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Abstract
We describe a methodology for detecting differentially methylated regions (DMRs) and variably methylated regions (VMRs), in data from Infinium 450K arrays that are very widely used in epigenetic studies. Region detection is more specific than single CpG analysis as it increases the extent of common findings between studies, and is more powerful as it reduces the multiple testing problem inherent in epigenetic whole-genome association studies (EWAS). In addition, results driven by single erroneous probes are removed. We have used multiple publicly available Infinium 450K data sets to generate a consensus list of DMRs for age, supporting the hypothesis that aging is associated with specific epigenetic modifications. The consensus aging DMRs are significantly enriched for muscle biogenesis pathways. We find a massive increase in VMRs with age and in regions of the genome associated with open chromatin and neurotransmission. Old age VMRs are significantly enriched for neurotransmission pathways. EWAS studies should investigate the role of this interindividual variation in DNA methylation, in the age-associated diseases of sarcopenia and dementia.
Highlights
Epigenetic marks hold promise as biomarkers for stratifying patients for intervention in diseases with environmental and developmental causality (Gluckman et al, 2009)
We develop a region discovery method tailored to Infinium 450K methylation data, for differentially methylated region (DMR) and variably methylated region (VMR) discovery
Our results suggest that some aging DMRs are general across the life course, the majority are specific to the age range examined; that is, different regions vary in methylation during childhood than in middle age
Summary
Epigenetic marks hold promise as biomarkers for stratifying patients for intervention in diseases with environmental and developmental causality (Gluckman et al, 2009). Unlike DNA biomarkers, epigenetic markers are affected by both the patient’s inherited genotype (Gibbs et al, 2010) and environmental exposures (Heijmans et al, 2008; McGowan et al, 2011). Efforts to discover DNA methylation marks associated with a wide range of diseases have been initiated including epigenome-wide association. Accepted for publication 31 August 2013 studies (EWAS) (Ng et al, 2012). These studies are aided by advances in technologies to assay genomewide DNA methylation patterns such as the Illumina Infinium HumanMethylation450 BeadChip ArrayTM (Infinium 450K)
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