University of Coimbra (Portugal) - Press Release: Study shows how Alzheimer’s disease, type 2 diabetes, and schizophrenia cause the brain to age faster than expected.

A research team from the University of Coimbra (UC) has demonstrated the impact that certain chronic diseases associated with cognitive decline—such as Alzheimer’s disease, type 2 diabetes, and schizophrenia—can have on brain aging. Using artificial intelligence techniques and various local and global databases, it was possible to differentiate biological age from chronological age, representing a new way to measure the impact of these chronic diseases that—either directly or indirectly—affect the brain. In cases of Alzheimer’s disease, brain aging can exceed the patient’s actual age by more than 9 years.

The study—recently published in the journal Brain Communications and led by first author Maria Fátima Dias, a researcher at the Centre for Biomedical Imaging and Translational Research (CIBIT) of the Institute for Nuclear Sciences Applied to Health at UC (ICNAS), and the Centre for Informatics and Systems of the University of Coimbra (CISUC), under the supervision of professors and researchers Miguel Castelo-Branco (Director of CIBIT and professor at the Faculty of Medicine of UC) and Paulo de Carvalho (Director of the Clinical Informatics Laboratory at CISUC and professor at the Faculty of Science and Technology of UC)—is based on the new concept of brain age gap estimation, the difference between a person’s chronological age and their estimated brain age (determined through AI models that analyzed brain MRI scans), to show the impact of certain diseases on brain aging.

“Estimated brain age is the brain’s ‘biological age,’ predicted by models that analyze brain images. Comparing it with chronological age (a person’s actual age, measured in years) allows us to determine whether the brain has aged faster or slower than expected. A positive brain age gap indicates accelerated brain aging, while a negative value suggests a biologically younger brain with delayed aging,” explains Miguel Castelo-Branco, senior author of the article.

In the study, using various artificial intelligence models, maps were generated to interpret which brain regions contributed most to calculating biological age. Metrics were also established to determine the average impact of each disease studied (all three are associated with or are risk factors for cognitive decline) on brain aging. “In the case of schizophrenia, brain aging is approximately 2 years; in type 2 diabetes, it’s 5 years; and in Alzheimer’s disease, it reaches 9 years,” says the researcher and Director of CIBIT.

These findings could open new avenues for diagnosing cognitive decline associated with these conditions. “In practice, this measure could be used as a useful biomarker for the early diagnosis of neurodegenerative diseases,” concludes Miguel Castelo-Branco.

The study involved researchers from the Faculty of Medicine of UC, the Centre for Biomedical Imaging and Translational Research, the Institute for Nuclear Sciences Applied to Health, the Centre for Informatics and Systems of UC, and the Associated Laboratory for Intelligent Systems.

The article—authored by Maria Fátima Dias, João Valente Duarte, Paulo de Carvalho, and Miguel Castelo-Branco—is available at: https://academic.oup.com/braincomms/article/7/2/fcaf109/8069058.