Meeting Abstract
Age specific patterning of DNA methylation (“epigenetic aging”) is the single best marker of biological age as it is strongly correlated with chronological age, the onset of age-related disease, and all-cause mortality. Epigenetic age predictors use loci specific changes in the status of DNA methylation across the genome to predict chronological age with astonishing accuracy. Discrepancies between chronological and epigenetic or “biological” age can be used to explore the molecular underpinnings that determine different aging trajectories. Further, important life history characteristics such as the onset of reproductive maturity and senescence are associated with epigenetic age, suggesting that accelerated epigenetic aging may have implications on the timing of ecologically important life history events. We aimed to identify and describe the age-related DNA methylome and develop an epigenetic clock for a model fish species, medaka (Oryzias latipes), using reduced representation bisulfite sequencing of 2-, 6-, and 12-month old animals. Our findings suggest that a substantial portion of methylation changes correlate with chronological age, with a greater proportion of change occurring early in life relative to late. Using just 39 of these age-associated loci, we have developed a model that is highly predictive of chronological age (cor = 0.9495) and provides the ability to assess biological age acceleration in the response to environmental factors. Here, we present preliminary tests for age acceleration and provide a characterization of the age-related loci which demonstrates the genomic distribution and functional associations of the age-related methylome. Our results contribute towards ongoing research attempting to elucidate the functional role of DNA methylation in aging.
