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Cloettapreis_2013_Nr_41

22 Gene-gene interactions In addition to epigenetic factors, causal but non-examined rare variants, and environmental influences, the negligence of analytical approaches accounting for gene-gene interaction effects, such as statistical epistasis, may partly explain the phenomenon of «missing heritability»31 . Indeed, despite the obvious conception that the analysis of genetically complex traits should account for the underlying biological and statistical com­ plexity, the vast majority of large-scale genetic association studies to date are restricted to the use of single marker statistics. Clearly, this approach does not fully account for the polygenic nature of the phenotype under study and erroneously implies that the impact of genetic variation is due to independently acting effects. The above also holds true for the study of the genetics of episodic mem­ ory. Although the large-scale analysis of statistical epistasis related to complex traits has proven feasible32 , only few studies have addressed epi- static effects of a limited number of genetic variants on cognitive func- tions33-36 . In the light of the complex polygenic nature of episodic memo- ry, studies accounting for the statistical interaction between few (e.g., two) genetic variants should be regarded as proof-of-principle studies and as a starting point for more complex approaches. However, studies involv­ ing comprehensive sets of genetic variants and addressing interaction (e.g., epistatic) effects on human memory are still lacking. The concept of statistical epistasis was defined about a century ago and deals with the statistical deviation from additive interaction effects between genetic markers37 . Per definition, the inclusion of such statistical interaction terms as epistasis exponentially increases the number of statistical tests per­ formed. For example, a two-way interaction analysis between 1000 sin- gle markers requires the performance of 499 500 tests. Some strategies attempting to limit the number of necessary tests in analyses of epistasis employ a stepwise procedure by including only those interaction terms, for which the corresponding marker showed a significant main effect in the first step single-marker analysis. However, this approach is arbitrary as there is no biological rationale for considering only markers with sig- nificant main effects. Indeed, a recently published report of an exhaust­ ive genome-wide analysis showed that significant epistatic interactions would have been missed if SNPs that did not display any main effect had

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