Skip to main content

Precision Medicine and Personalized Medicine in Cardiovascular Disease

  • Chapter
  • First Online:
Sex-Specific Analysis of Cardiovascular Function

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1065))

Abstract

Precision medicine aims to offer “the right treatment to the right patient at the right time.” In cardiovascular medicine the potential of precision medicine applies to all stages of the disease development and includes risk prediction, preventative measures, and targeted therapeutic approaches. Precision medicine will benefit from new developments in the area of genomics and other omics but equally heavily depends on established biomarkers, functional tests, and imaging. Cardiovascular medicine often relies on noninvasive diagnostic procedures and symptom-based disease management. In contrast, other clinical disciplines including oncology and immunology have already moved to molecular diagnostics that lend themselves to precision medicine approaches. There are opportunities to implement precision medicine approaches by focusing on common diseases such as hypertension, conditions with diagnostic and prognostic uncertainty such as angina, and conditions that are associated with high mortality and involve costly and potentially harmful interventions such as dilated cardiomyopathy and cardiac resynchronization therapy. Sex and gender issues have not yet been fully explored in precision medicine although the opportunity to use molecular data to more accurately manage men and women with cardiovascular disease has been acknowledged. A mindshift is required in order to fully exploit the potential of precision medicine to tackle the global burden of cardiovascular diseases.

Precision medicine. Artwork by Piet Michiels, Leuven, Belgium

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Roffi M, Patrono C, Collet JP, Mueller C, Valgimigli M, Andreotti F, et al. 2015 ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: task force for the Management of Acute Coronary Syndromes in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2016;37(3):267–315.

    Article  CAS  PubMed  Google Scholar 

  2. 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(7):1281–357.

    Article  CAS  PubMed  Google Scholar 

  3. American Diabetes Association. 2. Classification and diagnosis of diabetes. Diabetes Care. 2017;40(Suppl 1):S11–24.

    Article  Google Scholar 

  4. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, 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. 2016;37(27):2129–200.

    Article  PubMed  Google Scholar 

  5. Medical Research Council. Stratified medicine. https://www.mrc.ac.uk/research/initiatives/stratified-medicine/. Accessed 7 Jan 2018.

  6. National Health Service. Improving outcomes through personalised medicine. https://www.england.nhs.uk/wp-content/uploads/2016/09/improving-outcomes-personalised-medicine.pdf. Accessed 7 Jan 2018.

  7. National Research Council (US) Committee on A framework for developing a new taxonomy of disease. Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease. Washington, DC: National Academic Press (US); 2011.

    Google Scholar 

  8. President Obama’s Precision Medicine Initiative. https://obamawhitehouse.archives.gov/the-press-office/2015/01/30/fact-sheet-president-obama-s-precision-medicine-initiative. Accessed 7 Jan 2018.

  9. Smith R. Stratified, personalised, or precision medicine. http://blogs.bmj.com/bmj/2012/10/15/richard-smith-stratified-personalised-or-precision-medicine/. Accessed 7 Jan 2018.

  10. Dominiczak A, Delles C, Padmanabhan S. Genomics and precision medicine for clinicians and scientists in hypertension. Hypertension. 2017;69(4):e10–3.

    Article  CAS  PubMed  Google Scholar 

  11. Konig IR, Fuchs O, Hansen G, von Mutius E, Kopp MV. What is precision medicine? Eur Respir J. 2017;50(4):1700391.

    Article  PubMed  Google Scholar 

  12. GBD 2013 Mortality and Causes of Death Collaborators. 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. 2015;385(9963):117–71.

    Article  Google Scholar 

  13. Dzau VJ, Ginsburg GS, Van Nuys K, Agus D, Goldman D. Aligning incentives to fulfil the promise of personalised medicine. Lancet. 2015;385(9982):2118–9.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet. 2017;389(10085):2239–51.

    Article  CAS  PubMed  Google Scholar 

  15. Dorajoo R, Liu J, Boehm BO. Genetics of type 2 diabetes and clinical utility. Genes (Basel). 2015;6(2):372–84.

    Article  CAS  Google Scholar 

  16. Rossi GP. Prevalence and diagnosis of primary aldosteronism. Curr Hypertens Rep. 2010;12(5):342–8.

    Article  PubMed  Google Scholar 

  17. Azizan EA, Brown MJ. Novel genetic determinants of adrenal aldosterone regulation. Curr Opin Endocrinol Diabetes Obes. 2016;23(3):209–17.

    Article  CAS  PubMed  Google Scholar 

  18. Ji W, Foo JN, O’Roak BJ, Zhao H, Larson MG, Simon DB, et al. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat Genet. 2008;40(5):592–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Titze J. Sodium balance is not just a renal affair. Curr Opin Nephrol Hypertens. 2014;23(2):101–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. National Institute for Health and Clinical Excellence. Hypertension in adults: diagnosis and management. https://www.nice.org.uk/guidance/cg127. Accessed 7 Jan 2018.

  21. Buhler FR, Burkart F, Lutold BE, Kung M, Marbet G, Pfisterer M. Antihypertensive beta blocking action as related to renin and age: a pharmacologic tool to identify pathogenetic mechanisms in essential hypertension. Am J Cardiol. 1975;36(5):653–69.

    Article  CAS  PubMed  Google Scholar 

  22. 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(10008):2059–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Shah SJ. Precision medicine for heart failure with preserved ejection fraction: an overview. J Cardiovasc Transl Res. 2017;10(3):233–44.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Shah SJ. Innovative clinical trial designs for precision medicine in heart failure with preserved ejection fraction. J Cardiovasc Transl Res. 2017;10(3):322–36.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Olsen MH, Angell SY, Asma S, Boutouyrie P, Burger D, Chirinos JA, et al. A call to action and a lifecourse strategy to address the global burden of raised blood pressure on current and future generations: the lancet commission on hypertension. Lancet. 2016;388(10060):2665–712.

    Article  PubMed  Google Scholar 

  26. Musunuru K, Hickey KT, Al-Khatib SM, Delles C, Fornage M, Fox CS, et al. Basic concepts and potential applications of genetics and genomics for cardiovascular and stroke clinicians: a scientific statement from the American Heart Association. Circ Cardiovasc Genet. 2015;8(1):216–42.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Cavallari LH, Lee CR, Beitelshees AL, RM C-DH, Duarte JD, Voora D, et al. Multisite investigation of outcomes with implementation of CYP2C19 genotype-guided antiplatelet therapy after percutaneous coronary intervention. JACC Cardiovasc Interv. 2017;11(2):181–91.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Wald NJ, Law MR. A strategy to reduce cardiovascular disease by more than 80%. BMJ. 2003;326(7404):1419.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Topol EJ. Individualized medicine from prewomb to tomb. Cell. 2014;157(1):241–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Snyderman R. Personalized health care: from theory to practice. Biotechnol J. 2012;7(8):973–9.

    Article  CAS  PubMed  Google Scholar 

  31. US Department of Veterans Affairs. VA Million Veteran Program linked to precision medicine effort. https://www.research.va.gov/pubs/varqu/spring2016/13.cfm. Accessed 7 Jan 2018.

  32. UK Biobank. http://www.ukbiobank.ac.uk/. Accessed 7 Jan 2018.

  33. Dzau V, Braunwald E. Resolved and unresolved issues in the prevention and treatment of coronary artery disease: a workshop consensus statement. Am Heart J. 1991;121(4 Pt 1):1244–63.

    Article  CAS  PubMed  Google Scholar 

  34. Padmanabhan S, Joe B. Towards precision medicine for hypertension: a review of genomic, Epigenomic, and Microbiomic effects on blood pressure in experimental rat models and humans. Physiol Rev. 2017;97(4):1469–528.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Sun D, Liu J, Xiao L, Liu Y, Wang Z, Li C, et al. Recent development of risk-prediction models for incident hypertension: an updated systematic review. PLoS One. 2017;12(10):e0187240.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Savoia C, Volpe M, Grassi G, Borghi C, Agabiti Rosei E, Touyz RM. Personalized medicine-a modern approach for the diagnosis and management of hypertension. Clin Sci (Lond). 2017;131(22):2671–85.

    Article  CAS  Google Scholar 

  37. Ladapo JA, Budoff M, Sharp D, Zapien M, Huang L, Maniet B, et al. Clinical utility of a precision medicine test evaluating outpatients with suspected obstructive coronary artery disease. Am J Med. 2017;130(4):482. e411–482.e417

    Article  PubMed  Google Scholar 

  38. Niccoli G, Montone RA, Lanza GA, Crea F. Angina after percutaneous coronary intervention: the need for precision medicine. Int J Cardiol. 2017;248:14–9.

    Article  PubMed  Google Scholar 

  39. Halliday BP, Cleland JGF, Goldberger JJ, Prasad SK. Personalizing risk stratification for sudden death in dilated cardiomyopathy: the past, present, and future. Circulation. 2017;136(2):215–31.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Kinnamon DD, Morales A, Bowen DJ, Burke W, Hershberger RE, DCM Consortium*. Toward genetics-driven early intervention in dilated cardiomyopathy: design and implementation of the DCM precision medicine study. Circ Cardiovasc Genet. 2017;10(6):e001826.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Nassif ME, Tang Y, Cleland JG, Abraham WT, Linde C, Gold MR, et al. Precision medicine for cardiac resynchronization: predicting quality of life benefits for individual patients-an analysis from 5 clinical trials. Circ Heart Fail. 2017;10(10):e004111.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Thanassoulis G, Peloso GM, Pencina MJ, Hoffmann U, Fox CS, Cupples LA, et al. A genetic risk score is associated with incident cardiovascular disease and coronary artery calcium: the Framingham heart study. Circ Cardiovasc Genet. 2012;5(1):113–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Berinstein E, Levy A. Recent developments and future directions for the use of pharmacogenomics in cardiovascular disease treatments. Expert Opin Drug Metab Toxicol. 2017;13(9):973–83.

    Article  CAS  PubMed  Google Scholar 

  44. Tuteja S, Limdi N. Pharmacogenetics in cardiovascular medicine. Curr Genet Med Rep. 2016;4(3):119–29.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Jie Z, Xia H, Zhong SL, Feng Q, Li S, Liang S, et al. The gut microbiome in atherosclerotic cardiovascular disease. Nat Commun. 2017;8(1):845.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Richard MA, Huan T, Ligthart S, Gondalia R, Jhun MA, Brody JA, et al. DNA methylation analysis identifies loci for blood pressure regulation. Am J Hum Genet. 2017;101(6):888–902.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Chu AY, Tin A, Schlosser P, Ko YA, Qiu C, Yao C, et al. Epigenome-wide association studies identify DNA methylation associated with kidney function. Nat Commun. 2017;8(1):1286.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Li J, Zhu X, Yu K, Jiang H, Zhang Y, Deng S, et al. Genome-wide analysis of DNA methylation and acute coronary syndrome. Circ Res. 2017;120(11):1754–67.

    Article  CAS  PubMed  Google Scholar 

  49. Ligthart S, Marzi C, Aslibekyan S, Mendelson MM, Conneely KN, Tanaka T, et al. DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. Genome Biol. 2016;17(1):255.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Mendelson MM, Marioni RE, Joehanes R, Liu C, Hedman AK, Aslibekyan S, et al. Association of Body Mass Index with DNA methylation and gene expression in blood cells and relations to Cardiometabolic disease: a Mendelian randomization approach. PLoS Med. 2017;14(1):e1002215.

    Article  PubMed  PubMed Central  Google Scholar 

  51. 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(9):852–72.

    Article  CAS  PubMed  Google Scholar 

  52. Delles C, Schiffer E, von Zur Muhlen C, Peter K, Rossing P, Parving HH, et al. Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals. J Hypertens. 2010;28(11):2316–22.

    Article  CAS  PubMed  Google Scholar 

  53. 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(11):2424–37.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Carty DM, Siwy J, Brennand JE, Zurbig P, Mullen W, Franke J, et al. Urinary proteomics for prediction of preeclampsia. Hypertension. 2011;57(3):561–9.

    Article  CAS  PubMed  Google Scholar 

  55. 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(6):1281–8.

    Article  CAS  PubMed  Google Scholar 

  56. Brown CE, McCarthy NS, Hughes AD, Sever P, Stalmach A, Mullen W, et al. Urinary proteomic biomarkers to predict cardiovascular events. Proteomics Clin Appl. 2015;9(5–6):610–7.

    Article  CAS  PubMed  Google Scholar 

  57. Williams SA, Murthy AC, DeLisle RK, Hyde C, Malarstig A, Ostroff R, et al. Improving assessment of drug safety through proteomics: early detection and mechanistic characterization of the unforeseen harmful effects of Torcetrapib. Circulation. 2017;37(10):999–1010.

    Article  CAS  Google Scholar 

  58. Yin X, Baig F, Haudebourg E, Blankley RT, Gandhi T, Muller S, et al. Plasma proteomics for epidemiology: increasing throughput with standard-flow rates. Circ Cardiovasc Genet. 2017;10(6):e001808.

    Article  CAS  PubMed  Google Scholar 

  59. Barba I, Andres M, Dorado DG. Metabolomics and heart diseases: from basic to clinical approach. Curr Med Chem. 2017. https://doi.org/10.2174/0929867324666171006151408.

  60. Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikainen LP, et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet. 2012;44(3):269–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Delles C, Rankin NJ, Boachie C, McConnachie A, Ford I, Kangas A, et al. Nuclear magnetic resonance-based metabolomics identifies phenylalanine as a novel predictor of incident heart failure hospitalisation: results from PROSPER and FINRISK 1997. Eur J Heart Fail. 2017. https://doi.org/10.1002/ejhf.1076.

  62. 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(2):422–9.

    Article  CAS  PubMed  Google Scholar 

  63. Beger RD, Dunn W, Schmidt MA, Gross SS, Kirwan JA, Cascante M, et al. Metabolomics enables precision medicine: “A white paper, community perspective”. Metabolomics. 2016;12(10):149.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Lawler PR, Akinkuolie AO, Harada P, Glynn RJ, Chasman DI, Ridker PM, et al. Residual risk of atherosclerotic cardiovascular events in relation to reductions in very-low-density lipoproteins. J Am Heart Assoc. 2017;6(12):e007402.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. McInnes IB, Thompson L, Giles JT, Bathon JM, Salmon JE, Beaulieu AD, et al. Effect of interleukin-6 receptor blockade on surrogates of vascular risk in rheumatoid arthritis: MEASURE, a randomised, placebo-controlled study. Ann Rheum Dis. 2015;74(4):694–702.

    Article  CAS  PubMed  Google Scholar 

  66. Dibble EH, Yoo DC. Precision medicine and PET/computed tomography in cardiovascular disorders. PET Clin. 2017;12(4):459–73.

    Article  PubMed  Google Scholar 

  67. Teague HL, Ahlman MA, Alavi A, Wagner DD, Lichtman AH, Nahrendorf M, et al. Unraveling vascular inflammation: from immunology to imaging. J Am Coll Cardiol. 2017;70(11):1403–12.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Futier E, Lefrant JY, Guinot PG, Godet T, Lorne E, Cuvillon P, et al. Effect of individualized vs standard blood pressure management strategies on postoperative organ dysfunction among high-risk patients undergoing major surgery: a randomized clinical trial. JAMA. 2017;318(14):1346–57.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Bundhun PK, Gupta C, Huang F. Should fraction flow reserve be considered an important decision-making tool to stratify patients with stable coronary artery disease for percutaneous coronary intervention?: a meta-analysis. Medicine (Baltimore). 2017;96(46):e8748.

    Article  Google Scholar 

  70. Lucas JE, Bazemore TC, Alo C, Monahan PB, Voora D. An electronic health record based model predicts statin adherence, LDL cholesterol, and cardiovascular disease in the United States military health system. PLoS One. 2017;12(11):e0187809.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Wu PY, Cheng CW, Kaddi C, Venugopalan J, Hoffman R, Wang MD. Advanced big data analytics for -Omic data and electronic health records: toward precision medicine. IEEE Trans Biomed Eng. 2017;64(2):263–3.

    Google Scholar 

  72. Brody JA, Morrison AC, Bis JC, O’Connell JR, Brown MR, Huffman JE, et al. Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology. Nat Genet. 2017;49(11):1560–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Goldstein BA, Navar AM, Carter RE. Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges. Eur Heart J. 2017;38(23):1805–14.

    PubMed  Google Scholar 

  74. Krittanawong C, Zhang H, Wang Z, Aydar M, Kitai T. Artificial intelligence in precision cardiovascular medicine. J Am Coll Cardiol. 2017;69(21):2657–64.

    Article  PubMed  Google Scholar 

  75. Capelli C, Sauvage E, Giusti G, Bosi GM, Ntsinjana H, Carminati M, et al. Patient-specific simulations for planning treatment in congenital heart disease. Interface Focus. 2018;8(1):20170021.

    Article  PubMed  Google Scholar 

  76. Mangion K, Gao H, Husmeier D, Luo X, Berry C. Advances in computational modelling for personalised medicine after myocardial infarction. Heart. 2017;104(7):550–7.

    Article  PubMed  Google Scholar 

  77. Ye S, Kronish IM. To persist or not to persist: learning from precision medicine to optimize statin adherence. Rev Esp Cardiol (Engl Ed). 2018;71(1):4–5.

    Article  Google Scholar 

  78. Day S, Coombes RC, McGrath-Lone L, Schoenborn C, Ward H. Stratified, precision or personalised medicine? Cancer services in the ‘real world’ of a London hospital. Sociol Health Illn. 2017;39(1):143–58.

    Article  PubMed  Google Scholar 

  79. Mukherjee C, Sweet KM, Luzum JA, Abdel-Rasoul M, Christman MF, Kitzmiller JP. Clinical pharmacogenomics: patient perspectives of pharmacogenomic testing and the incidence of actionable test results in a chronic disease cohort. Per Med. 2017;14(5):383–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM Jr, Kastelein JJ, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med. 2008;359(21):2195–207.

    Article  CAS  PubMed  Google Scholar 

  81. SPRINT Research Group, Wright JT Jr, 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(22):2103–16.

    Article  CAS  Google Scholar 

  82. 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(3):e010310.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Academy of Medical Sciences. Realising the potential of stratified medicine. https://acmedsci.ac.uk/viewFile/51e915f9f09fb.pdf. Accessed 7 Jan 2018.

  84. Latosinska A, Frantzi M, Vlahou A, Merseburger AS, Mischak H. Clinical proteomics for precision medicine: the bladder cancer case. Proteomics Clin Appl. 2017;12(2). https://doi.org/10.1002/prca.201700074.

    Article  CAS  Google Scholar 

  85. Feldman AM, Kontos CD, McClung JM, Gerhard GS, Khalili K, Cheung JY. Precision medicine for heart failure: lessons from oncology. Circ Heart Fail. 2017;10(6):e004202.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Chang HM, Moudgil R, Scarabelli T, Okwuosa TM, Yeh ETH. Cardiovascular complications of Cancer therapy: best practices in diagnosis, prevention, and management: part 1. J Am Coll Cardiol. 2017;70(20):2536–51.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Chang HM, Okwuosa TM, Scarabelli T, Moudgil R, Yeh ETH. Cardiovascular complications of Cancer therapy: best practices in diagnosis, prevention, and management: part 2. J Am Coll Cardiol. 2017;70(20):2552–65.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Melloni C, Berger JS, Wang TY, Gunes F, Stebbins A, Pieper KS, et al. Representation of women in randomized clinical trials of cardiovascular disease prevention. Circ Cardiovasc Qual Outcomes. 2010;3(2):135–42.

    Article  PubMed  Google Scholar 

  89. Reckelhoff JF, Cordozo LLY. As precision medicine becomes more important, is it finally time for increased emphasis on gender medicine? Biochemist. 2017;39:4–5.

    CAS  Google Scholar 

  90. Miller VM, Rocca WA, Faubion SS. Sex differences research, precision medicine, and the future of Women’s health. J Womens Health (Larchmt). 2015;24(12):969–71.

    Article  Google Scholar 

  91. Mata DA, Katchi FM, Ramasamy R. Precision medicine and men’s health. Am J Mens Health. 2017;11(4):1124–9.

    Article  PubMed  Google Scholar 

  92. Te Riet L, van Esch JH, Roks AJ, van den Meiracker AH, Danser AH. Hypertension: renin-angiotensin-aldosterone system alterations. Circ Res. 2015;116(6):960–75.

    Article  CAS  Google Scholar 

  93. Giannakopoulou E, Konstantinou F, Ragia G, Tavridou A, Karaglani M, Chatzaki E, et al. Epigenetics-by-sex interaction for coronary artery disease risk conferred by the cystathionine gamma-Lyase gene promoter methylation. OMICS. 2017;21(12):741–8.

    Article  CAS  PubMed  Google Scholar 

  94. Baetta R, Pontremoli M, Martinez Fernandez A, Spickett CM, Banfi C. Proteomics in cardiovascular diseases: unveiling sex and gender differences in the era of precision medicine. J Proteome. 2017;173:62–76.

    Article  CAS  Google Scholar 

  95. Franconi F, Campesi I. Pharmacogenomics, pharmacokinetics and pharmacodynamics: interaction with biological differences between men and women. Br J Pharmacol. 2014;171(3):580–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Gaignebet L, Kararigas G. En route to precision medicine through the integration of biological sex into pharmacogenomics. Clin Sci (Lond). 2017;131(4):329–42.

    Article  CAS  Google Scholar 

  97. Academy of Medical Sciences. Stratified, personalised or P4 medicine: a new direction for placing the patient at the centre of healthcare and health education. May 2015. https://acmedsci.ac.uk/viewFile/564091e072d41.pdf. Accessed 7 Jan 2018.

Download references

Acknowledgments

Our work is supported by grants from the European Commission (Cooperative Research Projects “sysVASC” (603288), “HOMAGE” (305507), and “PRIORITY” (101813)) and the British Heart Foundation (Centre of Research Excellence Award RE/13/5/30177).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christian Delles .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Currie, G., Delles, C. (2018). Precision Medicine and Personalized Medicine in Cardiovascular Disease. In: Kerkhof, P., Miller, V. (eds) Sex-Specific Analysis of Cardiovascular Function. Advances in Experimental Medicine and Biology, vol 1065. Springer, Cham. https://doi.org/10.1007/978-3-319-77932-4_36

Download citation

Publish with us

Policies and ethics