Barcelona AI Detects Aging in Blood Cells With 68% Accuracy

Imagine if doctors could see exactly how your cells are aging and then reverse the damage. Scientists in Barcelona just brought that future closer to reality.

A team at the Bellvitge Biomedical Research Institute developed ChromAgeNet, an artificial intelligence tool that detects aging in blood stem cells by studying the 3D structure of DNA. Published in the journal Aging Cell, the research shows that AI can spot the difference between young and old cells with 68% accuracy using only low-cost imaging techniques.

The discovery centers on chromatin, the way DNA organizes itself inside cell nuclei. In young cells, chromatin stays tightly packed at the edges of the nucleus. As cells age, that neat architecture falls apart and becomes scattered.

Dr. Maria Carolina Florian, who led the research, explains the challenge they tackled. "Analyzing changes in blood stem cells is crucial to opening the door to interventions that can slow their decline and restore their original function," she tells Euronews.

What makes ChromAgeNet special is that it shows its work. Unlike typical AI black boxes, this tool reveals which features it uses to make decisions. Researchers can see exactly what structural changes the AI identifies as signs of aging.

The team trained the tool using 3D images of mouse stem cells and convolutional neural networks. The AI learned to detect subtle structural variations that human eyes simply cannot see.

The Ripple Effect

The Barcelona team has already tested ChromAgeNet on aged cells treated with epigenetic drugs. The tool successfully identified which treatments pushed cells toward more youthful patterns, suggesting a practical path for screening new therapies.

The implications stretch far beyond individual cells. Blood stem cells produce all our blood cells and play a fundamental role in immune system function. Rejuvenating these cells could strengthen immunity and improve quality of life as we age.

Dr. Paula Petrone from the Barcelona Supercomputing Center emphasizes the accessibility angle. "A deep-learning algorithm can tell apart young and aged stem cells by analyzing images of cell nuclei stained with a low-cost substance called DAPI," she says.

The team made their code and image database publicly available to accelerate research worldwide. They're now working to adapt the tool for human stem cells and seeking EU funding to expand the work.

Previous research from Florian's lab demonstrated that stimulating aged blood stem cells can improve not only immune function but also life expectancy and overall health. ChromAgeNet provides a new way to identify which interventions actually work.

The scientists are actively looking for collaborators across Europe interested in practical applications, turning what started as a proof of concept into a tool that could reshape how we approach aging and immunity.