Dempfle A, Scherag A, Hein R et al.Gene-environment interactions for complex traits: definitions, methodological requirements and challenges. Eur J Hum Genet 16:1164-72

Institute of Medical Biometry and Epidemiology, Philipps University Marburg, Marburg, Germany.
European Journal of HumanGenetics (Impact Factor: 4.35). 10/2008; 16(10):1164-72. DOI: 10.1038/ejhg.2008.106
Source: PubMed


Genetic and environmental risk factors and their interactions contribute to the development of complex diseases. In this review, we discuss methodological issues involved in investigating gene-environment (G x E) interactions in genetic-epidemiological studies of complex diseases and their potential relevance for clinical application. Although there are some important examples of interactions and applications, the widespread use of the knowledge about G x E interaction for targeted intervention or personalized treatment (pharmacogenetics) is still beyond current means. This is due to the fact that convincing evidence and high predictive or discriminative power are necessary conditions for usefulness in clinical practice. We attempt to clarify conceptual differences of the term 'interaction' in the statistical and biological sciences, since precise definitions are important for the interpretation of results. We argue that the investigation of G x E interactions is more rewarding for the detailed characterization of identified disease genes (ie at advanced stages of genetic research) and the stratified analysis of environmental effects by genotype or vice versa. Advantages and disadvantages of different epidemiological study designs are given and sample size requirements are exemplified. These issues as well as a critical appraisal of common methodological concerns are finally discussed.

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Available from: André Scherag, Feb 09, 2015
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    • "Vielmehr ist davon auszugehen, dass menschliches Verhalten durch die Wechselwirkung einer Vielzahl unterschiedlicher Gene beeinflusst wird (Plomin & Crabbe, 2000). Um die mit einzelnen Genen einhergehenden kleinen Effektstärken und insbesondere Interaktionseffekte statistisch ermitteln zu können werden sehr große Stichprobenumfänge benötigt (siehe Dempfle et al., 2008; Luan, Wong, Day & Wareham, 2001). In der psychiatrischen Forschung wird diese Anforderung aufgrund der meist aufwendigen Studiendesigns sowie der teilweise geringen Prävalenzraten psychischer Störungsbilder üblicherweise nicht erfüllt (Duncan & Keller, 2011; vgl. "
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    • "Population structure may confound genetic classifiers as demonstrated in autism (Belgard et al., 2013; Robinson et al., 2013). However, use of unaffected siblings in association studies (instead of independent controls) protects against false positives resulting from population stratification (Dempfle et al., 2008). So, to maintain statistical power, affected, and unaffected individuals from the different families were analyzed as a whole without considering ethnicity, but limiting false positive results coming from population stratification using unaffected siblings as controls. "
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