Researchers have made a significant breakthrough in understanding brain aging, identifying seven genes responsible for fast biological brain aging and 13 existing drugs that can target those genes. The study, published in Science Advances, used deep learning models to analyze MRI data from nearly 39,000 UK Biobank participants and pinpoint specific gene targets.
Slowing down brain aging is a powerful strategy to prevent many diseases and enhance longevity. Previous research has shown that delaying aging by even 2% could result in significant healthcare savings. Brain aging pattern significantly impacts overall human aging, contributing to the rise in neurodegeneration and decline in physical and cognitive health.
A key parameter in brain health research is the brain age gap (BAG), which measures how old a person’s brain appears compared to their actual age. A larger BAG is often seen in individuals with brain disorders like Alzheimer’s and schizophrenia, and is linked to lower cognitive test scores.
To understand the factors driving brain aging, researchers turned to genes, which are known to play a crucial role in shaping how the brain ages. The study used deep learning models trained on MRI scans, lifestyle data, health records, and genetic information from UK Biobank participants to identify specific gene targets.
The findings revealed that seven genes (MAPT, TNFSF12, GZMB, SIRPB1, GNLY, NMB, and C1RL) were promising targets for brain aging. The researchers also used a technique called saliency map analysis to identify the critical brain regions linked to aging, including the lentiform nucleus and posterior limb of the internal capsule.
By combining insights on specific gene targets, brain regions linked to aging, and existing clinical trial data, the researchers identified 13 drugs and supplements that can be repurposed to slow down brain aging. These include hydrocortisone, testosterone, diclofenac, and metformin. While the results are promising, more research is needed across diverse populations to evaluate the true extent of these findings.
Source: https://medicalxpress.com/news/2025-03-deep-uncovers-gene-potential-drugs.html