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Summary

Despite the fact that during the perimenopause there is a decline in attention and working/verbal memory, there are significant individual differences. The exact contributions of hormones and menopausal symptoms to domain-specific cognitive functions remain unknown. Bearing this in mind, recently, Weber et al [1] published results of the Rochester Investigation of Cognition Across Menopause (RICAM), a longitudinal study conducted over three waves from 2005 through 2016. The study aimed at determining if there were distinct cognitive profiles during the perimenopause, and identifying factors related to each profile. Analysis included 85 perimenopausal women (aged 40-60) of the cohort to whom 400 bi-annual visits were performed, administrating a comprehensive neuropsychological (NP) battery, and self-reporting questionnaires that assessed depression, anxiety, vasomotor symptoms and sleep quality; as well as measuring 17β-estradiol (E2) and FSH. Multilevel latent profile analysis was utilized to identify cognitive profiles and regressions were carried out to determine differences in hormones and symptoms by profile after adjusting for Stages of Reproductive Aging Workshop + 10 (STRAW + 10) stage and demographic factors. Perimenopausal cognitive profiles consisted of cognitively normal (Profile 1; n = 162), weaknesses in verbal learning and memory (Profile 2; n = 94), strengths in verbal learning and memory (Profile 3; n = 98) and strengths in attention and executive function (Profile 4; n = 61). It was found that profile 2 was differentiated by less hormonal variability and more sleep disturbance than women with profile 1 (p < 0.05). The investigators conclude that there is significant heterogeneity in cognition during the perimenopause and that, although, the majority of women do not develop impairments, a significant minority of women experience weaknesses in verbal learning and memory. Therefore, as the authors state, profile analysis could help identify populations that are at risk and perform prompt interventions.

Commentary

The menopausal transition is characterized by fluctuating, but basically declining levels of E2. There is evidence that during this stage, besides age, a decrease in cognition occurs. Authors have previously demonstrated that compared to premenopausal women, those in the late peri- and early postmenopausal stage, perform worse on measures of attention/working memory, processing speed, verbal fluency and verbal memory [2]. Important to mention is that the cognitive domains that change over the menopausal transition also change across the menstrual cycle, suggesting the crucial role of sex steroid hormones over the female brain, specifically in these domains. According to a meta-analysis, the link between cognition and hormones can be related to the fact that oophorectomy leads to a decrease in cognitive abilities, most prominently verbal memory, semantic memory and processing speed [3]. Recently, Chaikittisilpa et al [4] found a high prevalence of mild cognitive impairment, and the non-amnestic subtype, among women with surgical menopause. Add back E2 therapy reverses the deficits in verbal memory induced by oophorectomy. Therefore, suggesting that E2 contributes to changes in verbal memory across the menopausal transition. Unfortunately, as the authors state, there are no large randomized controlled trials evaluating the effects of E2 therapy on cognition in perimenopausal women that can aid at better understanding the role of E2 over female cognition. In the present commented study, the performed a novel approach to better understand cognition during the perimenopause, focusing on cognition heterogeneity during this stage. Indeed, until now, all longitudinal studies related to cognition and the menopausal transition have examined mean cognitive changes, an approach that characterizes the normative experience of women and identifies cognitive domains that could be sensitive to reproductive aging and sex steroid hormones. Nevertheless, this approach fails to capture the significant heterogeneity inherent in cognition and the variability of women’s experiences. In this sense, significant individual differences have been observed; for instance, some women show no changes while others show significant changes. So, authors used latent profile analysis to identify subsets of women who may experience more significant declines and analyzed the factors that differentiate these women from those who experience limited cognitive changes. Also, they used NP tests considered to be more extensive than those used in prior studies, and examined cognition function more frequently than in other studies. Using this approach, they found four distinct cognitive functional profiles among the 85 women with 415 observations. The majority (39%) of observations fit into Profile 1, with normal cognitive function. They also identified two distinct profiles showing cognitive strengths: one in verbal learning and memory, and one in attention and executive function. Nevertheless, over 20% of observations fit profile 2, with weaknesses in verbal learning and memory. It was observed that demographic factors differed between profiles; women having visits fitting the cognitively normal or cognitive strength profiles were more likely to be White and better educated. Of importance is the fact that, for most women, the menopausal transition does not lead to significant cognitive impairment consistent with dementia; whereas, for a significant minority, weaknesses are seen in the areas of verbal learning and memory, which is consistent with other studies, but found to be greater in the present study. As the authors state, profile 2 is similar to that of amnestic mild cognitive impairment, a risk factor for Alzheimer’s disease. Although, not all individuals with amnestic mild cognitive impairment develop Alzheimer, many researchers consider this mild cognitive impairment as a prodromal stage, with verbal memory being the best and earliest predictor. Specifically, profile 2 (weakness in verbal learning and memory) was associated with less variability in FSH and E2 levels as compared to profile 1 (cognitively normal). Profile 2 was also associated with more sleep symptoms and a trend for more depressive symptoms (p=0.06) compared to profile 1. There was also a trend for profile 4 (strength in attention and executive function) to be associated with fewer sleep symptoms as compared to profile 1.

There are several limitations to the present study, first, aspects of language, such as naming, or aspects of executive function, such as set-shifting and response inhibition, were not measured. Thus, authors could only rely on self-reportedVSM rather than objective measures of vasomotor symptoms and sleep. On the other hand, hormone measures were taken 6 months apart, which may not adequately capture variability across successive menstrual cycles. Some women were further along in the menopausal transition than others, and there was variability in the number of perimenopausal visits they underwent. Finally, the RICAM cohort is a relatively small sample of well educated, predominantly White women. Hence, there is a need for more longitudinal data to see whether these same findings can be generalized to a larger, more representative sample of perimenopausal women.

In conclusion, the present study confirms that there is significant heterogeneity in women’s cognitive function during the perimenopause, with most showing no global impairment, yet a significant minority developing weaknesses in verbal learning and memory that are related to both hormonal flux and menopausal symptoms. More longitudinal studies, with more participants, will be needed to determine if these weaknesses persist in the late postmenopausal period.

Peter Chedraui, MD, PhD
Instituto de Investigación e Innovación en Salud Integral
Universidad Católica de Santiago de Guayaquil, Guayaquil, Ecuador

References

  1. Weber MT, Rubin LH, Schroeder R, Steffenella T, Maki PM. Cognitive profiles in perimenopause: hormonal and menopausal symptom correlates. Climacteric. 2021;24(4):401-407.
    https://pubmed.ncbi.nlm.nih.gov/33759672/
  2. Weber MT, Rubin LH, Maki PM. Cognition in perimenopause: the effect of transition stage. Menopause. 2013;20(5):511-7.
    https://pubmed.ncbi.nlm.nih.gov/23615642/
  3. Georgakis MK, Beskou-Kontou T, Theodoridis I, Skalkidou A, Petridou ET. Surgical menopause in association with cognitive function and risk of dementia: A systematic review and meta-analysis. Psychoneuroendocrinology. 2019;106:9-19.
    https://pubmed.ncbi.nlm.nih.gov/30928686/
  4. Chaikittisilpa S, Orprayoon N, Santibenchakul S, Hemrungrojn S, Phutrakool P, Kengsakul M, Jaisamrarn U. Prevalence of mild cognitive impairment in surgical menopause: subtypes and associated factors. Climacteric. 2021;24(4):394-400.
    https://pubmed.ncbi.nlm.nih.gov/33688775/

 


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If you would like to add a comment or contribute to a discussion based on this issue, please contact Menopause Live Editor, Peter Chedraui, at peter.chedraui@cu.ucsg.edu.ec.

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