Until recently, scientists estimated biological age with so-called epigenetic clocks which are DNA-based tools that produce a single number for how fast someone is aging.
But our organs don’t all age at the same pace. A new system, called Systems Age, offers a far more detailed picture.
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Developed by an international research team that includes Morgan Levine, the model, published in Nature Aging, uses blood biomarkers, clinical data, and machine learning to estimate the biological age of 11 organs and systems, such as the heart, lungs, liver, kidneys, brain, and hormonal system.
According to Morgan Levine, this organ-specific approach can help identify which age-related diseases a person is most at risk of developing.
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The model
To build the model, scientists analyzed health data from more than 15,000 participants in long-term projects such as the Health and Retirement Study and the Framingham Heart Study.
By training artificial intelligence on thousands of blood samples, they identified DNA patterns linked to the decline of specific organs.
When the model was tested on an additional 8,000 people, the results were striking: the heart’s “aging score” turned out to be the best predictor of cardiovascular disease yet discovered.
The brain’s score correlated with cognitive decline, while the musculoskeletal system’s results were tied to conditions such as arthritis and loss of strength.
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Aging isn’t the same for everyone
One of the most revealing insights from the study is that two people of the same chronological age can have vastly different biological profiles.
A 60-year-old, for example, might have an immune system that looks 45 or 75.
This difference could help explain why some seemingly young people experience diseases like heart attacks or early-onset dementia.
A new direction for preventive medicine
The goal of Systems Age isn’t diagnosis, but prevention.
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If a patient’s immune system appears to be aging faster than other systems, doctors could recommend personalized strategies, such as targeted exercise, diet changes, medication, or vaccines, to slow down that specific decline.
The researchers also believe the test could be used to evaluate the effects of anti-aging treatments, nutritional interventions, and tailored fitness programs.
Sources: ElConfidencial, and Nature Aging.
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This article is made and published by Ida-Marie Palm Varbæk, who may have used AI in the preparation.