Genes & Nutrition

, Volume 2, Issue 1, pp 75–80 | Cite as

Genes, diet and public health

  • Udo SeedorfEmail author
  • Helmut Schulte
  • Gerd Assmann


Common chronic diseases such as coronary heart disease (CHD), diabetes, cancer, hypertension and obesity are significantly influenced by dietary and other behavioural habits. There is increasing scientific evidence that genetic factors (SNPs), conferring either protection or risk, also contribute importantly to the incidence of these diseases. SNPs are of particular interest because they influence disease in a complex but largely unknown manner by interacting with environmental and lifestyle factors. Because genetic factors also affect a person’s response to dietary habits, SNPs likely will be useful in helping to determine and understand why individuals differ in their response to diets. Therefore, the discovery of SNPs will likely revolutionize not only the diagnosis of disease but also the practice of preventative medicine. Other developments, like new biomarkers and noninvasive imaging techniques, might turn out to be highly sensitive and specific in order to identify patients at risk, especially in cases with asymptomatic coronary heart disease. Thus, further knowledge of such new risk factors and their interaction with nutrition, has the potential to provide a more precise and personalized approach to prevent and treat chronic diseases like coronary artery disease, myocardial infarction and stroke.


Myocardial infarction Epidemiology Genetics Disease prevention Biomarkers Dietary recommendations 


  1. 1.
    Schulte H, Cullen P, Assmann G (1999) Obesity, mortality and cardiovascular disease in the Munster Heart Study (PROCAM). Atherosclerosis 144:199–209PubMedCrossRefGoogle Scholar
  2. 2.
    Schaefer EJ (2002) Lipoproteins, nutrition, and heart disease. Am J Clin Nutr 75:191–212PubMedGoogle Scholar
  3. 3.
    Marenberg ME, Risch N, Berkman LF, Floderus B, de Faire U (1994) Genetic susceptibility to death from coronary heart disease in a study of twins. N Engl J Med 330:1041–1046PubMedCrossRefGoogle Scholar
  4. 4.
    Guttmacher E, Collins FS (2003) Welcome to the genomic era. N Engl J Med 349:996–998PubMedCrossRefGoogle Scholar
  5. 5.
    Williams RR, Hunt SC, Heiss G, Province MA, Bensen JT, Higgins M, Chamberlain RM, Ware J, Hopkins PN (2001) Usefulness of cardiovascular family history data for population-based preventive medicine and medical research (the Health Family Tree Study and the NHLBI Family Heart Study). Am J Cardiol 87:129–135PubMedCrossRefGoogle Scholar
  6. 6.
    Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB (1998) Prediction of coronary heart disease using risk factor categories. Circulation 97:1837–1847PubMedGoogle Scholar
  7. 7.
    Assmann G, Cullen P, Schulte H (2002) Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation 105:310–315PubMedCrossRefGoogle Scholar
  8. 8.
    Samani NJ, Burton P, Mangino M, Ball SG, Balmforth AJ, Barrett J, Bishop T, Hall A (2005) BHF Family Heart Study Research Group. A genomewide linkage study of 1,933 families affected by premature coronary artery disease: The British Heart Foundation (BHF) Family Heart Study. Am J Hum Genet 77:1011–1020PubMedCrossRefGoogle Scholar
  9. 9.
    Pajukanta P, Cargill M, Viitanen L, Nuotio I, Kareinen A, Perola M, Terwilliger JD, Kempas E, Daly M, Lilja H, Rioux JD, Brettin T, Viikari JS, Rönnemaa T, Laakso M, Lander ES, Peltonen L (2000) Two loci on chromosomes 2 and X for premature coronary heart disease identified in early- and late-settlement populations of Finland. Am J Hum Genet 67:1481–1493PubMedCrossRefGoogle Scholar
  10. 10.
    Francke S, Manraj M, Lacquemant C, Lecoeur C, Lepretre F, Passa P, Hebe A, Corset L, Yan SL, Lahmidi S, Jankee S, Gunness TK, Ramjuttun US, Balgobin V, Dina C, Froguel P (2001) A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16p13 and replicates linkage with the metabolic syndrome on 3q27. Hum Mol Genet 10:2751–2765PubMedCrossRefGoogle Scholar
  11. 11.
    Broeckel U, Hengstenberg C, Mayer B, Holmer S, Martin LJ, Comuzzie AG, Blangero J, Nurnberg P, Reis A, Riegger GA, Jacob HJ, Schunkert H (2002) A comprehensive linkage analysis for myocardial infarction and its related risk factors. Nat Genet 30:210–214PubMedCrossRefGoogle Scholar
  12. 12.
    Harrap SB, Zammit KS, Wong ZY, Williams FM, Bahlo M, Tonkin AM, Anderson ST (2002) Genome-wide linkage analysis of the acute coronary syndrome suggests a locus on chromosome 2. Arterioscler Thromb Vasc Biol 22:874–878PubMedCrossRefGoogle Scholar
  13. 13.
    Hauser ER, Crossman DC, Granger CB, Haines JL, Jones CJ, Mooser V, McAdam B et al (2004) A genomewide scan for early-onset coronary artery disease in 438 families: the GENECARD Study. Am J Hum Genet 75:436–447PubMedCrossRefGoogle Scholar
  14. 14.
    Helgadottir, Manolescu A, Thorleifsson G, Gretarsdottir S, Jonsdottir H, Thorsteinsdottir U, Samani NJ et al (2004) The gene encoding 5-lipoxygenase activating protein confers risk of myocardial infarction and stroke. Nat Genet 36:233–239Google Scholar
  15. 15.
    Wang L, Fan C, Topol SE, Topol EJ, Wang Q (2003) Mutation of MEF2A in an inherited disorder with features of coronary artery disease. Science 302:1578–1581PubMedCrossRefGoogle Scholar
  16. 16.
    Heijmans BT, Beekman M, Putter H, Lakenberg N, van der Wijk HJ, Whitfield JB, Posthuma D, Pedersen NL, Martin NG, Boomsma DI, Slagboom PE (2005) Meta-analysis of four new genome scans for lipid parameters and analysis of positional candidates in positive linkage regions. Eur J Hum Genet 13:1143–1153PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Leibniz Institute for Arteriosclerosis ResearchUniversity of MunsterMunsterGermany
  2. 2.Institute of Clinical Chemistry and Laboratory Medicine, Central LaboratoryUniversity of MunsterMunsterGermany

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