The development of a reliable and accurate biomarker of biological age is an important step for the longevity science field. Testing potential rejuvenation therapies is at present a drawn-out and expensive process, as the only truly effective way to determine outcomes is to wait and see. That requires years and millions of dollars in funding for mouse studies, a cost that greatly restricts the amount of experimentation and exploration it is possible to carry out, even for the better funded research groups. If instead a biomarker test could be applied shortly before and shortly after a treatment in order to assess its potential, that would greatly accelerate progress in the field. Epigenetic clocks based on assessment of patterns of DNA methylation are presently the most promising candidate for such a biomarker of aging, and here researchers discuss the behavior of presently established clocks in mice and humans.
Epigenetic clocks provide powerful tools to evaluate nutritional, hormonal, and genetic effects on aging. What can we learn from differences between species in how these clocks tick? One of the most fascinating findings in human aging is that it is associated with highly reproducible DNA methylation (DNAm) changes. DNAm levels at age-associated CG dinucleotides (CpG sites) can be integrated into epigenetic age predictors, which provide robust biomarkers to estimate chronological age. With the advent of more and more publically available DNAm profiles, such aging signatures were further developed to facilitate higher precision in age predictions, particularly for blood samples. Probably the most commonly used epigenetic aging signature is based on DNAm levels at 353 CpG sites and facilitates relatively precise age predictions for many human tissues: the median “error” (MAE), defined by the median absolute difference between DNAm age and chronological age, is usually less than 4 years.
Now – about 6 years after the first epigenetic clock paper – similar age predictors have been established for mice. Again, they were initially described for defined murine tissues, specifically liver and blood, taking into account the fact that there are notoriously large differences in the epigenetic makeup of cells from different tissues. However, it is also possible to derive a multi-tissue murine DNAm age predictor, in analogy to the most commonly used human clock. The signature is based on 329 CpGs and has been validated for cortex, muscle, lung, liver, and heart tissue. Overall, the multi-tissue age predictor reached a MAE of less than 4 weeks, although how it performs in other tissues has yet to be shown.
Studies indicate that the epigenetic clocks of mice tick faster than those of humans. This can be anticipated because the maximum life-span of mice (about 2 years) is much shorter than it is in humans (about 85 years). If the molecular changes of aging are linked to life expectancy and generation time, then this might support the notion that aging reflects a controlled evolutionary process. However, there is still an open debate on whether aging is due to an accumulation of cellular defects, or is driven by a developmental mechanism. Either way, comparison of epigenetic clocks in mice and men will provide new insights into the regulation of age-associated DNAm.
Direct comparison of age-associated CpGs in mice and men indicated that there is a moderate but significant association between the two species. It is not always trivial to identify orthologous CpG sites, and further interspecies comparison will be required to better understand similarities and differences of age-associated genomic regions. However, the overlap of age-associated CpGs in age predictors for human and mice seems to be rather low, and hence epigenetic clocks need to be trained specifically for different species. In terms of function, age-associated CpGs in humans and mice seem to be enriched in genes that are involved in morphogenesis and development. However, in both species age-associated DNAm changes are not generally reflected at the gene expression level – and thus the biological relevance remains largely unclear.
Mouse DNAm clocks provide powerful tools to study longevity interventions in one of the most relevant model organisms for aging research. These signatures were initially trained to correlate with the “real” chronological age of mice – but aging rates may differ between individuals. In fact, there is evidence that epigenetic clocks rather reflect the biological age, which is related to the perceived aging process of an organism. In analogy, it was previously demonstrated that human DNAm age is related to life expectancy: accelerated epigenetic age is associated with higher all-cause mortality. This finding has been validated in various additional cohorts and with different epigenetic age predictors. Furthermore, human epigenetic aging rates have been shown to be significantly associated with sex, race/ethnicity, and some disease risk factors. In mice, there was no clear difference in predicted DNAm age of male and females. However, ovariectomy, which reduces the average life span in female rats, results also in significant age acceleration. Caloric restriction or dietary rapamycin treatment, both of which result in increased life expectancy of mice, reduced epigenetic age. In humans, specific diet seems to have a less pronounced impact on epigenetic age, but there is significant association of DNAm age and body mass index (BMI). Apparently, different parameters can affect biological aging in mice and men.