Age as a moderator variable in the investigation of the relationship between brain structure and cognition

Understanding how differences in brain structure relate to differences in cognition across the lifespan is essential for addressing age-related cognitive decline. Since age is strongly associated with both brain structure and cognition, predictive models often risk simply capturing age effects. To mitigate this risk, deconfounding is typically applied to remove the linear effects of age. Here, we propose to treat age instead as a moderator variable, therefore capturing changes in how brain structure and cognitive abilities are statistically connected. For this view to hold, variations in brain structure linked to differences in cognitive performance in older subjects (e.g. related to disease) would differ from those in younger subjects. Using structural brain imaging data from the UK Biobank, we found evidence supporting this, and that the generalisability of prediction models depends on the age group used to train the model. These findings highlight the complex nature of age-related brain-cognition interactions, and suggest that the optimal modelling approach depends on the population under study.