Scientists have used DNA methylation markers to measure the anti-aging effects of healthy diet and physical activity, reaching interesting, if at times contradictory, results .
Move, eat healthy, check your biological age
Physical activity (PA) and healthy diet are two powerful interventions that have time and again shown their potential to slow aging. Their importance is bolstered by the current lack of approved age-reversing drugs and therapies.
We have discussed methods of measuring the potential anti-aging effects of interventions through epigenetic clocks that derive our biological age from methylation patterns in our DNA. Although epigenetic clocks are not without their imperfections, as we discuss in this recent interview with Dr. Morgan Levine, the second-generation clock GrimAge is widely considered one of the best .
Epigenetic clocks give us the amazing ability to check any intervention for its anti-aging potential by simply adding a methylation blood test to the trial protocol. We should probably expect a deluge of such data in the near future, which would increase our understanding of the aging processes.
In this new study, the researchers applied GrimAge to the dataset that originated in DAMA – a two-year randomized interventional trial of physical activity and healthy diet in 219 postmenopausal women . DAMA required from its participants some changes in physical activity and in eating habits. The dietary changes were mostly along the lines of the Mediterranean diet, such as consuming more fruits, vegetables, legumes, fish, and whole grains along with less meat, refined grains, desserts, dairy products, and alcohol. The study also mandated the exclusive use of olive oil as dressing and cooking fat.
On the physical activity (PA) front, the subjects were required to up their PA levels to at least one hour of moderate activity per day at three times the resting metabolic rate (MET), thus providing 3 MET-hours’ worth of activity. This was in addition to more strenuous activity that added 6 to 10 MET-hours weekly. The subjects were divided into four groups: the PA group, the diet group, the PA + diet group, and the control group.
Interestingly, in addition to GrimAge, the researchers used a second metric called epigenetic mutation load (EML). Contrary to epigenetic clocks that use a specific subset of methylation sites that are thought to be associated with aging, EML is defined as the sum total of extreme methylation values per sample. EML is rarely used as a biomarker of aging, but it is known to increase with age. Although much of this increase can probably be explained by epigenetic drift (stochastic mutations that accumulate with time), EML has also shown some correlation with factors that are known to accelerate aging, such as smoking and alcohol intake, and with epigenetic clocks . The researchers suggest that EML and epigenetic clocks might be complementary in that they describe different aspects of aging.
Results: Some expected, some surprising
Using GrimAge, the researchers measured aging acceleration (AA), which they defined as the difference between predicted biological age and chronological age. Both GrimAgeAA and EML measurements were taken twice, at the beginning (baseline) and at the end of the study. Measuring at baseline proved informative in itself, since the values could be linked to various aspects of the subjects’ current lifestyle. For instance, GrimAgeAA was strongly affected by smoking and body mass index, with obesity being several times more detrimental than simply being overweight.
Among dietary habits, GrimAgeAA was heavily correlated with the intake of fruits and vegetables (you can guess the nature of the correlation: that’s right, eat more fruits and veggies if you want to live longer), but not with meat consumption. EML was correlated with processed meat consumption, but this was the only statistically significant correlation that EML showed at baseline.
The post-interventional results were a bit of a mixed bag as well. GrimAgeAA showed strong association with dietary interventions, and EML with the increase in physical activity, but not vice versa. Since GrimAge is a much more established biomarker of aging, it is tempting to conclude that physical activity might not be so good at slowing aging after all, but this is just one study. There are others that confirm the positive effect of physical activity on lifespan and healthspan . The discrepancies can also stem from the fact that while a 200+ sample size is considered respectable for an interventional study, it might be too small for accurate statistical analysis, especially when divided into four groups.
Importantly, this is an interventional anti-aging study in humans, and we still have few of those. It poses some interesting questions and pioneers the use of EML as a possible biomarker of aging, though its potential as such is still unclear. Despite its limitations, the study largely confirms what we know about the anti-aging potential of healthy diet and physical activity. As the researchers justly note, DAMA required from its participants only moderate and easily achievable changes in their lifestyle. The study seems to confirm that such changes, even if applied later in life, can have a meaningful anti-aging effect.
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 Fiorito, G., Caini, S., Palli, D., Bendinelli, B., Saieva, C., Ermini, I., … & Masala, G. (2021). DNA methylation-based biomarkers of aging were slowed down in a two-year diet and physical activity intervention trial: the DAMA study. Aging Cell, e13439.
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 Masala, G., Assedi, M., Caini, S., Ermini, I., Occhini, D., Castaldo, M., … & Palli, D. (2014). The DAMA trial: a diet and physical activity intervention trial to reduce mammographic breast density in postmenopausal women in Tuscany, Italy. Study protocol and baseline characteristics. Tumori Journal, 100(4), 377-385.
 Bergsma, T., & Rogaeva, E. (2020). DNA methylation clocks and their predictive capacity for aging phenotypes and healthspan. Neuroscience insights, 15, 2633105520942221.
 Reimers, C. D., Knapp, G., & Reimers, A. K. (2012). Does physical activity increase life expectancy? A review of the literature. Journal of aging research, 2012.
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