Biomarkers could monitor brain aging, revealing ways to treat dementia and other age-related brain disorders.
Researchers have identified 13 proteins in the blood that predict how quickly or slowly a person’s brain ages compared to the rest of the body.
The study, published in Nature Aging on December 9, used a machine learning model to estimate brain ages from scans of more than 10,000 people. The authors then analyzed thousands of scans along with blood samples and found eight proteins that were associated with rapid brain aging, and five linked to slower brain aging.
“Previous studies have mainly focused on the association between proteins and chronological age, that is, the actual age of the individual,” says study co-author Wei-Shi Liu, a neurologist at Fudan University in Shanghai, China.
However, studying biomarkers linked to a person’s brain age could help scientists identify molecules to target in future treatments for age-related brain diseases. “All of these proteins are promising therapeutic targets for brain disorders, but it may take a long time to validate them,” Liu says.
Brain Age Difference
Using machine learning to analyze brain imaging data from 10,949 people, Liu and his colleagues created a model to calculate a person’s brain age, based on features such as brain volume, surface area and white matter distribution.
They wanted to identify proteins that are associated with a large brain age gap—the difference between brain age and chronological age. To do this, the researchers analyzed levels of 2,922 proteins in blood samples from 4,696 people, more than half of whom were women, and compared them with the same people’s brain ages derived from the scans. They identified 13 proteins that appeared to be linked to large brain age gaps, some of which are known to be involved in movement, cognition, and mental health.
