Abstract
Understanding the fundamental dynamics of epigenome variation during normal aging is critical for elucidating key epigenetic alterations that affect development, cell differentiation and diseases. Advances in the field of aging and DNA methylation strongly support the aging epigenetic drift model. Although this model aligns with previous studies, the role of other epigenetic marks, such as histone modification, as well as the impact of sampling specific CpGs, must be evaluated. Ultimately, it is crucial to investigate how all CpGs in the human genome change their methylation with aging in their specific genomic and epigenomic contexts. Here, we analyze whole genome bisulfite sequencing DNA methylation maps of brain frontal cortex from individuals of diverse ages. Comparisons with blood data reveal tissue-specific patterns of epigenetic drift. By integrating chromatin state information, divergent degrees and directions of aging-associated methylation in different genomic regions are revealed. Whole genome bisulfite sequencing data also open a new door to investigate whether adjacent CpG sites exhibit coordinated DNA methylation changes with aging. We identified significant 'aging-segments', which are clusters of nearby CpGs that respond to aging by similar DNA methylation changes. These segments not only capture previously identified aging-CpGs but also include specific functional categories of genes with implications on epigenetic regulation of aging. For example, genes associated with development are highly enriched in positive aging segments, which are gradually hyper-methylated with aging. On the other hand, regions that are gradually hypo-methylated with aging ('negative aging segments') in the brain harbor genes involved in metabolism and protein ubiquitination. Given the importance of protein ubiquitination in proteome homeostasis of aging brains and neurodegenerative disorders, our finding suggests the significance of epigenetic regulation of this posttranslational modification pathway in the aging brain. Utilizing aging segments rather than individual CpGs will provide more comprehensive genomic and epigenomic contexts to understand the intricate associations between genomic neighborhoods and developmental and aging processes. These results complement the aging epigenetic drift model and provide new insights.