Abstract
Depression is associated with markers of accelerated aging, but it is unclear how this relationship changes across the lifespan. We examined whether a brain-based measure of accelerated aging differed between depressed and never-depressed subjects across the adult lifespan and whether it was related to cognitive performance and disability. We applied a machine-learning approach that estimated brain age from structural MRI data in two depressed cohorts, respectively 170 midlife adults and 154 older adults enrolled in studies with common entry criteria. Both cohorts completed broad cognitive batteries and the older subgroup completed a disability assessment. The machine-learning model estimated brain age from MRI data, which was compared to chronological age to determine the brain–age gap (BAG; estimated age-chronological age). BAG did not differ between midlife depressed and nondepressed adults. Older depressed adults exhibited significantly higher BAG than nondepressed elders (Wald χ2 = 8.84, p = 0.0029), indicating a higher estimated brain age than chronological age. BAG was not associated with midlife cognitive performance. In the older cohort, higher BAG was associated with poorer episodic memory performance (Wald χ2 = 4.10, p = 0.0430) and, in the older depressed group alone, slower processing speed (Wald χ2 = 4.43, p = 0.0354). We also observed a statistical interaction where greater depressive symptom severity in context of higher BAG was associated with poorer executive function (Wald χ2 = 5.89, p = 0.0152) and working memory performance (Wald χ2 = 4.47, p = 0.0346). Increased BAG was associated with greater disability (Wald χ2 = 6.00, p = 0.0143). Unlike midlife depression, geriatric depression exhibits accelerated brain aging, which in turn is associated with cognitive and functional deficits.
Highlights
Aging has an inevitable effect at molecular, cellular, and organ levels, with biological aging resulting in degeneration or reduction in the organ’s reparative or regenerative potential1
As white matter hyperintensity (WMH) are common in geriatric major depressive disorder (MDD), associated with aging[42,43], and a potential marker of accelerated cerebrovascular aging, in further exploratory analyses we examined the relationship between WMH volume, brain-age “gap” (BAG), and clinical measures
After adjusting for covariates including diagnosis, a higher BAG was associated with poorer episodic memory performance (Wald Χ2 = 4.10, 132 df, p = 0.0430; Fig. 2) but not executive function (Wald Χ2 = 0.03, 132 df, p = 0.8643), processing speed (Wald Χ2 = 2.78, 132 df, p = 0.0957), or working memory (Wald Χ2 = 0.00, 132 df, p = 0.9974)
Summary
Aging has an inevitable effect at molecular, cellular, and organ levels, with biological aging resulting in degeneration or reduction in the organ’s reparative or regenerative potential. Using standard structural MRI sequences, a prediction model generated from a learning sample of neurologically healthy adults can be applied to a new individual brain MRI to estimate that individual’s apparent biological age. The difference between this estimated biological age and the subject’s chronological age yields the brain-age “gap” (BAG), a marker of how much “older” or “younger” a given brain appears relative to the individual’s chronological age. This hypothesis is supported by studies associating greater chronicity or duration of depression with volumetric differences in key regions such as the hippocampus 14–16
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