Brain Aging Linked to Metabolic Shifts, New Model Shows

A new computer model of brain metabolism, the most comprehensive of its kind, integrates more than 16,800 biochemical interactions across neurons, supporting glial cells and the bloodstream. This open-source model enables researchers to study how the brain's energy supply shifts with aging, potentially informing strategies to mitigate age-related neurological decline.

Developed by a team at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, the model offers insights into how brain metabolism deteriorates with age and highlights potential interventions. The findings were published in Frontiers in Science as part of the Blue Brain Project, a research initiative focused on simulating brain function.

A window into brain aging

The model, which combines data from human and rodent brains, simulates the complex interplay between neuronal activity, metabolic processes and blood flow. It allows researchers to track how molecular changes over time affect brain function.

To investigate how aging influences brain metabolism, the team mapped biochemical interactions in both young and aged brains, identifying vulnerabilities that arise with age. Their analysis revealed that small shifts in the concentration of certain molecules can trigger widespread disruptions across multiple metabolic pathways. As a result, aged brain cells may become less resilient to stress and damage.

“This study provides an x-ray view into the battery that powers the brain. We can now track how the energy system of the brain ages at the molecular level.”

Dr. Henry Markram.

The model also highlighted potential therapeutic targets. One promising intervention involves supplementing with nicotinamide adenine dinucleotide (NAD), a molecule essential for cellular energy production. Previous studies have explored NAD supplementation as a possible strategy for promoting healthy aging.

Identifying molecular targets for intervention

Beyond identifying broad metabolic changes, the model helped pinpoint specific proteins that may influence age-related declines in brain function. One key finding was the role of estrogen-related receptor alpha (ESRRA), a protein implicated in metabolic regulation. Its predicted decline with age suggests a potential avenue for drug development to support neuronal health.

The study’s findings reinforce the idea that brain aging is not driven by a single failing pathway but by the breakdown of multiple interconnected metabolic systems. This suggests that interventions targeting multiple processes may be necessary to preserve brain function in aging populations.

“While there are usually many steps between a computational model’s predictions and practical guidance for people, some of the suggestions of our model include already approved supplements, dietary changes or lifestyle habits.” 

Dr. Polina Shichkova.

A research tool for neuroscientists

The model was validated by comparing its predictions to experimental data from brain tissue. The high degree of accuracy in its simulations confirms its potential as a research tool for neuroscientists studying age-related conditions such as dementia.

The team has made the model publicly available on the Open Brain Platform, an initiative of the Open Brain Institute. By providing access to this computational tool, the researchers aim to support further investigations into the mechanisms underlying neurodegenerative diseases and facilitate the development of targeted interventions.

Looking ahead

While the model provides valuable insights into brain metabolism, further research is needed to test these findings in human subjects. The role of energy metabolism in neurological conditions remains an active area of study, and validating these computational predictions through experimental research will be essential.

Reference: Shichkova P, Coggan JS, Kanari L, et al. Breakdown and repair of metabolism in the aging brain. Front Sci. 2025;Volume 3-2025. doi: 10.3389/fsci.2025.1441297

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