Researchers have identified 13 proteins in the blood that predict how quickly or slowly a person’s brain ages compared with the rest of their body.
Their study, published in Nature Aging on 9 DEC 2024, used a machine-learning model to estimate ‘brain ages’ from scans of more than 10,000 people. The authors then analyzed thousands of scans alongside blood samples and found eight (8) proteins that were associated with fast brain ageing, and five (5) linked to slower brain ageing. “Previous studies mainly focused on the association between the proteins and the chronological age, that means the real 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 to identify molecules to target in future treatments for age-related brain diseases. “These proteins are all promising therapeutic targets for brain disorders, but it may take a long time to validate them,” says Liu.
Brain age gap
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, on the basis of features such as the brain’s volume, surface area and distribution of white matter.
ABSTRACT: Plasma proteomics identify biomarkers and undulating changes of brain aging
Proteomics enables the characterization of brain aging biomarkers and discernment of changes during brain aging. We leveraged multimodal brain imaging data from 10,949 healthy adults to estimate brain age gap (BAG), an indicator of brain aging. Proteome-wide association analysis across 4,696 participants of 2,922 proteins identified 13 significantly associated with BAG, implicating stress, regeneration and inflammation. Brevican (BCAN) (β = −0.838, P = 2.63 × 10−10) and growth differentiation factor 15 (β = 0.825, P = 3.48 × 10−11) showed the most significant, and multiple, associations with dementia, stroke and movement functions. Dysregulation of BCAN affected multiple cortical and subcortical structures. Mendelian randomization supported the causal association between BCAN and BAG. We revealed undulating changes in the plasma proteome across brain aging, and profiled brain age-related change peaks at 57, 70 and 78 years, implicating distinct biological pathways during brain aging. Our findings revealed the plasma proteomic landscape of brain aging and pinpointed biomarkers for brain disorders.
REFERENCE: Nature; 09 DEC 2024; Miryam Naddaf