Increased Power to Detect Gene–Environment Interaction Using Siblings Controls

Purpose Interest is increasing in studying gene–environment (G×E) interaction in disease etiology. Study designs using related controls as a more appropriate control group for evaluating G×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×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×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.