scholar 

  77. Hage C et al (2017) Inflammatory biomarkers predict heart failure severity and prognosis in patients with heart failure with preserved ejection fraction: a holistic proteomic approach. Circ Cardiovasc Genet 10(1):e001633

    Article  CAS  PubMed  Google Scholar 

  78. Kalogeropoulos A et al (2010) Inflammatory markers and incident heart failure risk in older adults: the Health ABC (Health, Aging, and Body Composition) study. J Am Coll Cardiol 55(19):2129–2137

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Van Tassell BW et al (2017) Interleukin-1 blockade in recently decompensated systolic heart failure: results from REDHART (Recently Decompensated Heart Failure Anakinra Response Trial). Circ Heart Fail 10(11):e004373

    PubMed  PubMed Central  Google Scholar 

  80. Petkova-Kirova PS et al (2006) Electrical remodeling of cardiac myocytes from mice with heart failure due to the overexpression of tumor necrosis factor-alpha. Am J Physiol Heart Circ Physiol 290(5):H2098–H2107

    Article  CAS  PubMed  Google Scholar 

  81. Bozkurt B et al (2001) Results of targeted anti-tumor necrosis factor therapy with etanercept (ENBREL) in patients with advanced heart failure. Circulation 103(8):1044–1047

    Article  CAS  PubMed  Google Scholar 

  82. Fredj S et al (2005) Role of interleukin-6 in cardiomyocyte/cardiac fibroblast interactions during myocyte hypertrophy and fibroblast proliferation. J Cell Physiol 204(2):428–436

    Article  CAS  PubMed  Google Scholar 

  83. Gabay C (2006) Interleukin-6 and chronic inflammation. Arthritis Res Ther 8(Suppl 2):S3

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  84. Fuchs F et al (2013) Activation of the inflammatory transcription factor nuclear factor interleukin-6 during inflammatory and psychological stress in the brain. J Neuroinflammation 10(1):905

    Article  CAS  Google Scholar 

  85. Li Y et al (2004) Critical roles for the Fas/Fas ligand system in postinfarction ventricular remodeling and heart failure. Circ Res 95(6):627–636

    Article  CAS  PubMed  Google Scholar 

  86. Okuyama M et al (1997) Serum levels of soluble form of Fas molecule in patients with congestive heart failure. Am J Cardiol 79(12):1698–1701

    Article  CAS  PubMed  Google Scholar 

  87. Yamaguchi S et al (1999) Elevated circulating levels and cardiac secretion of soluble Fas ligand in patients with congestive heart failure. Am J Cardiol 83(10):1500–1503

    Article  CAS  PubMed  Google Scholar 

  88. Bedi MS et al (2008) Myocardial Fas and cytokine expression in end-stage heart failure: impact of LVAD support. ClinTransl Sci 1(3):245–248

    CAS  Google Scholar 

  89. Meisner M (2014) Update on procalcitonin measurements. Ann Lab Med 34(4):263–273

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Travaglino F et al (2014) Thirty and ninety days mortality predictive value of admission and in-hospital procalcitonin and mid-regional pro-adrenomedullin testing in patients with dyspnea. Results from the VERyfing DYspnea trial. Am J Emerg Med 32(4):334–341

    Article  PubMed  Google Scholar 

  91. Wang W et al (2014) Procalcitonin testing for diagnosis and short-term prognosis in bacterial infection complicated by congestive heart failure: a multicenter analysis of 4,698 cases. Crit Care 18(1):1–9

    Article  Google Scholar 

  92. Demissei BG et al (2016) Procalcitonin-based indication of bacterial infection identifies high risk acute heart failure patients. Int J Cardiol 204:164–171

    Article  PubMed  Google Scholar 

  93. Maisel A et al (2012) Use of procalcitonin for the diagnosis of pneumonia in patients presenting with a chief complaint of dyspnoea: results from the BACH (Biomarkers in Acute Heart Failure) trial. Eur J Heart Fail 14(3):278–286

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Alba GA et al (2016) Diagnostic and prognostic utility of procalcitonin in patients presenting to the emergency department with dyspnea. Am J Med 129(1):96–104.e7

    Article  CAS  PubMed  Google Scholar 

  95. Berezin AE (2018) Circulating biomarkers in heart failure. Adv Exp Med Biol 1067:89–108

  96. Curigliano G et al (2012) Cardiovascular toxicity induced by chemotherapy, targeted agents and radiotherapy: ESMO Clinical Practice Guidelines. Ann Oncol 23(suppl_7):155

    Article  Google Scholar 

  97. Thygesen K et al (2013) Third universal definition of myocardial infarction. Glob Heart 113(2):69–70

    Google Scholar 

  98. Sawaya H et al (2011) Early detection and prediction of cardiotoxicity in chemotherapy-treated patients. Am J Cardiol 107(9):1375–1380

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Latini R et al (2007) Prognostic value of very low plasma concentrations of troponin T in patients with stable chronic heart failure. Circulation 116(11):1242–1249

    Article  CAS  PubMed  Google Scholar 

  100. Horwich TB et al (2003) Cardiac troponin I is associated with impaired hemodynamics, progressive left ventricular dysfunction, and increased mortality rates in advanced heart failure. Circulation 108(7):833–838

    Article  CAS  PubMed  Google Scholar 

  101. Hudson MP et al (2004) Implications of elevated cardiac troponin T in ambulatory patients with heart failure: a prospective analysis. Am Heart J 147(3):546–552

    Article  CAS  PubMed  Google Scholar 

  102. La Vecchia L et al (2000) Cardiac troponin I as diagnostic and prognostic marker in severe heart failure. J Heart Lung Transplant 19(7):644–652

    Article  PubMed  Google Scholar 

  103. Peacock WF et al (2008) Cardiac troponin and outcome in acute heart failure. N Engl J Med 358(20):2117–2126

    Article  CAS  PubMed  Google Scholar 

  104. Tentzeris I et al (2011) Complementary role of copeptin and high-sensitivity troponin in predicting outcome in patients with stable chronic heart failure. Eur J Heart Fail 13(7):726–733

    Article  CAS  PubMed  Google Scholar 

  105. Xue Y et al (2011) Serial changes in high-sensitive troponin I predict outcome in patients with decompensated heart failure. Eur J Heart Fail 13(1):37–42

    Article  CAS  PubMed  Google Scholar 

  106. Ather S et al (2013) Recurrent low-level troponin I elevation is a worse prognostic indicator than occasional injury pattern in patients hospitalized with heart failure. Int J Cardiol 166(2):394–398

    Article  PubMed  Google Scholar 

  107. Sato Y et al (2001) Persistently increased serum concentrations of cardiac troponin t in patients with idiopathic dilated cardiomyopathy are predictive of adverse outcomes. Circulation 103(3):369–374

    Article  CAS  PubMed  Google Scholar 

  108. Chmurzynska A (2006) The multigene family of fatty acid-binding proteins (FABPs): function, structure and polymorphism. J Appl Genet 47(1):39–48

    Article  PubMed  Google Scholar 

  109. Berridge B, Van Vleet JF, Herman E (2013) Cardiac, vascular, and skeletal muscle systems. Haschek and Rousseaux's Handbook Toxicol Pathol III:1567–1665

    Article  Google Scholar 

  110. Viswanathan K et al (2010) Heart-type fatty acid-binding protein predicts long-term mortality and re-infarction in consecutive patients with suspected acute coronary syndrome who are troponin-negative. J Am Coll Cardiol 55(23):2590–2598

    Article  CAS  PubMed  Google Scholar 

  111. O'Donoghue M et al (2006) Prognostic utility of heart-type fatty acid binding protein in patients with acute coronary syndromes. Circulation 114(6):550–557

    Article  CAS  PubMed  Google Scholar 

  112. Setsuta K et al (2002) Use of cytosolic and myofibril markers in the detection of ongoing myocardial damage in patients with chronic heart failure. Am J Med 113(9):717–722

    Article  CAS  PubMed  Google Scholar 

  113. Kitai T et al (2017) Circulating intestinal fatty acid-binding protein (I-FABP) levels in acute decompensated heart failure. Clin Biochem 50(9):491–495

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Qian HY et al (2016) Heart-type fatty acid binding protein in the assessment of acute pulmonary embolism. Am J Med Sci 352(6):557–562

    Article  PubMed  Google Scholar 

  115. Savic-Radojevic A et al (2017) Novel biomarkers of heart failure. Adv Clin Chem 79:93–152

    Article  CAS  PubMed  Google Scholar 

  116. Francis GS (2011) Neurohormonal control of heart failure. Cleve Clin J Med 78(Suppl 1):S75–S79

    Article  PubMed  Google Scholar 

  117. Chidsey CA, Harrison DC, Braunwald E (1962) Augmentation of the plasma nor-epinephrine response to exercise in patients with congestive heart failure. N Engl J Med 267:650–654

    Article  CAS  PubMed  Google Scholar 

  118. Cohn JN et al (1984) Plasma norepinephrine as a guide to prognosis in patients with chronic congestive heart failure. N Engl J Med 311(13):819–823

    Article  CAS  PubMed  Google Scholar 

  119. Packer M (1992) The neurohormonal hypothesis: a theory to explain the mechanism of disease progression in heart failure. J Am Coll Cardiol 20(1):248–254

    Article  CAS  PubMed  Google Scholar 

  120. Latini R et al (2004) The comparative prognostic value of plasma neurohormones at baseline in patients with heart failure enrolled in Val-HeFT. Eur Heart J 25:292–299

    Article  CAS  PubMed  Google Scholar 

  121. Givertz MM, Braunwald E (2004) Neurohormones in heart failure: predicting outcomes, optimizing care. Eur Heart J 25(4):281

    Article  PubMed  Google Scholar 

  122. Jankowich MD, Wu W, Choudhary G (2016) Association of elevated plasma endothelin-1 levels with pulmonary hypertension, mortality, and heart failure in African American individuals: the Jackson Heart Study. JAMA Cardiol 1(4):461–469

    Article  PubMed  Google Scholar 

  123. Ara-Somohano C et al (2017) Evaluation of eight biomarkers to predict short-term mortality in patients with acute severe dyspnea. Minerva Anestesiol 83(8):824–835

    PubMed  Google Scholar 

  124. Teerlink JR (2005) Endothelins: pathophysiology and treatment implications in chronic heart failure. Current Heart Failure Reports 2(4):191–197

    Article  CAS  PubMed  Google Scholar 

  125. Kitamura K et al (2012) Adrenomedullin: a novel hypotensive peptide isolated from human pheochromocytoma. Biochem Biophys Res Commun 425(3):553–560

    Article  CAS  Google Scholar 

  126. Liquori ME et al (2014) Cardiac biomarkers in heart failure. Clin Biochem 47(6):327–337

    Article  CAS  PubMed  Google Scholar 

  127. Shah R et al (2012) Mid-regional pro-atrial natriuretic peptide and mid-regional pro-adrenomedullin are valuable for the evaluation of patients with acute dyspnea: results from the Pro-BNP Investigation of Dyspnea in the Emergency Department (PRIDE) study. J Am Coll Cardiol 59(13):E948–E948

    Article  Google Scholar 

  128. Bustamante A et al (2017) Sepsis biomarkers reprofiling to predict stroke-associated infections. J Neuroimmunol 312:19–23

    Article  CAS  PubMed  Google Scholar 

  129. Maisel A et al (2010) Mid-region pro-hormone markers for diagnosis and prognosis in acute dyspnea: results from the BACH (Biomarkers in Acute Heart Failure) trial. J Am Coll Cardiol 55(19):2062–2076

    Article  CAS  PubMed  Google Scholar 

  130. Odermatt J et al (2017) Pro-Adrenomedullin predicts 10-year all-cause mortality in community-dwelling patients: a prospective cohort study. BMC Cardiovasc Disord 17(1):178

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  131. Dres M et al (2017) Mid-regional pro-adrenomedullin and copeptin to predict short-term prognosis of COPD exacerbations: a multicenter prospective blinded study. International Journal of Chronic Obstructive Pulmonary Disease 12:1047–1056

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Richards AM et al (1998) Plasma N-terminal pro–brain natriuretic peptide and adrenomedullin. Circulation 97(19):1921–1929

    Article  CAS  PubMed  Google Scholar 

  133. Welsh P et al (2018) Prognostic importance of emerging cardiac, inflammatory, and renal biomarkers in chronic heart failure patients with reduced ejection fraction and anaemia: RED-HF study. Eur J Heart Fail 20(2):268–277

    Article  CAS  PubMed  Google Scholar 

  134. Schrier RW (2006) Water and sodium retention in edematous disorders: role of vasopressin and aldosterone. Am J Med 119(7):S47–S53

    Article  CAS  PubMed  Google Scholar 

  135. Maisel A et al (2011) Increased 90-day mortality in patients with acute heart failure with elevated copeptin clinical perspective. J Am Coll Cardiol 55(5):613

    Google Scholar 

  136. Sabatine MS et al (2012) Evaluation of multiple biomarkers of cardiovascular stress for risk prediction and guiding medical therapy in patients with stable coronary disease. Circulation 125(2):233–240

    Article  CAS  PubMed  Google Scholar 

  137. Remde H et al (2016) The cardiovascular markers copeptin and high-sensitive C-reactive protein decrease following specific therapy for primary aldosteronism. J Hypertens 34(10):1

    Article  CAS  Google Scholar 

  138. Moayedi Y, Ross HJ (2017) Advances in heart failure: a review of biomarkers, emerging pharmacological therapies, durable mechanical support and telemonitoring. Clin Sci 131(7):553

    Article  CAS  Google Scholar 

  139. Yan JJ et al (2017) Predictive value of plasma copeptin level for the risk and mortality of heart failure: a meta-analysis. J Cell Mol Med 21(9):1815–1825

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Sahin I et al (2016) Higher copeptin levels are associated with worse outcome in patients with hypertrophic cardiomyopathy. Clin Cardiol 40(1):32–37

    Article  PubMed  PubMed Central  Google Scholar 

  141. Hokamaki J et al (2004) Urinary biopyrrins levels are elevated in relation to severity of heart failure. J Am Coll Cardiol 43(10):1880–1885

    Article  CAS  PubMed  Google Scholar 

  142. Mcmurray J et al (1993) Evidence of oxidative stress in chronic heart failure in humans. Eur Heart J 14(11):1493–1498

    Article  CAS  PubMed  Google Scholar 

  143. Mak S et al (2000) Unsaturated aldehydes including 4-OH-nonenal are elevated in patients with congestive heart failure. J Card Fail 6(2):108–114

    Article  CAS  PubMed  Google Scholar 

  144. Tang WHW et al (2003) Plasma B-type natriuretic peptide levels in ambulatory patients with established chronic symptomatic systolic heart failure. Circulation 108(24):2964–2966

    Article  CAS  PubMed  Google Scholar 

  145. de Lemos JA et al (2009) Screening the population for left ventricular hypertrophy and left ventricular systolic dysfunction using natriuretic peptides: results from the Dallas Heart Study. Am Heart J 157(4):746–753 e2

    Article  PubMed  Google Scholar 

  146. Richards AM et al (2001) Plasma N-terminal pro-brain natriuretic peptide and adrenomedullin: prognostic utility and prediction of benefit from carvedilol in chronic ischemic left ventricular dysfunction. J Am Coll Cardiol 37(7):1781–1787

    Article  CAS  PubMed  Google Scholar 

  147. Costello-Boerrigter LC et al (2006) Amino-terminal pro-B-type natriuretic peptide and B-type natriuretic peptide in the general community: determinants and detection of left ventricular dysfunction. J Am Coll Cardiol 47(2):345–353

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Scharling H et al (2006) Plasma pro-B-type natriuretic peptide in the general population: screening for left ventricular hypertrophy and systolic dysfunction. Eur Heart J 27(24):3004–3010

    Article  PubMed  CAS  Google Scholar 

  149. McKie PM et al (2011) Predictive utility of atrial, N-terminal pro-atrial, and N-terminal pro-B-type natriuretic peptides for mortality and cardiovascular events in the general community: a 9-year follow-up study. Mayo Clin Proc 86(12):1154–1160

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Bayes-Genis A et al (2005) NT-proBNP testing for diagnosis and short-term prognosis in acute destabilized heart failure: an international pooled analysis of 1256 patients: the International Collaborative of NT-proBNP Study. Eur Heart J 27(3):330–337

    PubMed  Google Scholar 

  151. Salah K et al (2014) A novel discharge risk model for patients hospitalised for acute decompensated heart failure incorporating N-terminal pro-B-type natriuretic peptide levels: a European coLlaboration on Acute decompeNsated Heart Failure: ÉLAN-HF Score. Heart 100(2):115–125

    Article  CAS  PubMed  Google Scholar 

  152. von Haehling S et al (2007) Comparison of midregional pro-atrial natriuretic peptide with N-terminal pro-B-type natriuretic peptide in predicting survival in patients with chronic heart failure. J Am Coll Cardiol 50(20):1973–1980

    Article  CAS  Google Scholar 

  153. Tolppanen H et al (2017) Mid-regional pro-atrial natriuretic peptide to predict clinical course in heart failure patients undergoing cardiac resynchronization therapy. EP Europace 19(11):1848–1854

    Article  Google Scholar 

  154. Miller WL et al (2012) Serial measurements of midregion proANP and copeptin in ambulatory patients with heart failure: incremental prognostic value of novel biomarkers in heart failure. Heart 98(5): p. 389-94. 

    Article  PubMed  CAS  Google Scholar 

  155. Doerstling S et al (2018) Growth differentiation factor 15 in a community-based sample: age-dependent reference limits and prognostic impact. Ups J Med Sci 123(2):86–93

    Article  PubMed  PubMed Central  Google Scholar 

  156. Eggers KM et al (2013) Cardiac troponin I levels measured with a high-sensitive assay increase over time and are strong predictors of mortality in an elderly population. J Am Coll Cardiol 61(18):1906–1913

    Article  CAS  PubMed  Google Scholar 

  157. Fudim M et al (2018) High-sensitivity troponin I in hospitalized and ambulatory patients with heart failure with preserved ejection fraction: insights from the heart failure clinical research network. J Am Heart Assoc 7(24):e010364–e010364

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Castro LTd et al (2019) Elevated high-sensitivity troponin I in the stabilized phase after an acute coronary syndrome predicts all-cause and cardiovascular mortality in a highly admixed population: a 7-year cohort. Arq Bras Cardiol 112(3):230–237

    PubMed  PubMed Central  Google Scholar 

  159. Arimoto T et al (2005) Prognostic value of elevated circulating heart-type fatty acid binding protein in patients with congestive heart failure. J Card Fail 11(1):56–60

    Article  CAS  PubMed  Google Scholar 

  160. Otaki Y et al (2014) Association of heart-type fatty acid-binding protein with cardiovascular risk factors and all-cause mortality in the general population: the Takahata study. PLoS One 9(5):e94834

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  161. Jeong JH et al (2016) The prognostic value of serum levels of heart-type fatty acid binding protein and high sensitivity C-reactive protein in patients with increased levels of amino-terminal pro-B type natriuretic peptide. Ann Lab Med 36(5):420–426

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Ho S-K et al (2018) The prognostic significance of heart-type fatty acid binding protein in patients with stable coronary heart disease. Sci Rep 8(1):14410

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  163. Tang WH et al (2009) Usefulness of myeloperoxidase levels in healthy elderly subjects to predict risk of developing heart failure. Am J Cardiol 103(9):1269–1274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Reichlin T et al (2010) Use of myeloperoxidase for risk stratification in acute heart failure. Clin Chem 56(6):944–951

    Article  CAS  PubMed  Google Scholar 

  165. Brennan ML, Penn MS, Lente FV (2004) Prognostic value of myeloperoxidase in patients with chest pain. N Engl J Med 13(2):1595–1604

    Google Scholar 

  166. Ng LL et al (2006) Myeloperoxidase and C-reactive protein augment the specificity of B-type natriuretic peptide in community screening for systolic heart failure. Am Heart J 152(1):94–101

    Article  CAS  PubMed  Google Scholar 

  167. Castro PF et al (2002) Effects of early decrease in oxidative stress after medical therapy in patients with class IV congestive heart failure. Am J Cardiol 89(2):236–239

    Article  CAS  PubMed  Google Scholar 

  168. Díaz-Vélez CR et al (1996) Increased malondialdehyde in peripheral blood of patients with congestive heart failure. Am Heart J 131(1):146–152

    Article  PubMed  Google Scholar 

  169. Krishnan E (2009) Hyperuricemia and incident heart failure. Circ Heart Fail 2(6):556–562

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Palazzuoli A et al (2016) Prognostic significance of hyperuricemia in patients with acute heart failure. Am J Cardiol 117(10):1616–1621

    Article  CAS  PubMed  Google Scholar 

  171. Wannamethee SG et al (2018) Serum uric acid as a potential marker for heart failure risk in men on antihypertensive treatment: the British Regional Heart Study. Int J Cardiol 252:187–192

    Article  PubMed  PubMed Central  Google Scholar 

  172. Amin A et al (2017) On admission serum sodium and uric acid levels predict 30 day rehospitalization or death in patients with acute decompensated heart failure. Esc Heart Failure 4(2):162–168

    Article  PubMed  PubMed Central  Google Scholar 

  173. Huang G et al (2019) Prognostic value of serum uric acid in patients with acute heart failure: a meta-analysis. Medicine 98(8):e14525–e14525

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  174. Okazaki H et al (2016) Are atherosclerotic risk factors associated with a poor prognosis in patients with hyperuricemic acute heart failure? The evaluation of the causal dependence of acute heart failure and hyperuricemia. Heart Vessel 32(4):1–10

    Google Scholar 

  175. Alonso-Martínez JL et al (2002) C-reactive protein as a predictor of improvement and readmission in heart failure. Eur J Heart Fail 4(3):331–336

    Article  PubMed  Google Scholar 

  176. Park JJ et al (2014) Prognostic value of C-reactive protein as an inflammatory and N-terminal probrain natriuretic peptide as a neurohumoral marker in acute heart failure (from the Korean Heart Failure registry). Am J Cardiol 113(3):511–517

    Article  CAS  PubMed  Google Scholar 

  177. Anand IS et al (2005) C-reactive protein in heart failure. Circulation 112(10):1428–1434

    Article  CAS  PubMed  Google Scholar 

  178. Deswal A et al (2001) Cytokines and cytokine receptors in advanced heart failure. Circulation 103(16):2055–2059

    Article  CAS  PubMed  Google Scholar 

  179. Liu W et al (2019) Serum levels of inflammatory cytokines and expression of BCL2 and BAX mRNA in peripheral blood mononuclear cells and in patients with chronic heart failure. Med Sci Monit 25:2633–2639

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Vasan RS et al (2003) Inflammatory markers and risk of heart Failure in elderly subjects without prior myocardial infarction. Circulation 107(11):1486–1491

    Article  CAS  PubMed  Google Scholar 

  181. Canbay A et al (2015) Procalcitonin: a marker of heart failure. Acta Cardiol 70(4):473–478

    Article  PubMed  Google Scholar 

  182. Ahmad T et al (2014) Biomarkers of myocardial stress and fibrosis as predictors of mode of death in patients with chronic heart failure. JACC: Heart Failure 2(3):260–268

    PubMed  Google Scholar 

  183. Bayes-Genis A et al (2014) Head-to-head comparison of 2 myocardial fibrosis biomarkers for long-term heart failure risk stratification: ST2 versus galectin-3. J Am Coll Cardiol 63(2):158–166

    Article  CAS  PubMed  Google Scholar 

  184. Gaggin HK et al (2014) Head-to-head comparison of serial soluble ST2, growth differentiation factor-15, and highly-sensitive troponin T measurements in patients with chronic heart failure. Jacc Heart Failure 2(1):65

    Article  PubMed  Google Scholar 

  185. Shah RV et al (2010) Galectin-3, cardiac structure and function, and long-term mortality in patients with acutely decompensated heart failure. Eur J Heart Fail 12(8):826–832

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. Boer RA (2011) De, et al., Predictive value of plasma galectin-3 levels in heart failure with reduced and preserved ejection fraction. Ann Med 43(1):60–68

    Article  PubMed  CAS  Google Scholar 

  187. van Vark LC et al (2017) Prognostic value of serial galectin-3 measurements in patients with acute heart failure. J Am Heart Assoc 6(12):e003700

    PubMed  PubMed Central  Google Scholar 

  188. Anand IS et al (2003) Changes in brain natriuretic peptide and norepinephrine over time and mortality and morbidity in the Valsartan Heart Failure Trial (Val-HeFT). Circulation 107(9):1278–1283

    Article  CAS  PubMed  Google Scholar 

  189. Ix JH et al (2007) Association of cystatin C with mortality, cardiovascular events, and incident heart failure among persons with coronary heart disease: data from the Heart and Soul Study. Circulation 115(2):173–179

    Article  CAS  PubMed  Google Scholar 

  190. Kim TH, Kim H, Kim IC (2015) The potential of cystatin-C to evaluate the prognosis of acute heart failure: a comparative study. Int J Cardiovasc Interv 17(4):72–76

    Google Scholar 

  191. Chen S, Tang Y, Zhou X (2019) Cystatin C for predicting all-cause mortality and rehospitalization in patients with heart failure: a meta-analysis. Biosci Rep 39(2):BSR20181761

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  192. Damman K et al (2011) Clinical outcome of renal tubular damage in chronic heart failure. Eur Heart J 32(21):2705–2712

    Article  CAS  PubMed  Google Scholar 

  193. Deursen VMV et al (2014) Prognostic value of plasma neutrophil gelatinase-associated lipocalin for mortality in patients with heart failure. Circ Heart Fail 7(1):35–42

    Article  PubMed  CAS  Google Scholar 

  194. Kirbiš S, Gorenjak M, Sinkovič A (2015) The role of urine neutrophil gelatinase-associated lipocalin (NGAL) in acute heart failure in patients with ST-elevation myocardial infarction. BMC Cardiovasc Disord 15:49–49

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  195. Sokolski M et al (2017) Urinary levels of novel kidney biomarkers and risk of true worsening renal function and mortality in patients with acute heart failure. Eur J Heart Fail 19(6):760–767

    Article  CAS  PubMed  Google Scholar 

  196. Maisel AS et al (2016) Neutrophil gelatinase-associated lipocalin for acute kidney injury during acute heart failure hospitalizations : the AKINESIS study. J Am Coll Cardiol 68(13):1420–1431

    Article  CAS  PubMed  Google Scholar 

  197. Damman K et al (2017) Plasma neutrophil gelatinase-associated lipocalin and predicting clinically relevant worsening renal function in acute heart failure. Int J Mol Sci 18(7):1470

    Article  PubMed Central  CAS  Google Scholar 

  198. Trachtenberg BH, Hare JM (2009) Biomarkers of oxidative stress in heart failure. Heart Fail Clin 5(4):561–577

    Article  PubMed  Google Scholar 

  199. Tang WHW et al (2006) Plasma myeloperoxidase levels in patients with chronic heart Failure. Am J Cardiol 98(6):796–799

    Article  CAS  PubMed  Google Scholar 

  200. Cabassi A et al (2015) Myeloperoxidase-related chlorination activity is positively associated with circulating ceruloplasmin in chronic heart failure patients: relationship with neurohormonal, inflammatory, and nutritional parameters. Biomed Res Int 2015(11):1–10

    Article  CAS  Google Scholar 

  201. Shah KB et al (2009) Lack of diagnostic and prognostic utility of circulating plasma myeloperoxidase concentrations in patients presenting with dyspnea. Clin Chem 55(1):59–67

    Article  CAS  PubMed  Google Scholar 

  202. Mann EBDL and Mann DL, Heart failure:a companion to Braunwald’s heart disease. Elsevier/Saunders

  203. Gan L-M et al (2019) Safety, tolerability, pharmacokinetics and effect on serum uric acid of the myeloperoxidase inhibitor AZD4831 in a randomized, placebo-controlled, phase I study in healthy volunteers. Br J Clin Pharmacol 85(4):762–770

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  204. George J et al (2006) High-dose allopurinol improves endothelial function by profoundly reducing vascular oxidative stress and not by lowering uric acid. Circulation 114(23):2508–2516

    Article  CAS  PubMed  Google Scholar 

  205. Otaki Y et al (2017) Association of plasma xanthine oxidoreductase activity with severity and clinical outcome in patients with chronic heart failure. Int J Cardiol 228:151–157

    Article  PubMed  Google Scholar 

  206. Hare JM et al (2008) Impact of oxypurinol in patients with symptomatic heart failure: results of the OPT-CHF study. J Am Coll Cardiol 51(24):2301–2309

    Article  CAS  PubMed  Google Scholar 

  207. Masaki N et al (2016) Usefulness of the d-ROMs test for prediction of cardiovascular events. Int J Cardiol 222:226–232

    Article  PubMed  Google Scholar 

  208. Hitsumoto T (2018) Efficacy of the reactive oxygen metabolite test as a predictor of initial heart failure hospitalization in elderly patients with chronic heart failure. Cardiol Res 9(3):153–160

    Article  PubMed  PubMed Central  Google Scholar 

  209. Mann DL, Felker MG (2015) Heart Failure. Tex Heart Inst J 33(2625):965

    Google Scholar 

  210. Hyungseop Kim MD et al (2013) Potentials of cystatin C and uric acid for predicting prognosis of heart failure. Congestive Heart Failure 19(3):123

    Article  PubMed  CAS  Google Scholar 

  211. Berezin AE (2017) Up-to-date clinical approaches of biomarkers’ use in heart failure. Biomedical Research and Therapy 4(6):1344

    Article  Google Scholar 

  212. de Boer RA et al (2015) State of the art: newer biomarkers in heart failure. Eur J Heart Fail 17(6):559–569

    Article  PubMed  CAS  Google Scholar 

  213. Nickolas TL et al (2012) Diagnostic and prognostic stratification in the emergency department using urinary biomarkers of nephron damage. A multicenter prospective cohort study. J Am Coll Cardiol 59(3):246–255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  214. Ky B et al (2012) Multiple biomarkers for risk prediction in chronic heart failure. Circ Heart Fail 5(2):183

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  215. Demissei BG et al (2017) A multimarker multi-time point-based risk stratification strategy in acute heart failure: results from the RELAX-AHF trial. Eur J Heart Fail 19(8):1001–1010

    Article  CAS  PubMed  Google Scholar 

  216. Piek A et al (2018) Novel heart failure biomarkers: why do we fail to exploit their potential? Crit Rev Clin Lab Sci 55(4):246–263

    Article  CAS  PubMed  Google Scholar 

  217. Evans GA (2000) Designer science and the “omic” revolution. Nat Biotechnol 18(2):127–120

    Article  CAS  PubMed  Google Scholar 

  218. Apple FS et al (2017) Cardiovascular disease: impact of biomarkers, proteomics, and genomics. Clin Chem 63(1):1–4

    Article  CAS  PubMed  Google Scholar 

  219. Edwards AV, White MY, Cordwell SJ (2008) The role of proteomics in clinical cardiovascular biomarker discovery. Mol Cell Proteomics 7(10):1824–1837

    Article  CAS  PubMed  Google Scholar 

  220. P Cappola T et al (2011) Loss-of-function DNA sequence variant in the CLCNKA chloride channel implicates the cardio-renal axis in interindividual heart failure risk variation. Proc Natl Acad Sci U S A 108:2456–2461

    Article  PubMed  Google Scholar 

  221. Villard E et al (2011) Editor’s choice: fast track: a genome-wide association study identifies two loci associated with heart failure due to dilated cardiomyopathy. Eur Heart J 32(9):1065

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  222. Berezin A (2016) Epigenetically modified endothelial progenitor cells in heart failure. J Clin Epigenet 2:2

    Google Scholar 

  223. Serie DJ et al (2017) Genome-wide association study of cardiotoxicity in the NCCTG N9831 (Alliance) adjuvant trastuzumab trial. Pharmacogenet Genomics 27(10):378–385

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  224. Wells QS et al (2017) Genome-wide association and pathway analysis of left ventricular function after anthracycline exposure in adults. Pharmacogenet Genomics 27(7):247

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  225. Kessler T, Vilne B, Schunkert H (2016) The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular disease. Embo Mol Med 8(7):688–701

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  226. McPherson R, Tybjaerg-Hansen A (2016) Genetics of coronary artery disease. Circ Res 118:564–578

    Article  CAS  PubMed  Google Scholar 

  227. Yang J, Xu WW, Hu SJ (2015) Heart failure: advanced development in genetics and epigenetics. Biomed Res Int 2015(2):1–11

    CAS  Google Scholar 

  228. Abraham G et al (2016) Genomic prediction of coronary heart disease. Eur Heart J 37(43):3267–3278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  229. Napoli C et al (2016) Novel epigenetic-based therapies useful in cardiovascular medicine. World J Cardiol 8(2):211–219

    Article  PubMed  PubMed Central  Google Scholar 

  230. Movassagh M et al (2011) Distinct epigenomic features in end-stage failing human hearts. Circulation 124(22):2411–2422

    Article  PubMed  PubMed Central  Google Scholar 

  231. Haas J et al (2013) Alterations in cardiac DNA methylation in human dilated cardiomyopathy. Embo Mol Med 5(3):413–429

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  232. Meder B et al (2017) Epigenome-wide association study identifies cardiac gene patterning and a novel class of biomarkers for heart failure. Circulation 136(16):1528

    Article  CAS  PubMed  Google Scholar 

  233. Shu L, Arneson D, and Yang X, (2018) Bioinformatics principles for deciphering cardiovascular diseases. Encyclopedia of Cardiovascular Research and Medicine, 273–292.

  234. Gora M, Marek K, Beata B (2013) Will global transcriptome analysis allow the detection of novel prognostic markers in coronary artery disease and heart failure? Current Genomics 14(6):388–396

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  235. Costa V et al (2013) RNA-Seq and human complex diseases: recent accomplishments and future perspectives. Eur J Hum Genet 21(2):134

    Article  CAS  PubMed  Google Scholar 

  236. Ounzain S et al (2015) Fast track: editor’s choice: genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs. Eur Heart J 36(6):353

    Article  CAS  PubMed  Google Scholar 

  237. Schiano C et al (2017) Heart failure: pilot transcriptomic analysis of cardiac tissue by RNA-sequencing. Cardiol J 24(5):539–553

    Article  PubMed  Google Scholar 

  238. Toma M et al (2017) Differentiating heart failure phenotypes using sex-specific transcriptomic and proteomic biomarker panels. Esc Heart Fail 4(3):301–311

    Article  PubMed  PubMed Central  Google Scholar 

  239. Rabani V, Davani S (2017) Translational approaches in cardiovascular diseases by omics. Curr Issues Mol Biol 28:1–14

    PubMed  Google Scholar 

  240. Mebazaa A et al (2012) Unbiased plasma proteomics for novel diagnostic biomarkers in cardiovascular disease: identification of quiescin Q6 as a candidate biomarker of acutely decompensated heart failure. Eur Heart J 33(18):2317–2324

    Article  CAS  PubMed  Google Scholar 

  241. DeAguero JL et al (2017) Altered protein levels in the isolated extracellular matrix of failing human hearts with dilated cardiomyopathy. Cardiovasc Pathol 26:12–20

    Article  CAS  PubMed  Google Scholar 

  242. Raphael R et al (2016) Combining patient proteomics and in vitro cardiomyocyte phenotype testing to identify potential mediators of heart failure with preserved ejection fraction. J Transl Med 14(1):18

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  243. Stenemo M et al (2018) Circulating proteins as predictors of incident heart failure in the elderly. Eur J Heart Fail 20(1):55–62

    Article  CAS  PubMed  Google Scholar 

  244. Arab S et al (2006) Cardiovascular proteomics : tools to develop novel biomarkers and potential applications. J Am Coll Cardiol 48(9):1733–1741

    Article  CAS  PubMed  Google Scholar 

  245. Cheng S et al (2017) Potential impact and study considerations of metabolomics in cardiovascular health and disease: a scientific statement from the American Heart Association. Circ Cardiovasc Genet 10(2):e000032

    Article  PubMed  PubMed Central  Google Scholar 

  246. Hunter WG et al (2016) Metabolomic profiling identifies novel circulating biomarkers of mitochondrial dysfunction differentially elevated in heart failure with preserved versus reduced ejection fraction: evidence for shared metabolic impairments in clinical heart failure. J Am Heart Assoc 5(8):e003190

    Article  PubMed  PubMed Central  Google Scholar 

  247. Ahmad T et al (2016) Prognostic implications of long-chain acylcarnitines in heart failure and reversibility with mechanical circulatorysupport. J Am Coll Cardiol 67(3):291–299

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  248. Shu, L., et al., (2016) Mergeomics: integration of diverse genomics resources to identify pathogenic perturbations to biological systems. bioRxiv preprint; Jan. 7, 2016. https://doi.org/10.1101/036012

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Funding

This study is supported by grants from the National Natural Science Foundation of China (NSFC 81774050), Tianjin Outstanding Youth Science Foundation (17JCJQJC46200), the Natural Science Foundation of Tianjin (17JCYBJC29000), and State Key Development Program for Basic Research of China (973 Program, No. 2012CB518404).

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  1. First teaching hospital of Tianjin University of Traditional Chinese Medicine, Number 314 Anshanxi Road, Nankai District, Tianjin, China

    Michael Sarhene, Yili Wang, Jing Wei, Yuting Huang, Min Li, Lan Li, Zhou Zhengcan, Qin Xiaoyan, Xu Yunsheng, Mao Jingyuan & Fan Guanwei

  2. State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China

    Michael Sarhene, Yili Wang, Jing Wei, Yuting Huang, Min Li, Lan Li, Enoch Acheampong, Zhou Zhengcan, Qin Xiaoyan, Xu Yunsheng, Gao Xiumei & Fan Guanwei

  3. Tianjin Laboratory of Translational Research of TCM Prescription and Syndrome, Tianjin, 300193, China

    Michael Sarhene, Yili Wang, Jing Wei, Yuting Huang, Min Li & Lan Li

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  1. Michael Sarhene
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Sarhene, M., Wang, Y., Wei, J. et al. Biomarkers in heart failure: the past, current and future. Heart Fail Rev 24, 867–903 (2019). https://doi.org/10.1007/s10741-019-09807-z

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