Skip to main content
SpringerLink
Log in

Genetics of Cardiovascular Disease

  • Chapter
Prevention of Cardiovascular Diseases

  • 1384 Accesses

Abstract

Cardiovascular diseases (CVD) remain a major source of mortality and morbidity worldwide, and considerable effort has been applied to identifying modifiable environmental factors such as diet, exercise, weight control, smoking, and drug therapy that can reduce the risk of CVD. Many CVDs have a strong familial component, however, and at least some of this is attributable to genetic factors. Over the past decades, our understanding of monogenic CVD (sometimes referred to as “simple” or “Mendelian diseases,” such as familial hypercholesterolemia and hypertrophic cardiomyopathy) has increased dramatically. Monogenetic disorders are typically caused by relatively rare variants in single genes that have a large phenotypic effect in individuals and high penetrance. Consequently, these forms of CVD account for a small proportion of the total population CVD burden. In contrast, complex genetic diseases (sometimes referred to as “common” diseases, such as atherosclerosis) may be influenced by multiple (and interacting) sequence variants, epigenetics, and gene x environment interactions. The genetic component of complex diseases is possibly the aggregate of multiple small effects. The relatively small phenotypic variation (compared to monogenic traits) of intermediate CVD traits (such as hypertension) disposes individuals toward disease development. For these reasons, genetics (the study of the function of individual genes) and genomics (the study of the function of the entire genome, i.e., genes, non-protein-coding stretches of DNA, gene–gene interactions, etc.) play a potentially important part in our evolving understanding of CVDs, including risk prediction, discovery and functional explorations of susceptibility loci, and ultimately identification of new therapeutic targets.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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. Castelli WP, Doyle JT, Gordon T, et al. HDL cholesterol and other lipids in coronary heart disease. The cooperative lipoprotein phenotyping study. Circulation. 1977;55:767–72.

    Article  CAS  PubMed  Google Scholar 

  2. Knoblauch H, Bauerfeind A, Toliat MR, et al. Haplotypes and SNPs in 13 lipid-relevant genes explain most of the genetic variance in high-density lipoprotein and low-density lipoprotein cholesterol. Hum Mol Genet. 2004;13:993–1004.

    Article  CAS  PubMed  Google Scholar 

  3. Rader DJ, Cohen J, Hobbs HH. Monogenic hypercholesterolemia: new insights in pathogenesis and treatment. J Clin Invest. 2003;111:1795–803.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Jensen HK. The molecular genetic basis and diagnosis of familial hypercholesterolemia in Denmark. Dan Med Bull. 2002;49:318–45.

    CAS  PubMed  Google Scholar 

  5. De Castro-Oros I, Pocovi M, Civeira F. The genetic basis of familial hypercholesterolemia: inheritance, linkage, and mutations. Appl Clin Genet. 2010;3:53–64.

    PubMed Central  PubMed  Google Scholar 

  6. Goldstein J, Hobbs H, Brown M. Familial hypercholesterolemia. In: Beaudet A, Sly W, Valle D, editors. The metabolic and molecular bases of inherited disease. New York: McGraw-Hill; 2001. p. 2863–913.

    Google Scholar 

  7. Robinson JG. Management of familial hypercholesterolemia: a review of the recommendations from the National Lipid Association Expert Panel on familial hypercholesterolemia. J Manag Care Pharm. 2013;19:139–49.

    PubMed  Google Scholar 

  8. Horton JD, Cohen JC, Hobbs HH. PCSK9: a convertase that coordinates LDL catabolism. J Lipid Res. 2009;50 Suppl:S172–7.

    Google Scholar 

  9. Cohen J, Pertsemlidis A, Kotowski IK, et al. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat Genet. 2005;37:161–5.

    Article  CAS  PubMed  Google Scholar 

  10. Wierzbicki AS, Hardman TC, Viljoen A. Inhibition of pro-protein convertase subtilisin kexin 9 [corrected] (PCSK-9) as a treatment for hyperlipidaemia. Expert Opin Investig Drugs. 2012;21:667–76.

    Article  CAS  PubMed  Google Scholar 

  11. Ahmad Z, Adams-Huet B, Chen C, et al. Low prevalence of mutations in known loci for autosomal dominant hypercholesterolemia in a multiethnic patient cohort. Circ Cardiovasc Genet. 2012;5:666–75.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. Maron BJ, Maron MS. Hypertrophic cardiomyopathy. Lancet. 2013;381:242–55.

    Article  PubMed  Google Scholar 

  13. Subasic K. Hypertrophic cardiomyopathy. Nurs Clin North Am. 2013;48:571–84.

    Article  PubMed  Google Scholar 

  14. Yingchoncharoen T, Tang WW. Recent advances in hypertrophic cardiomyopathy. F1000Prime Rep. 2014;6:12.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Brugada R, Kelsey W, Lechin M, et al. Role of candidate modifier genes on the phenotypic expression of hypertrophy in patients with hypertrophic cardiomyopathy. J Investig Med. 1997;45:542–51.

    CAS  PubMed  Google Scholar 

  16. Lloyd-Jones DM, Nam BH, D’Agostino Sr RB, et al. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring. JAMA. 2004;291:2204–11.

    Article  CAS  PubMed  Google Scholar 

  17. Preuss M, Konig IR, Thompson JR, et al. Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) study: a Genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls. Circ Cardiovasc Genet. 2010;3:475–83.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  18. Consortium CADCDG. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat Genet. 2011;43:339–44.

    Google Scholar 

  19. Deloukas P, Kanoni S, Willenborg C, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 2013;45:25–33.

    Article  CAS  PubMed  Google Scholar 

  20. Schunkert H, Konig IR, Kathiresan S, et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 2011;43:333–8.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Saha N, Tay JS, Low PS, et al. Guanidine to adenine (G/A) substitution in the promoter region of the apolipoprotein AI gene is associated with elevated serum apolipoprotein AI levels in Chinese non-smokers. Genet Epidemiol. 1994;11:255–64.

    Article  CAS  PubMed  Google Scholar 

  22. Minnich A, DeLangavant G, Lavigne J, et al. G→A substitution at position −75 of the apolipoprotein A-I gene promoter. Evidence against a direct effect on HDL cholesterol levels. Arterioscler Thromb Vasc Biol. 1995;15:1740–5.

    Article  CAS  PubMed  Google Scholar 

  23. Barre DE, Guerra R, Verstraete R, et al. Genetic analysis of a polymorphism in the human apolipoprotein A-I gene promoter: effect on plasma HDL-cholesterol levels. J Lipid Res. 1994;35:1292–6.

    CAS  PubMed  Google Scholar 

  24. Miettinen HE, Korpela K, Hamalainen L, et al. Polymorphisms of the apolipoprotein and angiotensin converting enzyme genes in young North Karelian patients with coronary heart disease. Hum Genet. 1994;94:189–92.

    Article  CAS  PubMed  Google Scholar 

  25. Akita H, Chiba H, Tsuji M, et al. Evaluation of G-to-A substitution in the apolipoprotein A-I gene promoter as a determinant of high-density lipoprotein cholesterol level in subjects with and without cholesteryl ester transfer protein deficiency. Hum Genet. 1995;96:521–6.

    Article  CAS  PubMed  Google Scholar 

  26. Teslovich TM, Musunuru K, Smith AV, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–13.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  27. Kathiresan S, Willer CJ, Peloso GM, et al. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet. 2009;41:56–65.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Williams RR, Hunt SC, Hasstedt SJ, et al. Genetics of hypertension: what we know and don’t know. Clin Exp Hypertens A. 1990;12:865–76.

    Article  CAS  PubMed  Google Scholar 

  29. Ji W, Foo JN, O’Roak BJ, et al. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat Genet. 2008;40:592–9.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. Ehret GB, Munroe PB, Rice KM, et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature. 2011;478:103–9.

    Article  CAS  PubMed  Google Scholar 

  31. Kato N, Takeuchi F, Tabara Y, et al. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians. Nat Genet. 2011;43:531–8.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  32. Ganesh SK, Arnett DK, Assimes TL, et al. Genetics and genomics for the prevention and treatment of cardiovascular disease: update: a scientific statement from the American Heart Association. Circulation. 2013;128:2813–51.

    Article  PubMed  Google Scholar 

  33. Mega JL, Close SL, Wiviott SD, et al. Cytochrome P450 genetic polymorphisms and the response to prasugrel: relationship to pharmacokinetic, pharmacodynamic, and clinical outcomes. Circulation. 2009;119:2553–60.

    Article  CAS  PubMed  Google Scholar 

  34. Holmes MV, Perel P, Shah T, et al. CYP2C19 genotype, clopidogrel metabolism, platelet function, and cardiovascular events: a systematic review and meta-analysis. JAMA. 2011;306:2704–14.

    Article  CAS  PubMed  Google Scholar 

  35. Scott SA, Sangkuhl K, Stein CM, et al. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. Clin Pharmacol Ther. 2013;94:317–23.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  36. Rettie AE, Wienkers LC, Gonzalez FJ, et al. Impaired (S)-warfarin metabolism catalysed by the R144C allelic variant of CYP2C9. Pharmacogenetics. 1994;4:39–42.

    Article  CAS  PubMed  Google Scholar 

  37. Limdi NA, McGwin G, Goldstein JA, et al. Influence of CYP2C9 and VKORC1 1173C/T genotype on the risk of hemorrhagic complications in African-American and European-American patients on warfarin. Clin Pharmacol Ther. 2008;83:312–21.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. Finkelman BS, Gage BF, Johnson JA, et al. Genetic warfarin dosing: tables versus algorithms. J Am Coll Cardiol. 2011;57:612–8.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  39. Kimmel SE, French B, Kasner SE, et al. A pharmacogenetic versus a clinical algorithm for warfarin dosing. N Engl J Med. 2013;369:2283–93.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. Pirmohamed M, Burnside G, Eriksson N, et al. A randomized trial of genotype-guided dosing of warfarin. N Engl J Med. 2013;369:2294–303.

    Article  CAS  PubMed  Google Scholar 

  41. Lynch AI, Boerwinkle E, Davis BR, et al. Pharmacogenetic association of the NPPA T2238C genetic variant with cardiovascular disease outcomes in patients with hypertension. JAMA. 2008;299:296–307.

    Article  CAS  PubMed  Google Scholar 

  42. Barber MJ, Mangravite LM, Hyde CL, et al. Genome-wide association of lipid-lowering response to statins in combined study populations. PLoS One. 2010;5, e9763.

    Article  PubMed Central  PubMed  Google Scholar 

  43. Frazier-Wood AC, Aslibekyan S, Borecki IB, et al. Genome-wide association study indicates variants associated with insulin signaling and inflammation mediate lipoprotein responses to fenofibrate. Pharmacogenet Genomics. 2012;22:750–7.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  44. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. EGAPP Working Group Recommendations. 2009. http://www.egappreviews.org/recommendations/index.htm. Accessed 18 Mar 2014.

  45. Recommendations from the EGAPP Working Group: genomic profiling to assess cardiovascular risk to improve cardiovascular health. Genet Med. 2010;12:839–43.

    Google Scholar 

  46. Recommendations from the EGAPP Working Group: routine testing for Factor V Leiden (R506Q) and prothrombin (20210G>A) mutations in adults with a history of idiopathic venous thromboembolism and their adult family members. Genet Med. 2011;13:67–76.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

    Steven A. Claas M.S.

  2. Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA

    Stella Aslibekyan Ph.D.

  3. University of Alabama at Birmingham, Birmingham, AL, USA

    Stella Aslibekyan Ph.D.

  4. Department of Epidemiology, School of Public Health, University of Alabama School of Medicine, Birmingham, AL, USA

    Donna K. Arnett M.S.P.H., Ph.D.

  5. American Heart Association, Dallas, TX, USA

    Donna K. Arnett M.S.P.H., Ph.D.

Authors
  1. Steven A. Claas M.S.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stella Aslibekyan Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Donna K. Arnett M.S.P.H., Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Steven A. Claas M.S. .

Editor information

Editors and Affiliations

  1. Hospital da Bahia, Salvador, Bahia, Brazil

    Jadelson Andrade

  2. University Hospital of Santa Maria,Faculty of Medicine, University of Lisbon, Lisbon, Portugal

    Fausto Pinto

  3. Department of Epidemiology, School of Public Health, University of Alabama School of Medicine, Birmingham, Alabama, USA

    Donna Arnett

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Claas, S.A., Aslibekyan, S., Arnett, D.K. (2015). Genetics of Cardiovascular Disease. In: Andrade, J., Pinto, F., Arnett, D. (eds) Prevention of Cardiovascular Diseases. Springer, Cham. https://doi.org/10.1007/978-3-319-22357-5_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-22357-5_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22356-8

  • Online ISBN: 978-3-319-22357-5

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation