study shows ai can tell how fast you're aging—and how to slow it down
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people may be able to use aging clocks to track their health as they age, enabling them to see where lifestyle changes may be necessary to reduce their risk of early mortality and disease.
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artificial intelligence (ai) is being used in all corners of medicine, and new insights into the technology may help fight accelerated aging.
a study conducted by researchers at king college’s institute of psychiatry, psychology, and neuroscience in london, england, assessed different ai algorithms and machine learning systems to determine whether they could accurately predict a person’s potential health declines in aging and lifespan based on their current state of health. as it turns out, they can.
the researchers hope to utilize the results of the study and the ai machine learning algorithms to help create preventative measures for those who are aging faster than they should be based on their chronological age.
the study
the study, “metabolomic age (mileage) predicts health and life span: a comparison of multiple machine learning algorithms,” was recently published in science advances. it looked at 17 machine learning algorithms to test markers in the participant’s blood to assess their current state of health and aging. over 225,000 participants were recruited into the study, aged 40 to 69.
the ai algorithms, aptly dubbed aging clocks, were designed to figure out a person’s mileage or metabolomic age using molecules generated during the metabolic process, such as those that occur during digestion. these biomarkers were then used to determine a person’s mileage versus how old they are in years.
the difference between the two numbers, referred to as the mileage delta, was used to determine if a person was metabolically older or younger than their chronological age, helping researchers identify who may be aging at an accelerated rate and more at risk for chronic diseases and mortality earlier in life.
the study was the first of its kind to compare all the different machine learning algorithms to come to a general result based on the capabilities of each one.
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the results
out of the 225,000 participants, those who were tested as being older than their actual age were found to have a higher likelihood of developing chronic illness or already having a chronic disease. they also had a higher risk of early mortality, as well as were in worsened health or “frailer” than those in the group that was found to be of a similar age or lower age metabolically.
these individuals were put into the accelerated aging category. they were also found to have markers that indicated a higher incidence of increased cellular aging and increased risk for age-related diseases.
good health was apparent for those in the decelerated aging group or those who were found to be the same age or younger metabolically. still, the link was not as strong in this group as it was in those who fell into the accelerated aging group. thus, while aging clocks can be used to decrease accelerated aging through early detection and intervention methods, they cannot reverse aging in those who are doing so at a typical rate.
what these systems can do for the general population
the researchers hope that these aging clocks can be used in a widespread way to help identify different health markers that indicate how fast a person is aging.
in turn, they can practice early intervention in people who may be at a higher risk of age-related disease and shortened lifespans by providing them with the tools and information they need to make any necessary changes in their health trajectory, such as getting on new medications or engaging in preventative therapies, as reflected by their results to prevent further health degeneration.
people may also be able to use aging clocks to track their health as they age, enabling them to see where lifestyle changes may be necessary to reduce their risk of early mortality and disease.
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“metabolomic aging clocks have the potential to provide insights into who might be at greater risk of developing health problems later in life,” said dr. julian mutz, lead author of the study, in an article in sci tech daily. “unlike chronological age, which cannot be changed, our biological age is potentially modifiable. these clocks provide a proxy measure of biological age for biomedical and health research, which could help shape lifestyle choices taken by individuals and inform preventative strategies implemented by health services.”
while these aging clock tests may not be the discovery of the fountain of youth, they can come in incredibly handy when you’re aging a little faster than you should be.
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