A history of previous childbirths is linked to women's white matter brain age in midlife and older age

Abstract

Maternal brain adaptations occur in response to pregnancy, but little is known about how parity impacts white matter and white matter ageing trajectories later in life. Utilising global and regional brain age prediction based on multi‐shell diffusion‐weighted imaging data, we investigated the association between previous childbirths and white matter brain age in 8,895 women in the UK Biobank cohort (age range = 54–81 years). The results showed that number of previous childbirths was negatively associated with white matter brain age, potentially indicating a protective effect of parity on white matter later in life. Both global white matter and grey matter brain age estimates showed unique contributions to the association with previous childbirths, suggesting partly independent processes. Corpus callosum contributed uniquely to the global white matter association with previous childbirths, and showed a stronger relationship relative to several other tracts. While our findings demonstrate a link between reproductive history and brain white matter characteristics later in life, longitudinal studies are required to establish causality and determine how parity may influence women's white matter trajectories across the lifespan.

Mind the gap: Performance metric evaluation in brain‐age prediction

“…To estimate global brain age, we used the XGBoost regression algorithm (XGB; https://github.com/dmlc/xgboost ), which is based on gradient tree boosting. XGB has demonstrated high performance in previous machine learning competitions (Chen & Guestrin, 2016 ), and has been used in a number of recent brain age studies (Anatürk et al, 2021 ; Beck et al, 2021 ; de Lange et al, 2019 ; de Lange, Anatürk, et al, 2020 ; Voldsbekk et al, 2021 ; Richard et al, 2020 ). Learning objective was set to regression with squared loss.…”

Sex‐ and age‐specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort

“…Briefly, we processed diffusion‐weighted imaging data using an optimized diffusion pipeline as described in detail in Maximov et al, 2019 . We included metrics derived from DTI (Basser et al, 1994 ), DKI (Jensen et al, 2005 ), and WMTI (Fieremans et al, 2011 ) as input features in the age prediction models, as described in Voldsbekk et al, 2021 . The metrics for each model are listed in Supporting Information (SI) Section 1 .…”

“…Positive BAG values have also been associated with negative outcomes in population‐based studies, including cardiovascular risk, cognitive impairments, and dementia risk (Biondo et al, 2021 ; de Lange, Anatürk, et al, 2020 ; Egorova et al, 2019 ; Franke & Gaser, 2012 ; Gaser et al, 2013 ; Kolbeinsson et al, 2020 ; Löwe et al, 2016 ; Wang et al, 2019 ). Previous studies have shown accurate age prediction based on diffusion‐weighted imaging measures (Beck, de Lange, Maximov, et al, 2021 ; Cole, 2020 ; Richard et al, 2018 ; Voldsbekk et al, 2021 ), as well as associations between WM BAG and CMRs (Beck, de Lange, Alnaes, et al, 2021 ; Beck, de Lange, Pedersen, et al, 2021 ). However, these previous studies did not assess sex‐specific effects, or whether CMRs interact with APOE genotype to influence WM BAG during certain life phases.…”

Characterizing the Brain Structural Adaptations Across the Motherhood Transition

“…Despite being a promising tool, no study has applied this technique to study the human maternal brain during gestation or postpartum so far. The only diffusion-based neuroimaging study in the maternal brain literature is a recent large-scale cross-sectional study with middle-aged mothers (54–81 years) of the UK Biobank neuroimaging database ( 89 ). This study revealed that the more parity the less estimated brain age based on their WM characteristics, which suggests a protective effect of parity on WM later in life.…”

“…Recent investigations have approached the long-term effects of parenthood by analyzing how elderly subjects who became parents decades ago differ neuroanatomically from those who did not have children. In elder women, a higher number of previous children has been found to be associated with less apparent brain aging in WM ( 89 ), cortical ( 89 , 107 ) and subcortical regions ( 108 ), larger global GM cortical volume ( 89 ) and thickness ( 109 ) and distinct patterns of resting state functional connectivity ( 110 ). In Ning et al ( 111 ), middle-aged females and males with a higher number of children displayed better visual memory, faster response time, and lower predicted brain age, suggesting that lifestyles associated with parenting, rather than the physiology of pregnancy and lactation themselves, might be beneficial for brain aging processes.…”