AbstractBackgroundLife‐course exposure to risk and protective factors impacts brain macro‐ and micro‐structure, which in turn affects cognition. Brain Age Gap (BAG) directly measures brain reserve by comparing an individual’s neuroimaging‐based predicted age with their calendar age. Higher BAG implies accelerated brain aging and lower brain reserve. In this study, we comprehensively modeled mutual associations between brain risk and protective factors, reserve, and cognition in a large, middle‐aged population using structural equation modelling (SEM).MethodsCognitive test scores, lifestyle, and 3T MRI data for n = 4881 participants (mean age(±SD) = 59.2(±8.6), 50.1% male) were available from The Maastricht Study, a population‐based cohort study with extensive phenotyping. Whole brain volumes (gray matter (GM), cerebrospinal fluid (CSF), white matter hyperintensity (WMH)), cerebral microbleeds (CMB), and structural white matter connectivity were calculated. Lifestyle factors were combined into the Lifestyle for BRAin health (LIBRA) weighted sum score, with higher score indicating greater dementia risk (Figure 1). Cognition was calculated by averaging z‐scores across three cognitive domains (executive function and attention, memory, information processing speed). BAG was calculated by comparing calendar age to predictions from a neuroimaging‐based multivariable regression model. Paths between LIBRA, BAG and cognitive function were tested using linear regression and SEM, adjusting for confounders. LIBRA was split into tertiles for SEM analysis.ResultsCSF, GM, WMH and CMB best predicted BAG (R2 = 0.455, RMSE = 6.44). In regression analysis higher LIBRA scores (greater dementia risk) were associated with higher BAG (standardized regression coefficient ß = 0.127, p<0.001), lower connectivity (ß = ‐0.071, p = 0.002) and worse cognition (ßlinear = ‐0.044, p = 0.017, ßquadratic = ‐0.047, p = 0.018). Higher BAG was associated with lower connectivity (ß = ‐0.418, p<0.001) and worse cognition (ß = ‐0.165, p<0.001). Lower connectivity was associated with worse cognition (ß = 0.086, p<0.001). In mediation analysis (Figure 2), 21% of the total differences between the highest and lowest LIBRA tertile on cognition was mediated by BAG (ßindirect = ‐0.019, p<0.001; ßtotal = ‐0.092, p<0.001), and an additional 4.1% was mediated via connectivity (ßindirect = ‐0.003, p<0.001; ßtotal = ‐0.073, p<0.001).ConclusionAssociations between health‐ and lifestyle‐based risk/protective factors (LIBRA) and cognition is partially explained by maintenance of brain reserve (BAG) and neural reserve (connectivity). Lifestyle interventions promoting brain and neural reserve may help maintain cognitive function into older age.
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