Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka

Abstract

Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome (“epigenetic aging”) can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka ( Oryzias latipes ). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.

Age estimation in fishes using epigenetic clocks: Applications to fisheries management and conservation biology

“…Using medaka (Oryzias latipes) between 2 and 12 months of age and RRBS (Bertucci et al, 2021) built an epigenetic clock using liver samples. Furthermore, they showed that exposure to ionizing radiation during early development caused epigenetic age acceleration.…”

“…Furthermore, they showed that exposure to ionizing radiation during early development caused epigenetic age acceleration. This study is also important because it sets the basis to further explore aging-by-environment interactions (Bertucci et al, 2021). More recently, Weber et al (2022) developed epigenetic clocks for two species present in the Gulf of Mexico, the Northern red snapper (Lutjanus campechanus) and the Red grouper (Epinephelus morio).…”

Development of DNA methylation‐based epigenetic age predictors in loblolly pine (Pinus taeda)

“…Following the generation of our elastic net epigenetic clocks, we performed BLAST searches of 400 bp regions centered around each clock cytosine and used GenomicRanges to determine the genomic contexts for these sites (genes and CpG islands, shores, shelves, or open seas). Bertucci et al (2021) demonstrated that epigenetic clocks constructed using elastic net approaches on small sample sizes may be overfit, and linear models constructed using cytosines for which the relationship between methylation status and age is greatest…”

Genome‐wide DNA methylation patterns harbour signatures of hatchling sex and past incubation temperature in a species with environmental sex determination

“…These features have led biomedical fields to turn to DNAm‐based biomarkers to gain insight into biological ageing (Horvath, 2013 ; Horvath & Raj, 2018 ), contaminant exposure (Cardenas et al, 2017 ; Green et al, 2016 ; Gruzieva et al, 2017 ; Joubert et al, 2016 ), and the developmental origins of adult health and disease (Felix & Cecil, 2019 ; Heijmans et al, 2008 ). More recently, the ecological sciences have followed suit, harnessing the potential of the DNA methylome to understand life‐history variation (Anderson et al, 2021 ; Cayuela et al, 2021 ; de Paoli‐Iseppi et al, 2017 ; Lindner et al, 2021 ; Parrott & Bertucci, 2019 ), organismal health (Crossman et al, 2021 ; Hu et al, 2018 ; Lea et al, 2016 ), exposure to environmental stressors (Bertucci et al, 2021 ; Guillette et al, 2016 ; Liew et al, 2018 ; Mäkinen et al, 2022 ; Parrott, Bowden, et al, 2014 ) and developmental plasticity (Laubach et al, 2019 ; Navarro‐Martín et al, 2011 ; Parrott, Kohno, et al, 2014 ; von Holdt et al, 2021 ). Collectively, these studies indicate that DNAm patterns at discrete loci in nonlethally sampled tissues (e.g., blood) provide insight into fundamental aspects of an individual’s biology, health status and past environmental experience that would otherwise be nearly impossible to measure.…”