Sui Yihan, Wu Weimiao, Wang Zhong, Wang Jianxin, Wang Zuoheng, Wu Rongling
Center for Computational Biology, College of Biological Science and Technology, Beijing Forestry University, Beijing 100083, China. Tel.: +86-10-6233-6283; Fax: +86-10-6233-6164;
Brief Bioinform. 2014 Mar;15(2):319-26. doi: 10.1093/bib/bbs085. Epub 2013 Jan 17.
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.
表观遗传修饰可能通过基因表达调控在复杂疾病的形成和进展中发挥重要作用。利用全基因组关联研究（GWAS）可以系统地鉴定出导致人类疾病的表观遗传变异，尽管目前GWAS常用的病例对照设计中并未纳入表观遗传效应。在这里，我们表明通过将总体遗传效应分解为其不同成分，即加性、显性和表观遗传成分，可以将表观遗传修饰纳入病例对照研究中。我们描述了一种基于传统卡方检验方法来检验和估计每个成分显著性的通用程序。进行了模拟研究以探究该程序的检验效能和假阳性率，并为其实际应用提供建议。将表观遗传变异纳入GWAS可能会潜在地增进我们对遗传、环境和随机因素如何与表观等位基因相互作用以构建复杂疾病遗传结构的理解。
