Abstract
The menopause transition involves changes in oestrogens and adipose tissue distribution, which may influence female brain health post-menopause. Although increased central fat accumulation is linked to risk of cardiometabolic diseases, adipose tissue also serves as the primary biosynthesis site of oestrogens post-menopause. It is unclear whether different types of adipose tissue play diverging roles in female brain health post-menopause, and whether this depends on lifetime oestrogen exposure, which can have lasting effects on the brain and body even after menopause. Using the UK Biobank sample, we investigated associations between brain characteristics and visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT) in 10,251 post-menopausal females, and assessed whether the relationships varied depending on length of reproductive span (age at menarche to age at menopause). To parse the effects of common genetic variation, we computed polygenic scores for reproductive span. The results showed that higher VAT and ASAT were both associated with higher grey and white matter brain age, and greater white matter hyperintensity load. The associations varied positively with reproductive span, indicating more prominent associations between adipose tissue and brain measures in females with a longer reproductive span. The effects were in general small, but could not be fully explained by genetic variation or relevant confounders. Our findings indicate that associations between abdominal adipose tissue and brain health post-menopause may partly depend on individual differences in cumulative oestrogen exposure during reproductive years, emphasising the complexity of neural and endocrine ageing processes in females.
18 Authors
- Louise S. Schindler
- Sivaniya Subramaniapillai
- Claudia Barth
- Dennis van der Meer
- Mads L. Pedersen
- Tobias Kaufmann
- Ivan I. Maximov
- Jennifer Linge
- Olof Dahlqvist Leinhard
- Dani Beck
- Tiril P. Gurholt
- Irene Voldsbekk
- Sana Suri
- Klaus P. Ebmeier
- Bogdan Draganski
- Ole A. Andreassen
- Lars T. Westlye
- Ann-Marie G. de Lange
1 Application
Application ID | Title |
27412 | Boosting the power of GWAS using novel statistical tools |