title: Gene-environment interaction and affected sib pair linkage analysis.
abstract: OBJECTIVE
  Gene-environment (GxE) interaction influences risk for many complex disease traits. However, genome screens using affected sib pair linkage techniques are typically conducted without regard for GxE interaction. We propose a simple extension of the commonly used mean test and evaluate its power for several forms of GxE interaction.
  
  
  METHODS
  We compute expected IBD sharing by sibling exposure profile, that is by whether two sibs are exposed (EE), unexposed (UU), or are discordant for exposure (EU). We describe a simple extension of the mean test, the "mean-interaction" test that utilizes heterogeneity in IBD sharing across EE, EU, and UU sib pairs in a test for linkage.
  
  
  RESULTS
  The mean-interaction test provides greater power than the mean test for detecting linkage in the presence of moderate or strong GxE interaction, typically when the interaction relative risk (R(ge)) exceeds 3 or is less than 1/3. In the presence of strong interaction (R(ge) = 10), the required number of affected sib pairs to achieve 80% power for detecting linkage is approximately 30% higher when the environmental factor is ignored in the mean test, than when it is utilized in the mean-interaction test.
  
  
  CONCLUSIONS
  Linkage methods that incorporate environmental data and allow for interaction can lead to increased power for localizing a disease gene involved in a GxE interaction.
authors.affiliation: Department of Preventive Medicine, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90089, USA. jimg@usc.edu
authors.forename: W J
authors.initials: WJ
authors.lastname: Gauderman
authors.forename: K D
authors.initials: KD
authors.lastname: Siegmund
mesh_terms: D002874:Chromosome Mapping / Q000379:methods; D002877:Chromosomes, Human; D003198:Computer Simulation; D004777:Environment; D005191:Family Characteristics; D008040:Genetic Linkage / Q000235:genetics*; D005821:Genetic Techniques; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D012107:Research Design; D018401:Sample Size; D012984:Software; D013223:Statistics as Topic