Factors Influencing Change in Brain-Predicted Age Difference in a Cohort of Healthy Older Individuals

Abstract

Background: There is considerable variability in the rate at which we age biologically, and the brain is particularly susceptible to the effects of aging. Objective: We examined the test-retest reliability of brain age at one- and three-year intervals and identified characteristics that predict the longitudinal change in brain-predicted age difference (brain-PAD, defined by deviations of brain age from chronological age). Methods: T1-weighted magnetic resonance images were acquired at three timepoints from 497 community-dwelling adults (73.8±3.5 years at baseline, 48% were female). Brain age was estimated from whole brain volume, using a publicly available algorithm trained on an independent dataset. Linear mixed models were used, adjusting for sex, age, and age2. Results: Excellent retest reliability of brain age was observed over one and three years. We identified a significant sex difference in brain-PAD, where a faster rate of brain aging (worsening in brain age relative to chronological age) was observed in men, and this finding replicated in secondary analyses. The effect size, however, was relatively weak, equivalent to 0.16 years difference per year. A higher score in physical health related quality of life and verbal fluency were associated with a faster rate of brain aging, while depression was linked to a slower rate of brain aging, but these findings were not robust. Conclusion: Our study provides consistent evidence that older men have slightly faster brain atrophy than women. Given the sparsity of longitudinal research on brain age in older populations, future prospective studies are needed to confirm our findings.

Investigating the temporal pattern of neuroimaging-based brain age estimation as a biomarker for Alzheimer's Disease related neurodegeneration

“…How the BAG trajectory is moderated by AD progression-related covariates also yielded interesting results. In a healthy control population, a recent brain aging study found weak but accelerated brain aging in men compared to women in an older population ( Wrigglesworth et al, 2022 ). When stratifying our sample by disease status (i.e.…”

“…The misleading notion of describing greater BAG values in cross-sectional studies as an acceleration of brain aging was recently recognized by Vidal-Pineiro et al (2021) , though they did not explore the BAG in the context of AD. There have been remarkably few studies investigating the BAG with a longitudinal design ( Bjørnebekk et al, 2021 ; Egorova et al, 2019 ; McWhinney et al, 2021 ; Wrigglesworth et al, 2022 ), and fewer still related AD. Two notable BAG studies using longitudinal data to explore AD compared study time-points only to baseline assessment ( Franke and Gaser, 2012 ; Löwe et al, 2016 ), but this approach does not fully investigate potential non-linear trajectories of the BAG.…”

“…To study the temporal pattern, we utilized longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) ( http://adni.loni.usc.edu/ ) from individuals with up to 8 years of follow-up. Further, as BAG has been shown to be moderated by factors such as sex ( Franke and Gaser, 2019 ; Wrigglesworth et al, 2022 ) and carriership of the apolipoprotein E ε4 (APOEε4) allele ( Löwe et al, 2016 ), we also examined their influence on the BAG temporal patterns. Importantly, this study uses a longitudinal design to investigate the pattern (linear vs. non-linear) and rate of change in BAG over time in individuals who progress from MCI to clinical AD.…”

Health-related heterogeneity in brain aging and associations with longitudinal change in cognitive function

“…This uses voxel-level measures of grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) volume to provide a single estimate of brain age measured across the whole brain. Using this model, we have found an association between advanced brain aging and poor cognitive processing ( Wrigglesworth et al, 2022a ), and identified sex differences in the change in brain aging over time ( Wrigglesworth et al, 2022b ).…”

The association between sex hormones and the change in brain‐predicted age difference in older women

“…4 Using a brain age model based on structural magnetic resonance imaging (MRI), 3 we previously reported that brain-PAD is negatively associated with cognitive performance in older community-dwelling individuals, and observed a faster rate of brain ageing in men compared with women, over 3-years of follow-up. 5,6 Sex differences in brain ageing may arise from differences in the concentration of circulating sex hormones. 7 Oestrogens have received considerable attention in this field, especially as there are changes in the production of oestrogens after menopause.…”