Abstract
Obesity is a global health concern, and it is thought to accelerate the normal ageing process. Obesity has also been linked to neurodegenerative processes, possibly as a manifestation of accelerated brain-ageing. In this cross-sectional study we combined multimodal neuroimaging data and machine learning techniques to assess the discrepancy between brain-based predicted age and chronological age, known as brain age delta, in obese participants and in normal-weighted individuals using a tight matching for age, gender and education across groups. Data were taken from the publicly available dataset 'The Cambridge Centre for Ageing and Neuroscience (Cam-CAN)' covering the adult lifespan (18-90 years old). Overall, brain age delta was greater in obese individuals for grey matter (GM) and functional connectivity (intra- and inter-network connectivity) measures. When considering the age-range, the difference between groups peaked in mid-age (40-60 years old) for GM, while for intra-network connectivity it was more marked in late age (60-90 years old). Overall, our results provide evidence to the hypothesis that obesity accelerates the brain ageing process, with the earliest effect already evident in the 40-60 age range. Earlier intervention on obesity might contribute to maintain a healthy brain potentially reducing the risk of developing late-life brain-related pathologies.