Misclassification Bias in the Assessment of Gene-by-Environment Interactions

Background: Misclassification bias is a common concern in epidemiologic studies. Despite strong bias on main effects, gene-environment interactions have been shown to be biased towards the null under gene-environment independence. In the context of a recent article examining the interaction between nerve agent exposure and paraoxonase-1 gene on Gulf War Illness, we aimed to assess the impact of recall bias-a common misclassfication bias-on the identification of gene-environment interactions when the independence assumption is violated. Methods: We derive equations to quantify the bias of the interaction, and numerically illustrate these results by simulating a case-control study of 1000 cases and 1000 controls. Simulation input parameters included exposure prevalence, strength of gene-environment dependence, strength of the main effect, exposure specificity among cases, and strength of the gene-environment interaction. Results: We show that, even if gene-environment independence is violated, we can bound possible gene-environment interactions by knowing the strength and direction of the gene-environment dependence (ORGE) and the observed gene-environment interaction (ORINT-O)-thus often still allowing for the identification of such interactions. Depending on whether ORINT- O is larger or smaller than the inverse of ORGE, ORINT- O is a lower (if ORINT- O > 1/ORGE) or upper (if ORINT- O < 1/ORGE) bound for the true interaction. In addition, the bias magnitude is somewhat predictable by examining other characteristics such as exposure prevalence, the strength of the exposure main effect, and directions of the recall bias and gene-environment dependence. Conclusions: Even if gene-environment dependence exists, we may still be able to identify gene-environment interactions even when misclassification bias is present.

Automated summary

This study aimed to evaluate the impact of recall bias on the identification of gene-environment interactions when the independence assumption is violated. The results showed that even if gene-environment independence is violated, it is still possible to identify gene-environment interactions by knowing the strength and direction of gene-environment dependence.