Scientists claim a single MRI scan can reveal a person’s biological age, providing a more accurate measure of aging than a person’s chronological age.
The study findings were published in the journal Nature Aging. The teams say that the tool can predict an individual’s increased risk of cognitive impairment, and chronic conditions like heart diseases, and early deaths.
Ahmad Hariri, a professor of psychology and neuroscience at Duke University, and his colleagues used data from the Dunedin study which is one of the world’s most comprehensive and longest-running longitudinal studies.
The study has followed 1,037 people from Dunedin, New Zealand, from birth to middle age. These participants were born in 1972 and 1973 and received 19 assessments to check the function of their heart, brain, kidneys and more.
The team analyzed their brain MRIs taken from this cohort at the age 45 and then ran the data about brain structure through a machine learning algorithm.
The results were further analyzed in relation to data from the participants, such as tests of physical and cognitive decline and signs of facial aging like wrinkles.
They asserted that bigger declines in physical and cognitive health are linked to a faster pace of aging and then correlated features of the brain to those metrics.
Their resulting model was called “Dunedin Pace of Aging calculated from Neuroimaging.”
The Dunedin Pace has been widely adopted by various studies, and it allows research without epigenetic data but with brain MRI to measure accelerated aging.
To analyze their new tool, the team used MRIs from other datasets to estimate the pace of aging.
It includes 42,000 MRIs from the U.K.; over 1700 MRIs from the Alzheimer’s Disease Neuroimaging Initiative (ADNI); and 369 from the BrainLat set, which includes from five South American countries.
Hariri believes that DunedinPACNI retains the properties to be widely adopted because the types of MRIs it uses are routinely collected.
It has the potential to determine standards of what reflects healthy and poor aging.
The DunedinPACNI model, which measures biological aging could eventually be used to provide a more personalized approach to healthcare, helping to prepare individual patients for age-related health issues.
The study findings will highlight the importance of studying aging, particularly in healthy people.