Old Hearts Get Younger in Young Bodies — What It Means for Aging | Dr Jesse Poganik

Summary

The discussion explores whether biological age can change independently of chronological age, and what this means for aging research and medicine.

Stress, recovery, and biological age

Jesse Poganik describes research that began by testing how quickly DNA-methylation “epigenetic clocks” respond to interventions. Initial short drug experiments in mice showed no detectable change, so the research shifted to severe physiological stress and subsequent recovery.

• In heterochronic parabiosis, young and old mice are surgically connected so they share circulation. The young mouse’s epigenetic age rose while exposed to old circulation. After the animals were separated and the young mouse recovered, its measured biological age returned toward its original level.
• The old mouse showed a different pattern: its biological age decreased during exposure to young circulation, and the decrease persisted for months after separation. Related work reported that these old mice also lived longer than controls.
• In human datasets, pregnancy, severe COVID-19, and major surgery were associated with temporary increases in measured biological age, followed by a return toward baseline during recovery. Multiple groups have since replicated the pregnancy finding. Sleep deprivation was also mentioned as a model of short-term age changes.

These findings emphasize that a single measurement may not reveal whether an apparent age change is lasting. Longitudinal measurements are needed, though their cost and practical demands can limit how often they are collected.

What aging biomarkers can—and cannot—tell us

Epigenetic clocks use selected DNA-methylation sites, or CpGs, to estimate biological age. The sites chosen by a statistical model are not necessarily uniquely important in biology: if two sites carry similar information, a regression model may retain one and discard the other. How methylation changes relate to gene expression and other biological processes remains incompletely understood.

Changes in methylation, RNA, and proteins do not always correspond neatly. Untargeted metabolomics can produce large datasets, but only a small fraction of detected signals may be identified as specific metabolites. Differences between platforms also make datasets difficult to compare.

Proteomics is becoming more prominent because many platforms measure standardized panels of proteins, making results easier to combine across studies. Protein measurements can also be easier to interpret biologically, and plasma proteins associated with particular organs can be used to estimate organ-specific age. Measuring proteins is already routine in clinical laboratories, though high-throughput panels still involve trade-offs between breadth, cost, and practicality.

A useful aging biomarker should ultimately predict outcomes that matter in real life, such as chronic disease, ability to function, or survival. Whether a biomarker must be mechanistically interpretable or causal remains debated. An unexplained marker may still be useful if it reliably predicts outcomes, although understanding its mechanism could help guide research.

Transplanted hearts and “biological age assimilation”

To investigate whether age-related effects in parabiosis are caused by blood or by the broader environment of an organism, Poganik’s team studied transplanted hearts.

• In mice, old hearts transplanted into young animals became biologically younger by several DNA-methylation clocks; young hearts transplanted into old animals became biologically older.
• The researchers also examined the recipient’s own heart, liver, and blood. They did not detect corresponding age changes in those tissues using methylation measurements.
• In human transplant data, methylation-clock results from a small set of biopsy samples showed a similar pattern: donor hearts tended to reflect the recipient’s biological age. Analyses of clinical records also found that some measures of heart function were more consistently associated with recipient age than donor age.

The researchers call this pattern biological age assimilation. The human findings are preliminary and require further confirmation. They may have implications for organ-donor selection and for anti-aging strategies that replace or rejuvenate only one tissue. A young organ alone may not rejuvenate the rest of an older body, and the host environment may influence the transplanted organ.

Biological rejuvenation versus reversing aging

Poganik distinguishes aging as an ongoing process from biological age as a measured state or set of indicators. The researchers argue that biological rejuvenation may be achievable even if literally reversing the aging process is not.

An important test of a rejuvenation claim is whether its effects persist after an intervention ends. The discussion also stresses the need for more frequent, longitudinal monitoring to distinguish durable effects from temporary fluctuations.

Research directions

Poganik’s laboratory plans to continue work on transplantation and human data, investigate pregnancy as a model of changing biological age, and study drug repurposing. A key challenge in drug research is distinguishing an effect on biological aging from the effect of treating a disease, since disease itself can alter biological-age markers. More broadly, the lab aims to apply aging research to pressing clinical problems.

Researchers and sources featured

Researchers and clinicians

• Dr. Jesse Poganik — Guest; studies biological age and aging biomarkers.
• Vadim Gladyshev — Poganik’s former postdoctoral mentor.
• Bohan Zhang — Colleague whose work on old mice in parabiosis was discussed.
• Stefan Tullius — Transplant surgeon and collaborator.
• Tomohisa — Performed mouse transplant surgeries; no surname given in the subtitles.
• Steve Horvath — Associated with the universal mammalian methylation clock used in the studies.
• Morgan Levine — Discussed the interpretability of “black box” biomarkers at the Biomarkers of Aging conference.
• Ludger Gummesson — Associated with organ-specific proteomic aging clocks and a follow-up analysis of reduced protein panels; name as rendered in the subtitles.

Studies, organizations, and sources

• Poganik and colleagues’ 2023 Cell Metabolism paper on biological age increasing under stress and returning toward baseline after recovery.
• Bohan Zhang’s parabiosis study of old mice and persistent biological-age changes.
• A Nature Communications paper on age-associated DNA-methylation changes in human blood.
• The Cell Metabolism article discussing evidence needed to claim biological rejuvenation.
• A preprint on biological age assimilation after heart transplantation.
• UK Biobank’s Nightingale metabolomics work and its Olink proteomics effort.
• ARPA-H’s PROSPER program.
• The Biomarkers of Aging Consortium and its survey-based work on clinical implementation of aging biomarkers.
• A review on pregnancy-related changes in biological age, described as forthcoming in the subtitles.