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Genetik intermediärer Phänotypen

Genetics of intermediate phenotypes

  • Schwerpunkt: Multifaktorielle Erkrankungen
  • Published:
medizinische genetik

Zusammenfassung

Die Entstehung komplexer Erkrankungen wie koronare Herzkrankheit oder Diabetes mellitus wird durch zahlreiche Gene beeinflusst, von welchen jedes einzelne einen oft eher geringen Beitrag liefert. Der Nachweis, dass bestimmte genetische Varianten mit komplexen Erkrankungen assoziiert sind, ist oft schwer zu führen und bedarf großer, gut charakterisierter Patienten- und Kontrollgruppen. Alternativ und Erfolg versprechend ist die Untersuchung so genannter intermediärer Phänotypen. Dabei handelt es sich um Parameter, die mit der Entstehung der Erkrankung in Zusammenhang stehen, genetisch determiniert sind und einen Teilaspekt unter mehreren im Entstehungsmechanismus der Erkrankung repräsentieren. Dadurch kommt es zu einer Schärfung des Phänotyps und zu einer Reduktion der genetischen Heterogenität. Durch Untersuchung der Genetik solcher intermediärer Phänotypen statt der Genetik der Erkrankung an sich kann dieser Teilaspekt aufgeklärt werden. Besonders geeignet als intermediäre Phänotypen sind quantitative, gut messbare biochemische Parameter, wodurch im Gegensatz zu qualitativen Parametern eine deutlich verbesserte statistische Power erreicht werden kann.

Abstract

The development of complex diseases such as coronary heart disease and diabetes mellitus is influenced by numerous genes. However, the contribution of a single gene is relatively small. The identification of genetic variants associated with complex diseases therefore requires large efforts and well-characterized groups of patients and controls. Alternatively, investigation of intermediate phenotypes instead of these complex endpoints seems to be more promising. An intermediate phenotype is usually already well known to be associated with the investigated disease, is heritable, and represents one aspect among others in the pathogenesis of the complex disease. This results in an accentuation of the phenotype and reduction of genetic heterogeneity. Investigating the genetics of the intermediate phenotype instead of the genetics of the end phenotype allows elucidation of this aspect of the disease. Optimal intermediate phenotypes are quantitative, easy-to-measure biochemical parameters. This results in an increased statistical power in contrast to qualitative phenotypes.

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Literatur

  1. Baron RM, Kenny DA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51: 1173–1182

    Article  PubMed  CAS  Google Scholar 

  2. Boden G, Shulman GI (2002) Free fatty acids in obesity and type 2 diabetes: defining their role in the development of insulin resistance and beta-cell dysfunction. Eur J Clin Invest [Suppl 3] 32: 14–23

  3. Contopoulos-Ioannidis DG, Kouri IN, Ioannidis JP (2007) Genetic predisposition to asthma and atopy. Respiration 74: 8–12

    PubMed  Google Scholar 

  4. Davey SG, Ebrahim S (2003) ‚Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 32: 1–22

    Article  Google Scholar 

  5. Gottesman II, Gould TD (2003) The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 160: 636–645

    Article  PubMed  Google Scholar 

  6. Heid IM, Wagner SA, Gohlke H et al. (2006) Genetic architecture of the APM1 gene and its influence on adiponectin plasma levels and parameters of the metabolic syndrome in 1727 healthy Caucasians. Diabetes 55: 375–384

    Article  PubMed  CAS  Google Scholar 

  7. Huth C, Heid IM, Vollmert C et al. (2006) IL6 gene promoter polymorphisms and type 2 diabetes: joint analysis of individual participants‘ data from 21 studies. Diabetes 55: 2915–2921

    Article  PubMed  CAS  Google Scholar 

  8. Kahn SE, Hull RL, Utzschneider KM (2006) Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 444: 840–846

    Article  PubMed  CAS  Google Scholar 

  9. Katan MB (1986) Apolipoprotein E isoforms, serum cholesterol, and cancer. Lancet 1: 507–508

    Article  PubMed  CAS  Google Scholar 

  10. Kronenberg F, Coon H, Gutin A et al. (2002) A genome scan for loci influencing anti-atherogenic serum bilirubin levels. Eur J Hum Genet 10: 539–546

    Article  PubMed  CAS  Google Scholar 

  11. Lin J-P, O’Donnell CJ, Schwaiger JP et al. (2006) Association between UGT1A1*28 allele, bilirubin levels, and coronary heart disease in the Framingham Heart Study. Circulation 114: 1476–1481

    Article  PubMed  CAS  Google Scholar 

  12. Palmer LJ, Redline S (2003) Genomic approaches to understanding obstructive sleep apnea. Respir Physiol Neurobiol 135: 187–205

    Article  PubMed  CAS  Google Scholar 

  13. Prentice RL (1989) Surrogate endpoints in clinical trials: definition and operational criteria. Stat Med 8: 431–440

    Article  PubMed  CAS  Google Scholar 

  14. Sandholzer C, Saha N, Kark JD et al. (1992) Apo(a) isoforms predict risk for coronary heart disease: a study in six populations. Arterioscler Thromb 12: 1214–1226

    PubMed  CAS  Google Scholar 

  15. Schoenborn V, Heid IM, Vollmert C et al. (2006) The ATGL gene is associated with free fatty acids, triglycerides and type 2 diabetes. Diabetes 55: 1270–1275

    Article  PubMed  CAS  Google Scholar 

  16. Zimmermann R, Strauss JG, Haemmerle G et al. (2004) Fat mobilization in adipose tissue is promoted by adipose triglyceride lipase. Science 306: 1383–1386

    Article  PubMed  CAS  Google Scholar 

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Danksagung

Eigene Arbeiten, die in dieser Übersicht besprochen worden sind, wurden durch das GEN-AU Projekt GOLD (Genomics of Lipid-Associated Disorders) und das Nationale Genomforschungsnetz (NGFN) Deutschland gefördert.

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Correspondence to F. Kronenberg.

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Kronenberg, F., Heid, I. Genetik intermediärer Phänotypen. medgen 19, 304–308 (2007). https://doi.org/10.1007/s11825-007-0036-0

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  • DOI: https://doi.org/10.1007/s11825-007-0036-0

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