Abstract
The concept of brain maintenance refers to the preservation of brain integrity in older age, while cognitive reserve refers to the capacity to maintain cognition in the presence of neurodegeneration or aging‐related brain changes. While both mechanisms are thought to contribute to individual differences in cognitive function among older adults, there is currently no “gold standard” for measuring these constructs. Using machine‐learning methods, we estimated brain and cognitive age based on deviations from normative aging patterns in the Whitehall II MRI substudy cohort (N = 537, age range = 60.34–82.76), and tested the degree of correspondence between these constructs, as well as their associations with premorbid IQ, education, and lifestyle trajectories. In line with established literature highlighting IQ as a proxy for cognitive reserve, higher premorbid IQ was linked to lower cognitive age independent of brain age. No strong evidence was found for associations between brain or cognitive age and lifestyle trajectories from midlife to late life based on latent class growth analyses. However, post hoc analyses revealed a relationship between cumulative lifestyle measures and brain age independent of cognitive age. In conclusion, we present a novel approach to characterizing brain and cognitive maintenance in aging, which may be useful for future studies seeking to identify factors that contribute to brain preservation and cognitive reserve mechanisms in older age.
Highlights
Most cognitive abilities are well established to decline with age (Grady, 2012), and cognitive deterioration can to some extent be attributed to concurrent changes in brain structure (Bennett & Madden, 2014; Fjell et al, 2016; Fjell, Sneve, Grydeland, Storsve, & Walhovd, 2017; Fjell & Walhovd, 2010; Nyberg, Dahlin, Stigsdotter Neely, & Bäckman, 2009)
The aging population is characterized by considerable variation between individuals, and while some develop cognitive impairment, Alzheimer's disease, and other types of dementia, others may to a large extent maintain their cognitive function well into late life (Nyberg et al, 2012)
While our original method for estimating lifestyle engagement is in line with previous studies (i.e., count of unhealthy/healthy behaviors, (Lourida et al, 2019; Sabia et al, 2009) and the health behaviors were thresholded based on established guidelines and recommendations, our findings suggest that when brain and cognitive maintenance is of focus, lifestyle indices should integrate health behaviors in their continuous forms, where available, as this may improve sensitivity to the small effects often reported for lifestyle variables (Corley, Cox, & Deary, 2018)
Summary
Most cognitive abilities are well established to decline with age (Grady, 2012), and cognitive deterioration can to some extent be attributed to concurrent changes in brain structure (Bennett & Madden, 2014; Fjell et al, 2016; Fjell, Sneve, Grydeland, Storsve, & Walhovd, 2017; Fjell & Walhovd, 2010; Nyberg, Dahlin, Stigsdotter Neely, & Bäckman, 2009). A recent multicohort study of 45,615 individuals further highlighted that BAG may be a sensitive marker of disease, with accelerated brain aging observed in a range of conditions including mild cognitive impairments, Alzheimer's disease, and depression (Kaufmann et al, 2019) The linear regression analyses and Z-tests for correlated samples were rerun after outliers on any of the variables of interest were excluded (i.e., individuals with values Q3 + 3 × IQR)
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