The pace at which the brain ages can vary significantly among individuals, leading to a gap between the estimated biological age of the brain and the chronological age (the actual number of years a person has lived). This gap may be influenced by various factors, including physical (e.g.
pollution) and social (e.g. socioeconomic or health inequalities ) exposomes, especially in aging and dementia.
Until now, it was unclear how these combined factors could either accelerate or delay brain aging across diverse geographical populations. Now, in a trailblazing study published in Nature Medicine , researchers at the Global Brain Health Institute at Trinity College Dublin led a wider team of international colleagues to develop innovative measures of brain aging using advanced brain clocks based on deep learning of brain networks. This study involved a diverse dataset of 5,306 participants from 15 countries, including participants from the US, Latin America (LAC), Europe, and Asia.
Data from Ireland was integrated with other EU countries for the study. By analyzing data from functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), the researchers quantified brain age gaps in healthy individuals and those with neurodegenerative conditions such as mild cognitive impairment (MCI), Alzheimer's disease, and frontotemporal lobe degeneration (FTLD). The study revealed that populations from countries with greater inequalities generally exhibited older brain ages.
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