A equipment led by the Barcelonaβeta Brain Research Center (BBRC), a research center of the Pasqual Maragall Foundation, has developed through artificial intelligence a new biomarker associated with the alzheimer indicating accelerated brain aging.
The chronological age (the time elapsed since birth) and biological brain age may not coincide, and the latter parameter can be calculated from techniques neuroimaging to determine if the brain has aged more rapidly than expected.
Certain morphological characteristics, such as altered thickness or volume in specific regions of the brainact as biomarkers, that is, they are objective measurements that provide information about this ageing.
For this one studythe researchers have used a machine learning model, using artificial intelligence, to analyze these parameters from 22,600 MRI imagessourced from the UK Biobank, a large-scale biomedical database containing health and genetic information on half a million UK participants.
Thanks to this analysis of images, the researchers have been able to validate a new biomarker that has made it possible to demonstrate, for the first time, that the presence of pathological alterations Alzheimer’s disease is associated with accelerated brain aging, even in cognitively healthy people.
The results of the study, supported by the “la Caixa” Foundation and published in the scientific journal Elife, help to better understand the relationship between the brain aging process and neurodegenerative diseases.
Although age is the main risk factor for Alzheimer disease and most neurodegenerative diseases, the biological mechanisms that explain this association are still poorly understood”, explained Irene Cumplido, predoctoral researcher in the BBRC Neuroimaging Research Group and first author of the paper.
“For the study of age, it is necessary to have objective markers of biological brain aging, beyond chronological age, just as biomarkers are available for Alzheimer’s,” he pointed out.
The new biomarker for accelerated brain aging joins other indicators of the disease and already known risk factors, such as the presence of beta amyloid and tau proteins or the APOE-ε4 genotype).