A decline in measured biological age after treatment needs to be assessed alongside health improvements, says aging researcher Jesse Poganik
A decline in measured biological age after treatment needs to be assessed alongside health improvements, says aging researcher Jesse Poganik
In a conversation with biologist Eleanor Sheekey published on 30 October, Poganik of Harvard Medical School discusses two uses of biological age tests: predicting disease and evaluating treatment. He also suggests tracking how long a change in the measurement lasts after an intervention ends.
Epigenetic clocks estimate age from chemical marks on DNA. Poganik recalls that he initially wanted to find out how quickly their readings respond to drugs. After a week of treatment in mice, the readings were unchanged, so the team turned to interventions that place substantial stress on the body.
The researchers joined the circulatory systems of a young and an old mouse, then separated the animals and allowed them to recover; this experiment is described in a 2023 paper. As a comparison, they joined two young mice to distinguish the effects of the partner’s age from those of the procedure itself. They subtracted the young mice’s chronological age from the age estimated by the clocks for their tissues. This difference increased after exposure to an old partner and returned to baseline after separation and recovery.
Sheekey asks how long a reduction in measured biological age will last after an intervention ends. One of Poganik’s criteria for biological age reversal is “persistence of the effect after the intervention ends.” Under the definition he and his colleagues proposed, the estimate must fall below baseline and remain below it after the intervention stops. The same features are used to calculate the estimate before and after the intervention. Repeated measurements allow researchers to assess the size and duration of the reduction.
A biomarker is a measurable indicator of the body’s condition. To test whether it predicts disease risk, researchers compare baseline readings with subsequent disease and a person’s ability to live independently. These predictions can help identify people for screening or participation in a trial. A paper from the Biomarkers of Aging Consortium, coauthored by Poganik, makes the following argument:
“Useful biomarkers can be developed without a detailed understanding of causal relationships.”
Using a change in a biomarker to assess a treatment’s benefit requires a separate test of whether the drug-induced change predicts an improvement in health.
Poganik is interested in the possibility of measuring a defined set of blood proteins using the same method. This makes it easier to combine data from different studies and validate tests based on those data in new groups of people. Proteins characteristic of the heart, liver or other organs can be used to calculate separate age estimates for those organs. A single sample of plasma, the liquid component of blood, can yield several such estimates, which can then be compared with disease and organ function.
In his laboratory, Poganik studies drugs that are already being prescribed. Disease itself can raise biological age estimates, and treating it can lower them. He wants to determine how much of the reduction reflects recovery from disease and how much reflects the drug’s effects on aging processes.