Measuring Aging with Brain Scans
Photo: Ethan Whitman/Duke University
Many past attempts to measure biological age relied on biomarkers that capture various aspects of a person’s health. A chemical change to DNA called methylation is now the most widely used method for measuring differences in aging.
In a new study, researchers at Duke University developed a tool to measure aging based on a single brain scan. Their findings were reported in Nature Aging.
The researchers built their new tool on the foundations of their previous breakthroughs. Using data from the Dunedin study, they first developed a method to measure biological aging called the Pace of Aging, which measures the decline in function over time of 19 health-related biomarkers. Next, they found a way to correlate DNA methylation patterns at a single time point with the Pace of Aging measure. They called this measure DunedinPACE. However, it depends on having DNA methylation data, which many neuroscience aging studies do not collect. In their new study, the researchers aimed to capture aging rates from brain images instead.
The team used MRI scans collected from participants in the Dunedin study. They used those images and their earlier data on declining function over time to develop a model for measuring aging rates from brain scans alone. They call their new measure, which uses 315 structural measures in the brain scans, Dunedin Pace of Aging Calculated from Neuroimaging (DunedinPACNI).
DunedinPACNI predicted aging rates with similar accuracy to past tests of DNA methylation. Higher DunedinPACNI scores were associated with declining physical and cognitive function as well as facial aging.
The tool can also measure aging rates in other groups of people. DunedinPACNI accurately predicted cognitive impairment, faster brain atrophy and dementia. Higher DunedinPACNI scores also predicted physical frailty, poor health, future diseases and mortality.
While more study is needed before the test could be used in the clinic, it could ultimately help to identify those at greater disease risk to allow for increased monitoring and earlier interventions.