Blizard Institute of Cell and Molecular Science, Barts and The London School of Medicine and Dentistry, Queen Mary, University of London, London, UK.
Nat Rev Genet. 2011 Jul 12;12(8):529-41. doi: 10.1038/nrg3000.
Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.
尽管全基因组关联研究 (GWAS) 在确定与常见疾病相关的基因座方面取得了成功,但仍有相当一部分因果关系尚未得到解释。基因组技术的最新进展使我们能够开始对与人类疾病相关的表观遗传变异进行大规模研究,特别是 DNA 甲基化的变异。这种全基因组关联研究 (EWAS) 提供了新的机会,但也带来了新的挑战,这些挑战在 GWAS 中不会遇到。我们讨论了 EWAS 的设计、队列和样本选择、统计意义和功效、混杂因素和后续研究。我们还讨论了如何将 EWAS 与 GWAS 相结合,以帮助对功能分析的复杂 GWAS 单倍型进行剖析。