PT  - JOURNAL ARTICLE
AU  - Thomas Battram
AU  - Tom R. Gaunt
AU  - Doug Speed
AU  - Nicholas J. Timpson
AU  - Gibran Hemani
TI  - Exploring the variance in complex traits captured by DNA methylation assays
AID  - 10.1101/2020.10.09.333542
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.10.09.333542
4099  - http://biorxiv.org/content/early/2020/10/10/2020.10.09.333542.short
4100  - http://biorxiv.org/content/early/2020/10/10/2020.10.09.333542.full
AB  - Following years of epigenome-wide association studies (EWAS), traits analysed to date tend to yield few associations. Reinforcing this observation, we conducted EWAS on 400 traits and 16 yielded at least one association at the conventional significance threshold (P<1×10−7). To investigate why EWAS yield is low, we formally estimated the proportion of phenotypic variation captured by 421,693 blood derived DNA methylation markers (h2EWAS) across all 400 traits. The mean h2EWAS was zero, with evidence for regular cigarette smoking exhibiting the largest association with all markers (h2EWAS=0.42) and the only one surpassing a false discovery rate < 0.1. Though underpowered to determine the h2EWAS value for any one trait, h2EWAS was predictive of the number of EWAS hits across the traits analysed (AUC=0.7). Modelling the contributions of the methylome on a per-site versus a per-region basis gave varied h2EWAS estimates (r=0.47) but neither approach obtained substantially higher model fits across all traits. Our analysis indicates that most complex traits do not heavily associate with markers commonly measured in EWAS within blood. However, it is likely DNA methylation does capture variation in some traits and h2EWAS may be a reasonable way to prioritise traits that are likely to yield associations.Competing Interest StatementThe authors have declared no competing interest.