Implementing a method for studying longitudinal DNA methylation variability in association with age. Issue 8 (3rd August 2018)

• Record Type: Journal Article
• Authors: Wang, Yunzhang; Pedersen, Nancy L.; Hägg, Sara
• Is Part Of: Epigenetics. Volume 13:Issue 8(2018)
• Page Start: 866
• Page End: 874
• Publication Date: 2018-08-03
• Subjects: DNA methylation variability -- aging -- longitudinal study; Epigenesis -- Periodicals; Epigenetica; 572.86505
• DOI: 10.1080/15592294.2018.1521222
• Languages: English
• ISSNs: 1559-2294

Abstract

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 random intercept, properly estimated the change of interindividual variability over time. Our EWAS identified 570 CpG sites where methylation variability was significantly associated with age ( P < 1.3 × 10 −7 ). Gene regions of identified loci were enriched in nervous system development functions. In conclusion, we provide a method for analyzing methylation variability in longitudinal data and further identified age-varying methylation loci in a longitudinal analysis using these methods.