A case-control design for testing and estimating epigenetic effects on complex diseases

Yihan Sui, Weimiao Wu, Zhong Wang, Jianxin Wang, Zuoheng Wang, Rongling Wu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Epigenetic modifications may play an important role in the formation and progression of complex diseases through the regulation of gene expression. The systematic identification of epigenetic variants that contribute to human diseases can be made possible using genome-wide association studies (GWAS), although epigenetic effects are currently not included in commonly used case - control designs for GWAS. Here, we show that epigenetic modifications can be integrated into a case - control setting by dissolving the overall genetic effect into its different components, additive, dominant and epigenetic. We describe a general procedure for testing and estimating the significance of each component based on a conventional chi-squared test approach. Simulation studies were performed to investigate the power and false-positive rate of this procedure, providing recommendations for its practical use. The integration of epigenetic variants into GWAS can potentially improve our understanding of how genetic, environmental and stochastic factors interact with epialleles to construct the genetic architecture of complex diseases.

Original languageEnglish (US)
Article numberbbs085
Pages (from-to)319-326
Number of pages8
JournalBriefings in bioinformatics
Issue number2
StatePublished - Mar 2014

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology


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