90 Minutes to Reverse Biological Age by 17.8 Years? New Study by the Father of Epigenetic Clock: Not a Measurement Error—Immune Cell Distribution Is the Key!

For those who love sports, the feeling of being "drained" after a sweaty workout is all too familiar. Sore muscles and rapid breathing truly record the body's efforts. But you must have had this wonderful experience: after exercise, you suddenly feel refreshed, as if you've gotten several years younger!

Remarkably, this renewed state may not just be a psychological effect. Recently, a study by scientists from multiple top international research institutions published in Aging Cell found that this feeling may be biologically real: after an intense soccer match, athletes' biological age can instantly reverse by more than a decade!

Of course, this number sounds exaggerated. How could such an astonishing result be achieved in just 90 minutes of exercise? Is it a real physiological miracle or a "beautiful misunderstanding" caused by measurement tools under extreme conditions?

For a long time, our understanding of genetics has seemed deterministic: the genes inherited from our parents largely determine many of our physiological traits and disease risks. However, the truth is quite different. You’ll find that people with vastly different lifestyles have significantly varying aging processes, and exercise, diet, and even stress silently alter the trajectory of our lives.

The answer lies in epigenetics. The prefix "Epi-" means "above," referring to a dynamic regulatory system that exists beyond our inherent genes. It does not change the genes themselves but determines when and where genes are expressed or silenced[2]. Among the most widely studied epigenetic mechanisms is DNA methylation[3].

The appearance of such groups on DNA isn’t necessarily a bad thing. In fact, abnormal patterns of these marks are observed in various diseases[4], and an interesting finding is that they undergo predictable systematic changes with age[5]. Based on this, the first generation of epigenetic clocks was developed, which predict people’s actual physiological age by analyzing DNA methylation patterns[6].

However, version 1.0 clocks cannot answer questions such as whether a person is healthy or how fast their aging rate is. To address this deficiency, scientists have developed second-generation clocks (such as GrimAge[7] and PhenoAge[8]). These clocks directly assess an individual’s overall health status and aging rate by integrating epigenetic information related to health outcomes like all-cause mortality and chronic disease risk.

Building on this, newer generations of clocks have even evolved to reflect specific physiological functions. For example, the DNAmFitAge (fitness age) clock featured in this study can quantify a person’s cardiorespiratory endurance and provide a specific fitness age assessment.

Now, let’s return to the puzzling soccer field. What happens when advanced epigenetic clocks meet professional athletes in a state of physiological exhaustion?

To capture such fleeting physiological changes, a single measurement is far from sufficient. Thus, the essence of this study’s design lies in its grasp of timing: longitudinally comparing three key time points—before the game, immediately after the game, and after rest—to fully map the body’s dynamic changes during the "stress-recovery" cycle.

Data showed that athletes’ epigenetic clocks underwent an astonishing reversal after the game. For instance, DNAmGrimAge2, which better reflects overall health, decreased by an average of 7.07 years (especially in midfielders who ran the most, with a decrease of 17.8 years!). Meanwhile, the fitness-related DNAmFitAge recorded a decrease of 4.76 years.

Can this "younger by several years" effect be maintained? The answer is no. The entire process follows a clear V-shaped curve! Athletes’ biological age drops to its lowest point immediately after the game ends. However, after 24 hours of rest and recovery, the values basically return to pre-game levels (it seems to be just a trial experience...).

Such an exaggerated reversal—does it mean that the epigenetic clocks we have long trusted have inherent shortcomings? Under extreme physiological stress like intense exercise (with changes in body fluids, metabolites, and even inflammatory factors), could the detection process be interfered with, resulting in unreliable readings?

Alternatively, it’s possible that the clocks are not inaccurate but, with high sensitivity, have recorded real and intense biological events within the body—meaning that the measured object, our own physiological state, has indeed undergone drastic changes in a short period.

Which hypothesis holds? Let’s look at cell-level research results: the composition of immune cells in athletes’ saliva samples changed dramatically— the relative proportion of CD4+ T lymphocytes (which play a central regulatory role in adaptive immunity) decreased by nearly two-thirds, while the relative proportion of granulocytes, a major component of the innate immune system, increased by nearly half!

This change in cell proportion has a specific term in immunology: "exercise-induced immune cell redistribution"[9]. Don’t be mistaken—this does not indicate impaired immune function but an active, purposeful physiological mobilization by the body.

Under the stress of high-intensity exercise, the body redistributes immune cells to cope with minor muscle tissue damage and potential inflammation. For example, lymphocytes like CD4+ T cells migrate to peripheral tissues (such as damaged muscles) to perform immune surveillance and regulatory functions, while granulocytes are mobilized from storage sites like bone marrow into the bloodstream, ready to respond to damage and repair.

It seems the second hypothesis is more valid. Changes in FitAge readings are not due to inaccuracy but precisely quantify the body’s activation of high-intensity stress and repair processes (suggesting it can be confidently applied in sports science).

But the excitement of this study doesn’t end here. Beyond reflecting the present, FitAge can even glimpse the future—identifying individuals at high risk before injuries occur!

The experimental process is simple: collect physiological data from all players mid-season, divide them into "injured group" and "non-injured group" based on whether they get injured after sampling, and then compare the differences in physiological indicators between the two groups before and after the game.

Results showed that the predicted FitAge value of the "non-injured group" decreased 24 hours after the game compared to before the game, indicating that their bodily systems could effectively cope with exercise-induced stress. The "injured group" showed the opposite trend: their predicted FitAge value increased rather than decreased after the game (a sign that the body is saying: "I can’t take it anymore; my recovery capacity is exhausted").

Moreover, these abnormal readings are highly consistent with changes in other physiological indicators!

Take the traditional muscle damage marker—creatine kinase (CK) levels—as an example. CK levels in the "injured group" increased significantly after the game, far exceeding those in the "non-injured group," indicating that their bodies indeed endured greater physiological load and muscle damage.

Immune system analysis at the cellular level also tells the same story: there are significant differences in the post-game reorganization and recovery patterns of immune cells between the "injured group" and "non-injured group." For example, the recovery trend of the "non-injured group" is more regular, while the immune response of the "injured group" is more disordered.

In summary, the abnormal readings of the FitAge clock are highly consistent with traditional damage markers and immune system disorders, going beyond mere correlation. It visualizes subjective fatigue, quantifies potential risks, and provides a relatively objective scientific basis for coaches and athletes when making difficult decisions between training and rest.

References
[1] Brooke RT, 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. 2025 Jul 28:e70182. doi: 10.1111/acel.70182. Epub ahead of print. PMID: 40726009.
[2] Tetsu Kinoshita, & Steven E. Jacobsen (2012). Opening the Door to Epigenetics in PCP. Plant and Cell Physiology, 53 (5), 763-765.
[3] Basavarajappa, B. S., & Subbanna, S. (2016). Epigenetic Mechanisms in Developmental Alcohol-Induced Neurobehavioral Deficits. Brain sciences, 6(2), 12.
[4] Han J. J. (2024). The ticking of aging clocks. Trends in endocrinology and metabolism: TEM, 35(1), 11–22. https://doi.org/10.1016/j.tem.2023.09.007
[5] Berdyshev, G. D., Korotaev, G. K., Boiarskikh, G. V., & Vaniushin, B. F. (1967). Nukleotidnyĭ sostav DNK i RNK somaticheskikh tkaneĭ gorbushi i ego izmenenie v technie neresta [Nucleotide composition of DNA and RNA from somatic tissues of humpback and its changes during spawning]. Biokhimiia (Moscow, Russia), 32(5), 988–993.
[6] Horvath, S., Zhang, Y., Langfelder, P., et al. (2012). Aging effects on DNA methylation modules in human brain and blood tissue. Genome biology, 13(10), R97.
[7] Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, Hou L, Baccarelli AA, Li Y, Stewart JD, Whitsel EA, Assimes TL, Ferrucci L, Horvath S. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019 Jan 21;11(2):303-327. doi: 10.18632/aging.101684. PMID: 30669119; PMCID: PMC6366976.
[8] Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, Whitsel EA, Wilson JG, Reiner AP, Aviv A, Lohman K, Liu Y, Ferrucci L, Horvath S. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018 Apr 18;10(4):573-591. doi: 10.18632/aging.101414. PMID: 29676998; PMCID: PMC5940111.
[9] Campbell JP, Turner JE. Debunking the Myth of Exercise-Induced Immune Suppression: Redefining the Impact of Exercise on Immunological Health Across the Lifespan. Front Immunol. 2018 Apr 16;9:648. doi: 10.3389/fimmu.2018.00648. PMID: 29713319; PMCID: PMC5911985.