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Wie groß sind die kleinen genetischen Risiken?

How big are the small genetic risks?

Zusammenfassung

Während Familienstudien sich als sehr geeignet zeigen, um starke genetische Risikovarianten aufzuspüren, sind genomweite Assoziationsstudien mit nichtverwandten Personen besonders effizient in der Identifizierung von moderaten und schwachen genetischen Risiken bei multifaktoriellen Erkrankungen und erkrankungsrelevanten quantitativen Parametern. Hier wird dargestellt, wie das genetische Risiko für solch moderat bis schwach wirkende Varianten berechnet wird. An den Beispielen Adipositas, Diabetes und altersbedingte Makuladegeneration wird gezeigt, welche Modelle Anwendung finden und wie groß diese „kleinen“ genetischen Risiken sind.

Abstract

While family studies are ideal to pinpoint strong genetic risk effects, genome-wide association studies in unrelated individuals are particularly successful in identifying moderate and small genetic risks for multifactorial diseases and disease-relevant quantitative parameters. Here, we present how the genetic risk for such variants is computed and what models are used to derive cumulative genetic risk. Using the examples of obesity, diabetes, and age-related macular degeneration, we illustrate how these risks are computed and tackle the question of how big the small genetic risks are.

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Abbreviations

GWAS:

genomweite Assoziationsstudie

BMI:

Body-Mass-Index

AMD:

altersbedingte Makuladegeneration

T2D:

Typ-2-Diabetes

OR:

Odds Ratio

PAR:

Populationsattributables Risiko

MAF:

„minor allele frequency“, Häufigkeit des selteneren Allels

EAF:

„effect allele frequency“, Häufigkeit des Effektallels

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Correspondence to I.M. Heid.

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Heid, I., Winkler, T., Grassmann, F. et al. Wie groß sind die kleinen genetischen Risiken?. medgen 23, 377–384 (2011). https://doi.org/10.1007/s11825-011-0295-7

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Schlüsselwörter

  • Genetische Assoziationsstudien
  • Risikobestimmung
  • Lineare Modelle
  • Adipositas
  • Altersbedingte Makuladegeneration

Keywords

  • Genetic association studies
  • Risk assessment
  • Linear models
  • Obesity
  • Age-related macular degeneration