Which areas of the brain age faster? The first genetic map of brain aging, made by a Romanian researcher from the USA

The brain does not age uniformly. Some areas deteriorate faster than others, and the pace of this decline is largely written in our DNA. Until now, scientists measured brain age by a single global number, with no mention of regional differences.

A research recently published in the journal GeroScience, coordinated by Nicholas J. Kim and Romanian researcher Andrei Irimia, biogerontologist and neurobiologist at the University of Southern California, USA, has led to the first detailed genetic map of local cortical aging, demonstrating that certain areas can age faster than others, and this difference is related, in part, to the genetic profile of each person.

The brain regions that show the strongest genetic associations with accelerated aging overlap with areas known to be first affected in Alzheimer's or other forms of dementia.

Dementia is not an inevitable consequence of aging

According to estimates published in The Lancet Public Health, by 2050 there will be around 153 million cases of dementia worldwide. In Europe, more than 9 million people in the EU27 states are currently living with dementia, and by 2050 the figure will increase by 58%, according to the January 2026 Alzheimer Europe report. Women are disproportionately affected: of the approximately 12.1 million people with dementia across Europe (EU and non-EU states), more than 8 million are women.

In Romania, approximately 288,000 people are diagnosed with dementia (1.53% of the total population), and by 2050 their number could reach almost 400,000 (2.47%), according to the same report.

In short, dementia is not an inevitable consequence of aging. The risk increases, but the evolution is not the same for everyone. Data from the study published in GeroScience show that genetic factors can influence the rate at which the brain ages, including the difference between a slow and an accelerated process.

From a general score to a detailed map

For years, researchers worked with only one estimate: brain age. Based on an MRI, they assessed how old the brain as a whole looks relative to its actual age. A 40-year-old adult could have a brain that looks like a 50-year-old, a sign associated with a greater risk of cognitive decline. The problem is that this average says nothing about the differences between areas.

“We treated brain age as a single note, almost as an overall average of the whole brain,” explained Nicholas Kim, lead author of the study. His team proposed that instead of a single score, they would analyze 148 regions of the cortex separately. For each area, they calculated how quickly or how slowly it ages, using an artificial intelligence model trained on MRI images.

The analysis is based on data from 41,708 adults without cognitive problems included in the UK Biobank, a UK database. For each participant, the estimated age of each region was compared to the actual age. The difference thus obtained was then correlated with hundreds of thousands of genetic variants.

Polygenic architecture: 1,212 genetic variants

The analysis identified 1,212 genetic variants associated with accelerated or delayed aging in at least one cortical region. These variants do not appear in isolation, but tend to cluster in common patterns related to different biological processes. Using statistical clustering methods, the researchers separated these variants into three categories, each with specific effects on certain areas of the brain.

The first group (106 variants) comprises genes involved in ion transport, vascular signaling and cell metabolism, including KCNK2, BMP6 and RHEB. These variants are associated with an accelerated aging of the cortex, especially in the area of ​​the precuneus, posterior cingulate and superior frontal regions, i.e. exactly in the core of the brain's “default mode network”, one of the first to be affected in Alzheimer's disease.

The second group (all 106 variants) includes genes such as NUAK1, LPAR1 and ROCK1, involved in cytoskeleton stability, lipid signaling and cellular stress response. Unlike the first group, these variants are associated with a protective effect: limbic and paralimbic areas (insula, cingulate, medial temporal regions) show signs of slower aging in carriers of these alleles.

These areas, responsible for emotional processing and interoception, are the first to degrade in frontotemporal dementia.

The third, smaller group (only 6 variants) involves genes related to chromatin remodeling and immune regulation, such as histones H1-1 and H4C8 or the BTN3A2 gene. Their effect is concentrated in the frontoinsular and perisylvian cortex, areas that integrate sensory, cognitive and affective information.

Genes that accelerate aging and genes that protect the brain

Of all the variants analyzed, some of the most important links to accelerated aging appear around the KCNK2 gene. It is involved in the functioning of neurons, and certain variants are associated with a cortex that appears older, especially in areas known to be vulnerable in Alzheimer's disease.

Previous research has shown that this gene influences the electrical balance of nerve cells. When it does not function normally, disturbances can occur that favor the progressive degradation of the brain.

At the opposite pole is the NUAK1 gene. Some variants of it are associated with a slower rate of cortical aging in several regions. It is an attention-grabbing result, especially since NUAK1 is already being studied as a possible target in treatments for neurodegenerative diseases.

Other genes of interest include GMNC (involved in cell cycle regulation and DNA replication), MSL2 (chromatin remodeling and histone acetylation), KANSL1 (a risk locus already known for Alzheimer's, Parkinson's and amyotrophic lateral sclerosis), and two members of the WNT family (WNT3 and WNT16) that control early neuronal formation and neuroplasticity.

“Brain aging does not depend on a single genetic factor, but on a set of genetic variants”

The study shows that the aging of the cortex cannot be attributed to a single gene. It is the result of an accumulation of genetic variants acting in different directions. Some are associated with a faster rate of degradation, others seem to slow down this process, and their effects differ from one region to another.

“What I find important about this research is that it shows that brain aging does not depend on a single genetic factor, but on a set of genes, which act differently from one region to another. By combining measurements of aging at the local level with genetic analysis, we can better understand how genetic inheritance influences the vulnerability of certain areas of the brain. This helps us understand more clearly why some regions are affected earlier in Alzheimer's disease,” said Romanian researcher Andrei Andrei Irimia, USC professor and project coordinator, quoted by the Medical Express publication.

Basically, the study redefines brain aging, showing that it is not random atrophy or haphazard functional loss, but the unfolding of genetically encoded, partially predictable trajectories that begin in embryonic development and continue throughout life.

Identifying people at risk before symptoms appear

The estimated age of different brain areas could be used as an indicator in studies of neurodegenerative diseases in the future. For example, people in whom certain regions appear more aged may be at greater risk of Alzheimer's disease, while others with a more favorable genetic profile may respond differently to treatment.

Some of the mechanisms identified in the study are already analyzed in medical research, including those related to neuron development, cell structure or metabolic processes. That means the results could be used both to estimate risk and to track how different areas of the brain respond to treatments.

In the longer term, this data could help identify people at increased risk long before symptoms appear. However, the results need to be confirmed in larger studies and on more diverse groups. If these steps are taken, the research could change the way neurodegenerative diseases are prevented and monitored.

However, it is important to note that the study design does not allow tracking how local brain age changes over time in the same person. The analyzed cohort comes predominantly from the population of European origin, and the results may not apply to the same extent to other populations.