10.6084/m9.figshare.3530819.v1 Slade E. Slade E. Kraft P. Kraft P. Supplementary Material for: Leveraging Methylome-Environment Interaction to Detect Genetic Determinants of Disease Karger Publishers 2016 DNA methylation Epigenetics Epigene-environment interaction Power and sample size Measurement error 2016-08-05 09:40:00 Dataset https://karger.figshare.com/articles/dataset/Supplementary_Material_for_Leveraging_Methylome-Environment_Interaction_to_Detect_Genetic_Determinants_of_Disease/3530819 <strong><em>Objective:</em></strong> The association between DNA methylation and a trait of interest may depend on an environmental exposure, and incorrectly accounting for this dependence can lead to a reduction in power of the standard tests used in epigenome-wide association studies. We present the M-ME test to jointly test for the main effect of DNA methylation and methylation-environment interaction. <b><i>Methods:</i></b> Through simulation, we compare the power and type 1 error of the M-ME test to a standard marginal test (M test) and a standard interaction test (ME test) under 1,800 different underlying models. These models allow for methylation-environment correlation and measurement error in the exposure. <b><i>Results:</i></b> In many true underlying models, either the M test or the ME test has very low power, but the M-ME test has optimal or nearly optimal power to detect a DNA methylation effect in all models considered, including those with methylation- environment dependence and measurement error in the exposure. Type 1 error inflation occurs in the tests when the exposure is measured with error and correlated with DNA methylation. <b><i>Conclusion:</i></b> The M-ME test is an attractive choice for studies aiming to detect any DNA methylation association when little is known about the epigenetic associations a priori.