Implementing a method for studying longitudinal DNA methylation variability in association with age.

ABSTRACT: Interindividual variability of DNA methylation is a mechanism of the epigenetic drift in aging. Studies on cross-sectional data have discovered a change in methylation variability in association with age. However, thus far, no method explored DNA methylation variability in longitudinal data, which was the aim of this study. First, we performed a simulation study to explore methods for estimating methylation variability in longitudinal data. Second, an epigenome-wide association study (EWAS) on 1011 longitudinal samples (385 individuals followed up to 18 years) was performed to identify age-varying methylation sites using these methods. Following Breusch-Pagan test of heteroscedasticity, we showed that a linear regression model, where the residuals were used in a mixed effect model with a r

SUBMITTER: Wang Y 

PROVIDER: S-EPMC6291263 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature