Objective: The interest in studying gene-environment (GxE) interaction is increasing for complex diseases. A design combining both related and unrelated controls (e.g., population-based and siblings) is proposed to increase the power to detect GxE interaction.
Study design and setting: We used simulations to assess the efficiency of the case-combined-control design relative to a classical case-control study under a variety of assumptions.
Results: The case-combined-control design appears more efficient and feasible than a classical case-control study for detecting interaction involving rare exposures and/or genetic factors. The number of available sibling controls per case and the frequencies of the risk factors are the most important parameters for determining relative efficiency. Relative efficiencies decrease as the frequency of the gene (G) increases. A positive correlation in exposure (E) between siblings decreases relative efficiency.
Conclusions: Although the case-combined-control design may not be efficient for common genes with moderate effects, it appears to be a useful alternative in certain situations where classical approaches remain unrealistic.