Estrogen exposure may influence women's risk of Alzheimer's disease, but little is known about how it affects normal brain aging. Recent findings from the UK Biobank demonstrate less evidence of brain aging in women with a history of multiple childbirths. Here, we investigated the link between brain aging, estrogen exposure, and APOE genotype beyond the effects of parity in 16,854 UK Biobank women. Machine learning was used to predict brain age based on neuroimaging-derived measures, and the difference between an individual's predicted and chronological age was used as an estimate of brain aging. Cumulative estrogen exposure was estimated using an index including age at menarche and menopause, BMI, time since menopause, and duration of hormone replacement therapy. Endogenous hormone exposure was approximated by reproductive span, while exogenous exposure was estimated by usage, onset, and duration of hormone replacement therapy and oral contraceptives. Higher cumulative, endogenous, and exogenous estrogen exposure were each linked to higher brain age relative to chronological age. Earlier onset of hormone replacement therapy, particularly before menopause, was associated with less evident brain aging in APOE e4 carriers only, while higher circulating estradiol levels during menopause were linked to more evident brain aging in carriers and less evident brain aging in non-carriers. The results indicate that estrogen exposure and parity may differentially relate to women's brain aging, and that APOE e4-specific associations between estrogen and brain aging may be of importance for optimizing hormone replacement therapy regimes in perimenopausal women. Women's health | Estrogens | Parity | Apolipoproteins E | Neuroimaging | Machine learningCorrespondence: a.m.g.d.lange@psykologi.uio.no claudia.barth@medisin.uio.no

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, we estimated brain and cognitive maintenance based on deviations from normative aging patterns in the Whitehall II MRI sub-study cohort, 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 cognitive maintenance independent of the degree of brain maintenance. No strong evidence was found for associations between lifestyle trajectories and brain or cognitive maintenance. In conclusion, we present a novel method to characterize 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.