Leveraging Methylome-Environment Interaction to Detect Genetic Determinants of Disease

Emily Slade, Peter Kraft

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Objective: 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. Methods: 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. Results: 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. Conclusion: 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.

Original languageEnglish
Pages (from-to)26-34
Number of pages9
JournalHuman Heredity
Issue number1
StatePublished - Oct 1 2016

Bibliographical note

Publisher Copyright:
© 2016 S. Karger AG, Basel.


  • DNA methylation
  • Epigene-environment interaction
  • Epigenetics
  • Measurement error
  • Power and sample size

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)


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