Estimation of a significance threshold for epigenome ‐wide association studies

ABSTRACT
Epigenome‐wide association studies (EWAS) are designed to characterise population‐level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA‐methylation status at cytosine‐guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome‐wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of for the 450k array, and a genome‐wide estimate of . We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type‐1 errors at the desired level.

Source: Genetic Epidemiology - October 16, 2017 Category: Epidemiology Authors: Ayden Saffari, Matt J. Silver, Patrizia Zavattari, Loredana Moi, Amedeo Columbano, Emma L. Meaburn, Frank Dudbridge Tags: RESEARCH ARTICLE Source Type: research