AI predicts brain aging associated with Alzheimer’s

Spanish scientists develop a biomarker of brain aging, validated with artificial intelligence, and find associations between accelerated aging of the brain and risk factors for Alzheimer’s.

AI predicts brain aging associated with Alzheimer’s

A new AI-validated biomarker of brain aging has shown for the first time that pathological changes in the brain characteristic of Alzheimer’s disease are associated with accelerated brain aging, even in people with normal cognition. The biomarker has been developed by scientists from the Barcelonaβeta Brain Research Center (BBRC), a research center of the Pasqual Maragall Foundation.

Researchers used machine learning techniques to analyze 22,661 MRI images from the UK Biobank – a large biomedical database containing health and genetic information on half a million people in the UK – and compare them with Alzheimer’s biomarkers for 2,300 people. of four independent cohorts, including cognitively healthy individuals included in the ALFA Study, promoted by the ”la Caixa” Foundation.

Biomarkers provide information about a disease or a biological process, and certain morphological characteristics, such as an alteration in thickness or volume in specific areas of the brain, may indicate accelerated aging of this organ. The results of the study have been published in eLife and help to better understand the relationship between the brain aging process and neurodegenerative diseases, something essential to develop strategies to prevent or delay these pathologies that are increasing due to the aging of the population.

Difference Between Chronological and Biological Brain Age

This study is the first that has demonstrated the association between brain biological age and the presence of biomarkers and risk factors for Alzheimer’s (such as beta amyloid and tau proteins or the APOE-ε4 genotype) in 2,314 cognitively healthy or cognitively impaired people. mild. The results also show the relationship between brain aging and markers of neurodegeneration and cerebrovascular pathology and position this new indicator as a potentially useful tool in the diagnosis of various brain diseases.

The study has shown the association between brain biological age and the presence of biomarkers and risk factors for Alzheimer’s, such as beta amyloid and tau proteins or the APOE-ε4 genotype.

Knowing the difference between chronological age –which is the time that has elapsed since birth– and the biological age of the brain –which is calculated using neuroimaging techniques– allows us to estimate whether brain aging has occurred more fast than expected. This is known as the brain-age delta, and is considered an indicator of biological brain aging. Thus, people with an estimated brain age higher than their chronological age might have an “older” brain than expected, whereas a person whose brain age is estimated to be less than their chronological age would have a “older” brain than expected. younger”.

“Although age is the main risk factor for Alzheimer’s disease and most neurodegenerative diseases, the biological mechanisms that explain this association are still poorly understood,” explains Irene Cumplido, predoctoral researcher in the Neuroimaging Research Group of the BBRC and first author of the work. “For the study of age, it is necessary to have objective markers of biological brain aging, beyond chronological age, in the same way that biomarkers are available for Alzheimer’s,” she specifies.

Studying Alzheimer’s using artificial intelligence

To carry out the study, the researchers trained a predictive model to calculate the brain age of healthy men and women, using more than 22,000 measurements that had been obtained from magnetic resonance imaging. This is the first time that the BBRC has used machine learning techniques to study brain aging. “These models learn the association between chronological age and brain morphological characteristics extracted from magnetic resonance imaging, which predicts a brain age for each individual,” explains Dr. Verónica Vilaplana, associate professor in the Department of Signal Theory and Communications of the Polytechnic University of Catalonia and also author of the study.

“A growing amount of research in the last two years has focused on the use of neuroimaging techniques to develop a marker of biological brain aging,” says Dr. Juan Domingo Gispert, head of the BBRC Neuroimaging Research Group. “Unlike previous studies, the new biomarker that we have developed is validated against several biological markers and risk factors associated with aging, so our study demonstrates the validity of our method as a biomarker of brain biological aging with relevance for various diseases. neurodegenerative”.

“We know that accelerated aging of the brain has been found in neurodegenerative disorders such as Alzheimer’s disease, but it was necessary to compare these data with specific biological markers of the disease,” says Cumplido. To this end, researchers have studied the associations of accelerated brain aging with various biomarkers and risk factors for Alzheimer’s in healthy people, such as the presence of beta amyloid and tau proteins, the APOE-ε4 genotype – the main genetic risk factor for Alzheimer’s disease – and other markers of neurodegeneration and cerebrovascular disease. They also performed a gender-stratified analysis to study differences between men and women with respect to brain age.

The estimate of accelerated brain aging was associated with abnormal beta-amyloid deposits, Alzheimer’s disease in more advanced stages, and the presence of the APOE-e4 genotype; some results especially useful for potential strategies that help prevent neurodegenerative pathologies.

Source: Barcelonaβeta Brain Research Center (BBRC)


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