Evidence for the Epigenetic Clock to Underestimate Age in Later Life
In recent years, the research community has put in ever more effort into the development of epigenetic clocks capable of assessing biological age. This focus has led to the discovery of various issues, as the nature of epigenetics of aging is further explored, challenges that will need to be understood and addressed in order to enable the practical use of epigenetic clocks. For example that degree of fitness doesn't appear to much affect epigenetic age, which is problematic to say the least, as we know that it affects the progression of aging. Here, researchers identify a systemic issue with assessment of epigenetic age in older individuals.
Subject age is a piece of data available in almost every study in which DNA methylation profiles are obtained. There is thus a huge amount of cross-sectional data in which it can be seen that the methylation level of many CpG sites varies with subject age, which, amongst other processes, could reflect developmental changes, cellular aging, cumulative environmental effects, and changes in cell-type composition.
Horvath used a large collection of publicly available DNA methylation data on multiple tissue types to train and test a model for age prediction from 353 CpG loci. This "epigenetic clock" continues to be widely used and is extremely valuable as a way of estimating ages of samples from unknown donors and possibly as an indicator of whether there are alterations in the aging rate of certain tissues or individuals. Although the epigenetic clock provides an estimate of age, the testing data used in generating this clock did not have a large representation of tissue from elderly individuals and as such it is unclear if the clock is accurate in older age groups, or those with age-related diseases.
The model systematically underestimates age in tissues from older people. This is seen in all examined tissues but most strongly in the cerebellum and is consistently observed in multiple datasets. Epigenetic age acceleration is thus age-dependent, and this can lead to spurious associations. The current literature includes examples of association tests with age acceleration calculated in a wide variety of ways. In conclusion, the concept of an epigenetic clock is compelling, but caution should be taken in interpreting associations with age acceleration. Association tests of age acceleration should include age as a covariate.
Higher blood levels of carotenoids, including lycopene, alpha- and beta-carotene, lutein+zeaxanthin, and beta-cryptoxanthin were associated with a younger epigenetic age. Dietary factors that were significantly associated with a younger epigenetic age were dairy, whole grains, fruit, and vegetables. In contrast, dietary fat intake and red meat were associated with older epigenetic ages (Lu et al. 2019, doi: 10.18632/aging.101684):
If your goal is optimal health and longevity, eating foods that are rich in these nutrients may be an important strategy for slowing epigenetic aging. Which foods contain these nutrients? Carotenoids are found almost exclusively in vegetables and fruits. For example, lycopene is enriched in watermelon and tomatoes, alpha- and beta-carotene is high in carrots, orange vegetables (sweet potato, squash, pumpkin) and greens, lutein+zeaxanthin is prevalent in greens, and beta-cryptoxanthin's highest levels are found in butternut squash and red bell peppers.
See: Epigenetic Aging: Can It Be Slowed With Diet? by Michael Lustgarten
https://michaellustgarten.com/2019/12/07/slowing-epigenetic-aging-with-diet/