A team led by the Barcelonaβeta Brain Research Center (BBRC), a research center of the Pasqual Maragall Foundation, has developed a new biomarker of brain aging based on more than 22,600 magnetic resonance images. This new biomarker has made it possible to demonstrate, for the first time, that The presence of pathological alterations in Alzheimer's disease is associated with accelerated brain aging, even in cognitively healthy people.
The results of the study, which has the impulse of The “la Caixa” Foundation, help to better understand the relationship between the brain aging process and neurodegenerative diseases, an urgent priority to develop effective strategies to address the increasing aging of the population.
Biomarkers are objective measurements that provide information about a disease or biological process. In the case of brain aging, certain morphological characteristics, such as altered thickness or volume in specific brain regions, may indicate accelerated aging. Researchers have used a machine learning model to analyze these parameters from magnetic resonance imaging.
This study is the first to demonstrate the association between biological brain age and the presence of biomarkers and risk factors for Alzheimer's (such as the presence of beta amyloid and tau proteins or the APOE-ε4 genotype) in a total of 2,314 cognitively healthy people or those with mild cognitive impairment. The study also shows the relationship between brain aging and markers of neurodegeneration and cerebrovascular pathology. The findings, published in the scientific journal Elife, position this new indicator as a potentially useful tool in the diagnosis of various brain diseases.
Artificial intelligence: a pioneering methodology for studying Alzheimer's
The difference between chronological age (the time elapsed since birth) and biological brain age (calculated from neuroimaging techniques) provides an estimate of whether the brain has aged more rapidly than expected. This is known as the brain age delta (translation of brain age delta, in English), and is an indicator of biological brain aging. Individuals who have an estimated brain age higher than their chronological age may have an “older” brain than expected, while an individual with an estimated brain age lower than their chronological age would have a “younger” brain.
“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 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, in the same way that biomarkers are available for Alzheimer's disease." he points out.
In this work, the research team has trained a predictive model to estimate the brain age of healthy men and women, using more than 22,000 measurements obtained from magnetic resonance imaging. These images have been obtained from the UK Biobank, a large-scale biomedical database containing genetic and health information from half a million participants in the United Kingdom.
This is the first time that the BBRC has applied machine learning techniques to the study of brain ageing, a methodology that has recently gained popularity thanks to its ability to identify relevant patterns from complex data. “These models learn the association between chronological age and brain morphological features extracted from magnetic resonance images, which predicts a brain age for each individual.”, explains the Dr Verónica Vilaplana, associate professor at the Department of Signal Theory and Communications at the Polytechnic University of Catalonia and also author of the study.
“A growing amount of research over the past two years focuses on using neuroimaging techniques to develop a marker of biological brain aging.”, he says Dr. Juan Domingo Gispert, head of the Neuroimaging Research Group at the BBRC. “Unlike previous studies, the new biomarker 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 to various neurodegenerative diseases.”
The largest cohort to date to predict brain age
The study used a total of 22,661 measurements from images in the UK Biobank dataset to predict the brain age of more than 2,300 healthy individuals or those with mild cognitive impairment from four independent cohorts: ALFA+, supported by the “la Caixa” Foundation (380 individuals), ADNI (719 individuals), EPAD (808) and OASIS (407).
“We know that accelerated brain aging has been found in neurodegenerative disorders such as Alzheimer's disease, but it was necessary to compare these data with biological markers specific to the disease.”, Cumplido says. To this end, the researchers studied the associations between accelerated brain aging and various biomarkers and risk factors for Alzheimer's in healthy individuals, 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. In addition, a sex-stratified analysis was introduced in order to study the differences between men and women with respect to brain age.
The estimate of accelerated brain aging was associated with abnormal beta amyloid deposits, more advanced stages of Alzheimer's pathology, and the presence of the APOE-e4 genotype; results particularly useful for potential prevention interventions.
