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Systematic-Methodological Platforms GEM SMP : Genetic Epidemiological Methods ( GEM ) Project : Statistical Methods for Gene-environment Interactions

Introduction Within NGFN-2, large-scale case-control studies for the identification of predisposing genes for complex diseases are planned. Many of the susceptibility genes, however, act through modification of disease risk associated with life-style and/or environmental factors. Thus statistical analysis of gene-environmental interactions is required for the investigation of the possible mechanisms involved. While there are several important examples of interactions, the full extend of their relevance is not clear from available data. Moreover, the meaning of interaction varies between statistical and biological sciences, as precise definitions are often omitted. We argue that the investigation of geneenvironment (G x E) interaction is mostly sensible in advanced stages of genetic research, for the detailed characterization of identified disease genes or the stratified analysis of environmental effects by genotype. The widespread use of GxE interaction for targeted intervention or personalized treatment (pharmacogenetics) is still beyond current means; hardly any such interaction is used in clinical practice due to unconvincing evidence or low predictive and discriminative power. Valid results on G x E interactions require studies that include large sample sizes, corrections for multiple testing and replication. The objective of the project is to evaluate the relative benefits of different approaches for the statistical analysis of gene-environmental interactions based on single nucleotide polymorphisms and haplotypes using simulated data and to employ these methods to real data sets.