No replies to this topic

[Steve H]

A new study has found that professional soccer players experience a drop in their biological age after a match, as measured by biomarkers assessed with state-of-the-art methylation clocks [1]. We asked Dr. Steve Horvath, the study’s co-author, to comment.

Clocks, stress, and exercise

Epigenetic clocks have become extremely popular in the longevity field, both as endpoints in studies and as commercial diagnostics marketed to longevity-conscious customers at a hefty price. These clocks, trained to predict chronological age, mortality, and/or disease, are based on some aspects of DNA methylation that closely track aging-associated states.

While the development of such clocks is among the most important breakthroughs in longevity in the last couple of decades, they have their drawbacks, such as susceptibility to external factors. For instance, a 2023 Harvard study showed that stress, such as a major surgery, a severe case of COVID-19, or pregnancy, can cause a transient increase in methylation age [2].

Physical activity is associated with huge health benefits. However, strenuous physical activity, such as that undertaken by elite athletes, can also be considered stressful. How, then, does it affect epigenetic clock readings?

Soccer meets science

This question is the focus of a new study, which involved taking hundreds of readings from about 20 professional soccer players from the elite German Bundesliga. Supporting personnel were also tested. “Experimental evidence suggests that exercise acts as a significant stressor, driving various physiological adaptations in the body, including changes in epigenetic mechanisms,” the authors write, explaining the study’s rationale.

The researchers used the advanced methylation-based clocks DNAmGrimAge2, a predictor of health and mortality, and DNAmFitAge, a predictor of physical fitness. Here, these methylation clocks were used to estimate the levels of various proteins in the blood.

The clocks showed transient decreases in biological age immediately after a match in players but not in supporting staff. The readings returned to baseline after a period of rest. The 90-minute strenuous exercise caused some interesting immunological changes, with one inflammation-associated protein, CRP, decreasing by 50%, and another one, the cytokine IL-6, increasing by 684% on average, as measured by their methylation proxies. Immune cell composition changed as well, with a 68% post-match decline in CD4 T-cells.

Steve Horvath explains

For context, we turned to one of the study’s authors, Dr. Steve Horvath, the name probably most associated with methylation clocks. Horvath is a co-founder of the Epigenetic Clock Development Foundation and a senior investigator at Altos Labs. This is what he had to say about the study:

The study showed that a single bout of very vigorous exercise, a 90-minute Bundesliga soccer match, shifted several epigenetic aging markers measured in saliva. Right after exercise, the GrimAge methylation clock dropped by about 31%. Because saliva DNA comes mostly from white blood cells, some of this shift likely reflects short-term changes in immune cell composition.

The big takeaway is that methylation clocks are dynamic and timing matters: a transient effect after intense activity can move these measures. It remains to be seen whether the same can be observed in blood, muscle or other tissues. In short, our epigenome is responsive on short timescales exciting for measurement science and crucial for designing longevity studies. Methylation age is one of several indicators of biological age and one needs to be careful about when and how to measure it.

We’ve learned that methylation clocks can be affected by multiple factors such as stress and (according to this paper) intense physical activity. Considering these effects, why are epigenetic clocks still so predictive of age/mortality?

Great question because it goes to the core of what aging clocks measure. A few facts are rock-solid: second-generation clocks like GrimAge are highly validated predictors of mortality across ages, sexes, and ancestries in both relatively healthy and clinically unwell cohorts with predictive performance comparable to many routine clinical biomarkers.

So how can these epigenetic clocks be predictive despite sensitivity to intense exercise? I have several thoughts on the subject. First, trait versus state. Clocks contain a stable, trait-like signal that reflects long-term biology (innate aging processes, chronic inflammation, harmful exposures such as metabolic stress, smoking, immune remodeling). Acute stressors add a short-lived, state-like wobble. Cohorts and trials average over the wobble; the stable signal carries the risk information.

Second, integration over time. GrimAge aggregates DNA-methylation surrogates of plasma proteins and smoking pack-years, i.e. features tied to cumulative risk. A single workout doesn’t erase years of biology, just as one salty meal doesn’t invalidate blood pressure.

Third, representation is not essence. It reminds me of Magritte’s painting “Ceci n’est pas une pipe.” A clock is a representation of biological age, not biological age itself. It can decrease briefly after a soccer match without meaning you got rejuvenated in 90 minutes.

I’d say that the practical takeaway for researchers is: standardize timing and pre-analytics. Avoid sampling immediately after vigorous activity (ideally allow about 24 hours), and collect at a consistent time of day. Decide a priori whether to adjust for estimated blood cell composition based on your causal question: if you want the cell-intrinsic signal, adjust; if you want the immune/physiological component that may carry mortality risk information, don’t. Otherwise, you may throw out valuable signal with the noise. Report sensitivity analyses both with and without cell-composition adjustment in your reports.

Keep blood tubes, methylation measurement platform, and bioinformatics pipeline consistent; apply batch correction with a locked statistical analysis plan. Consider adjusting for cell composition (deconvolution) or measure cell counts where feasible.

In general, use before and after treatment models. This allows for baseline-adjusted change and/or repeated measures models (linear mixed models) to dampen within-person noise.

How can these post-exercise shifts affect the potential usability/approval of epigenetic clocks in future clinical trials?

I don’t think this undermines their use in trials. Let me use a familiar analogy. Blood pressure spikes with exercise but blood pressure is an accepted surrogate endpoint for cardiovascular events and is used widely in trials. No one discards blood pressure because it’s variable, they standardize measurement. On a per-reading basis, GrimAge is less variable than blood pressure; the same logic applies.

For the me key question is why the shift after vigorous physical exercise? I think it likely is immune mobilization. Intense exercise demarginates leukocytes and transiently alters cell-type proportions which can nudge methylation-based estimates. By the way, many clocks are intentionally sensitive to immune biology; that sensitivity is part of why they predict mortality and morbidity outcomes.

The bottom line is, vigorous exercise can transiently shift some epigenetic age estimates, probably via immune dynamics but with routine standardization (similar as with blood pressure), GrimAge and related clocks are highly informative for risk stratification and as potential endpoints in clinical research.

We would like to ask you a small favor. We are a non-profit foundation, and unlike some other organizations, we have no shareholders and no products to sell you. All our news and educational content is free for everyone to read, but it does mean that we rely on the help of people like you. Every contribution, no matter if it’s big or small, supports independent journalism and sustains our future.

Yes I will donate❤️

Literature

[1] Brooke, R. T., Kocher, T., Zauner, R., Gordevicius, J., Milčiūtė, M., Nowakowski, M., Haser, C., Blobel, T., Sieland, J., Langhoff, D., Banzer, W., Horvath, S., & Pfab, F. Epigenetic Age Monitoring in Professional Soccer Players for Tracking Recovery and the Effects of Strenuous Exercise. Aging Cell, e70182. https://doi.org/10.1111/acel.70182

[2] Poganik, J. R., Zhang, B., Baht, G. S., Tyshkovskiy, A., Deik, A., Kerepesi, C., … & Gladyshev, V. N. (2023). Biological age is increased by stress and restored upon recovery. Cell metabolism, 35(5), 807-820.

View the article at lifespan.io