Throughout a single lifetime, the brain undergoes many changes. In early development, brain circuits are connected and pruned; in adolescence circuits mature and, in midlife, the menopause transition (MT) impacts a host of brain functions—from energy metabolism to synaptogenesis. Despite the clear link between MT and brain function, very little data exists on how different stages of the MT (pre-, peri-, and post-menopause) impacts the brain.
In a new study led by Lisa Mosconi, Ph.D., from the Weill Cornell Medical College/New York-Presbyterian Hospital, a team of researchers conducted a neuroimaging study with a total of 182 female participants at pre-, peri- and post-menopausal stages to determine the effect of MT on a panel of brain biomarkers related to structure, connectivity, energy metabolism, and Aβ deposition. To ensure that any changes the researchers observed were really the result of MT, specifically, and not due to chronological aging, each female MT group of participants was compared to an age-matched group of male participants.
The researchers found that the post- and peri-menopausal groups had lower gray matter volume (GMV) in various cortical and subcortical regions compared to the control group. Interestingly, by post-menopause these GMV changes stabilized and had largely recovered in the precuneus—a brain region important for social processing, episodic memory and integration of information. In fact, over a 2-year span, GMV in the precuneus increased compared to both peri-menopausal female participants and age-matched male participants. This increased GMV in the precuneus was also correlated with increased memory scores. Interestingly, the precuneus has also been shown to dynamically change in late pregnancy and to recover back to normal by weaning, indicating that this brain region is generally susceptible to fluctuations in estrogen.
White matter volume (WMV) was also reduced in post- and peri-menopausal groups. However, the researchers note that despite this WMV reduction, all MT groups had higher fractional anisotropy (FA)—a reflection of fiber density, axonal diameter, and white matter myelination—in the corona radiata and fornix. Dr. Mosconi and colleagues interpret the higher FA values in post- and peri-menopausal groups as increased efficiency in WM and speculate that the MT results in refinement of white matter connectivity within some key brain structures.
In addition to brain structure, the researchers discovered differences in brain metabolism and energy. Both the post- and peri-menopausal groups showed hypometabolism in the parieto-temporal cortices. And cerebral blood flow and ATP production in these regions were elevated post-menopause. Although cerebral blood flow, cerebral glucose metabolism, and regional brain activity typically rise and fall together, these metrics can dissociate in cases of pathology, inflammation, or as the brain’s way of compensating in some way. Preclinical data from other researchers have shown that estrogen loss during MT triggers a decrease in cerebral glucose metabolism, likely as a compensatory mechanism. Thus, Mosconi and colleagues hypothesize that the hypometabolism observed in the post- and peri-menopausal groups in their study reflect similar compensatory mechanisms. Mitochondrial ATP production in the brain was higher in the post-menopausal group, indicating another potential adaptive change in response to MT.
Finally, the researchers looked at Aβ deposition across all groups and found increased deposition in the post- and peri-menopausal groups compared to both the pre-menopausal female group and age-matched male participants. Given that the chronology of MT frequently aligns with the pre-symptomatic accumulation of beta amyloid pathology, the researchers suspect that this increased Aβ exposure in peri- and post-menopausal female participants partly explains the higher prevalence of AD in female individuals. On the other hand, it’s possible that hormonal changes from MT are accelerating aging, which is then increasing Aβdeposition; the study did not try to differentiate between chronological and biological aging. Furthermore, Aβ deposition doesn’t always mean AD is around the corner; many individuals carry Aβ and function just fine.
Notably, all of the MT results were independent of whether or not participants received hormonal treatment (HT) or a hysterectomy. However, the authors also note a few caveats to their study. First, the educational status of participants in the MT groups was an average of 17 years, which is greater than the average of 12-13 years reported for the general U.S. population. Second, a large proportion of the participants in this study (42%) were APOE-4 carriers, compared to only 15-30% in the general population. Given that APOE4 carriers show accelerated aging on a variety of biological markers, the non-representative sample of participants in this study may be a confounding factor. Finally, because the groups were predominantly made up of White participants (80% in the pre-menopausal group; 77% in the peri-menopausal group and 89% in the post-menopausal group), the results of this study are not representative of the general population.
Regardless, the results of this study make it clear that the menopausal transition period is a dynamic period of change that impact key brain biomarkers. Future studies will need to address whether the changes in post-menopausal groups observed in this study replicate in other studies and, if they do, whether or not such changes explain the sex-dependent emergence and progression of Alzheimer’s disease.
Lisa Mosconi, Ph.D., Weill Cornell Medical College/New York-Presbyterian Hospital