Epigenetix (United States)

ABSTRACTDetermining exact age in wild odontocetes is essential for understanding population dynamics, survival, and reproduction, yet remains logistically challenging. Although epigenetic ageing is emerging as a valuable approach, only nine species‐specific clocks currently exist. Most have been calibrated using known‐age animals in human care or well‐studied wild populations. Only three previous studies have used dental ages from stranded or bycaught individuals. This is due to concerns that dental age inaccuracies, especially in older animals, may affect epigenetic clock performance. To explore this, we developed the first species‐specific epigenetic clock for common dolphins (Delphinus delphis), analysing DNA methylation at 37,492 cytosine‐phosphate‐guanine sites in skin samples from stranded and bycaught dolphins with estimated dental ages. Elastic net models with Leave‐One‐Out Cross‐Validation were applied to three subsets: the ‘relaxed’ subset (all individuals; n = 75, median absolute error (MAE) = 2.02, r = 0.81, R2 = 0.66), the ‘strict’ subset (excluding individuals with minimum dental age estimates only; n = 73, MAE = 2.29, r = 0.81, R2 = 0.66), and the ‘restricted’ subset (excluding outliers with prediction errors > 6 years; n = 63, MAE = 1.80, r = 0.91, R2 = 0.82) to compare performance. Our models consistently underestimated the age of dolphins > 16 years, even when minimum dental ages were applied, suggesting that absolute errors between dental and epigenetic estimates are unlikely to reflect the dental ageing error. Additionally, post‐mortem decomposition condition code (DCC 1 to 3) did not affect age prediction, signalling promise for future epigenetic clocks calibrated with strandings and bycaught individuals.

ABSTRACTStrategies to slow the aging process or mitigate its consequences on health rely on the validation of minimally‐invasive biomarkers of aging that can be used to track aging and test the effectiveness of antiaging interventions. Study of aging in a nonhuman primate species offers a robust translational approach to achieving these aims, avoiding wide differences in genetics and environmental exposures that confound human aging studies. As epigenetic age appears to predict biological aging, biomarkers linked to epigenetic aging should be especially valuable in identifying individual differences in aging progression and documenting the impact of antiaging strategies. Proteins are the final effectors in most signaling pathways, indicating that alteration in levels of circulating proteins potentially offers an informative and valuable quantitative index of aging. Accordingly, a proteomic analysis was conducted on matching CSF and plasma samples collected from a large group of African green monkeys, with epigenetic ages ranging from young to old as determined by differential methylation of blood DNA. In addition to analyzing the data with linear statistical models, a gradient boosting machine learning technique was employed to identify not only individual CSF and plasma proteins that correlated with aging progression but also groups of proteins that could be used as predictors of global aging and of specialized aspects of aging such as inflammation. Overall, this study identified new CSF and plasma protein targets for understanding aging biology, together with identifying biomarkers to track changes in the rate of biological aging in a translationally relevant nonhuman primate model.

ABSTRACTKnowledge of animal age is essential to wildlife managers for obtaining meaningful and accurate insights into demographic parameters. A common approach to aging wildlife, including bears (Ursus spp.), has been extracting a tooth during physical capture and counting the cementum annuli. Limitations to tooth‐based aging include questionable accuracy and differing results based on the observer and laboratory. DNA methylation‐based epigenetic aging clocks have been developed for many species but not yet for polar bears (Ursus maritimus). We generated DNA methylation data from whole blood samples (n = 109) obtained during live capture operations from polar bears of known age in the Chukchi Sea and southern Beaufort Sea subpopulations. We used these samples to calibrate a species‐specific epigenetic clock to estimate polar bear chronological age from DNA methylation (DNAm) age. The final polar bear clock was highly accurate (r = 0.97) with a median absolute error of approximately 9 months. We applied the polar bear clock to 74 blood samples from live‐captured polar bears with a cementum annuli‐estimated age. Predicted age estimates for these bears ranged from 1.43 to 18.63 years compared to the estimated tooth age range of 3.23–25.27. These epigenetic clocks can be used for polar bear research and management where accurate estimates of age are needed for estimating demographic parameters.