We age because of certain genes

One of the main indicators of brain health is considered to be the difference between its biological age and the actual age of the person. If the brain is older than its owner, this can indicate an increased risk of neurodegenerative diseases, reduced cognitive function and poorer overall health.

The so-called “brain age gap” is particularly noticeable in people with Alzheimer’s disease, demyelination and schizophrenia. The larger the gap, the lower the scores on tests of memory, attention and thinking speed.

To find out what factors influence the biological age of the brain, the researchers used deep machine learning techniques. The 3D-ViT model analyzed MRI data, lifestyle, medical conditions and genetic information.

As a result, seven genes (MAPT, TNFSF12, GZMB, SIRPB1, GNLY, NMB, C1RL) were found to be directly linked to brain aging processes. They affect inflammatory processes, metabolism and the functioning of cells responsible for memory and thinking.

In addition, the scientists identified two key brain regions most susceptible to age-related changes: the lentiform nucleus, which is responsible for attention and working memory, and the posterior section of the internal capsule, which connects various brain structures to the cerebral cortex, where information processing, learning and decision-making take place.

Using data on genes and age-related brain changes, the researchers tested existing drugs that may affect this process. This resulted in a list of 13 drugs and supplements that can slow brain aging. These include hydrocortisone, testosterone, diclofenac and metformin.

Some of these drugs are already in clinical use, which means that their effects on the body have been studied. However, more trials are needed to confirm their effectiveness specifically against brain aging.

The study shows that genetic factors play an important role in the rate of brain aging, but their influence can be reduced. The next step will be to test the findings on a larger sample including different populations.

In the future, this could lead to the creation of personalized strategies for the prevention and treatment of age-related brain changes, which in turn could help preserve cognitive function for years to come.