title: Increased power to detect gene-environment interaction using siblings controls.
abstract: OBJECTIVE
  Interest is increasing in studying gene-environment (G x E) interaction in disease etiology. Study designs using related controls as a more appropriate control group for evaluating G x E interactions have been proposed but often assume unrealistic numbers of available relative controls. To evaluate a more realistic design, we studied the relative efficiency of a 1:0.5 case-sibling-control design compared with a classical 1:1 case-unrelated-control design and examined the effect of the analysis strategy.
  
  
  METHODS
  Simulations were performed to assess the efficiency of a 1:0.5 case-sibling-control design relative to a classical 1:1 case-unrelated-control design under a variety of assumptions for estimating G x E interaction. Both matched and unmatched analysis strategies were examined.
  
  
  RESULTS
  When using a matched analysis, the 1:1 case-unrelated-control design was almost always more powerful than the 1:0.5 case-sibling-control design. In contrast, when using an unmatched analysis, the 1:0.5 case-sibling-control design was almost always more powerful than the 1:1 case-unrelated-control design. The unconditional analysis of the case-sibling-control design to estimate G x E interaction, however, requires no correlation in E between siblings.
  
  
  CONCLUSIONS
  In most settings, a matched analysis may be required and a 1:1 case-unrelated-control design will be more powerful than a 1:0.5 case-sibling-control design.
authors.affiliation: National Institute of Health and Medical Research EMI00-06, Evry, France. nadine.andrieu@curie.net
authors.forename: Nadine
authors.initials: N
authors.lastname: Andrieu
authors.forename: Marie-Gabrielle
authors.initials: MG
authors.lastname: Dondon
authors.forename: Alisa M
authors.initials: AM
authors.lastname: Goldstein
mesh_terms: D016022:Case-Control Studies; D004777:Environment; D005240:Feasibility Studies; D015870:Gene Expression; D006801:Humans; D040582:Inheritance Patterns; D016555:Matched-Pair Analysis; D008957:Models, Genetic; D015233:Models, Statistical; D010641:Phenotype; D012107:Research Design; D018401:Sample Size; D035781:Siblings