Estrogen, brain structure, and cognition in postmenopausal women

Abstract

Declining estrogen levels before, during, and after menopause can affect memory and risk for Alzheimer’s disease. Undesirable side effects of hormone variations emphasize a role for hormone therapy (HT) where possible benefits include a delay in the onset of dementia—yet findings are inconsistent. Effects of HT may be mediated by estrogen receptors found throughout the brain. Effects may also depend on lifestyle factors, timing of use, and genetic risk. We studied the impact of self‐reported HT use on brain volume in 562 elderly women (71–94 years) with mixed cognitive status while adjusting for aforementioned factors. Covariate‐adjusted voxelwise linear regression analyses using a model with 16 predictors showed HT use as positively associated with regional brain volumes, regardless of cognitive status. Examinations of other factors related to menopause, oophorectomy and hysterectomy status independently yielded positive effects on brain volume when added to our model. One interaction term, HTxBMI, out of several examined, revealed significant negative association with overall brain volume, suggesting a greater reduction in brain volume than BMI alone. Our main findings relating HT to regional brain volume were as hypothesized, but some exploratory analyses were not in line with existing hypotheses. Studies suggest lower levels of estrogen resulting from oophorectomy and hysterectomy affect brain volume negatively, and the addition of HT modifies the relation between BMI and brain volume positively. Effects of HT may depend on the age range assessed, motivating studies with a wider age range as well as a randomized design.

1 INTRODUCTION

By 2030, the world population of menopausal and postmenopausal women is projected to increase to 1.2 billion, with 47 million new entrants each year (Hill,1996). Using age 50 as a proxy for menopause, about 25 million women pass through menopause each year (Hill,1996). Perimenopause, menopause, and postmenopause all represent periods of life where many women have been considered candidates for conjugated equine estrogens (CEE) or other forms of exogenous hormone therapy (HT) to treat menopausal symptoms. HT was initially regarded as potentially protective against heart disease, osteoporosis, and dementia (Green & Simpkins,2000; Mendelsohn,2002) in postmenopausal women. Prescriptions for CEE fell abruptly (Kim et al.,2005) after negative reports from large multicenter trials showed equivocal effects or even increased risk of adverse health outcomes (Grady et al.,2002; Shumaker et al.,2003; Shumaker, Legault, Kuller, et al.,2004). More recently, however, studies began to re‐evaluate the possible benefits of HT including stress reduction, enhancement of cardiovascular health, improvement in cognitive performance, and a delay in the onset of dementia (Herrera, Hodis, Mack, & Mather,2017; Merlo, Spampinato, & Sortino,2017; Speth, D’Ambra, Ji, & Sandberg,2018).

Alzheimer’s disease (AD) is the most common neurodegenerative cause of dementia; female sex is a key risk factor for AD, particularly after menopause and precipitous declines in estrogen levels (Mosconi et al.,2018; Riedel, Thompson, & Brinton,2016). Estradiol is the most bioactive estrogen before menopause (Fischer, Gleason, & Asthana,2014), acting on alpha and beta‐receptors found throughout the brain (Barth, Villringer, & Sacher,2015) (see Figure1). Some studies suggest that memory is influenced by the relative expression of estrogen receptors as they interact with estradiol (Bean, Ianov, & Foster,2014). Given the postmenopausal decline in levels of estradiol and potentially beneficial hormones such as progesterone, one hypothesis is that boosting these levels through HT may reduce AD risk in women. Initial support for the protective effects of HT came from observational studies, such as the Kuopio Osteoporosis Risk Factor and Prevention study, which involved a 20‐year follow‐up of 8,195 women, with 227 cases of incident AD (Imtiaz et al.,2017). In this study, long‐term postmenopausal HT was associated with a lower risk of any dementia diagnosis including AD. This contrasts with the aforementioned multicenter trials that randomized women to receive HT and failed to find any benefit of HT on dementia risk (Grady et al.,2002; Shumaker et al.,2003; Shumaker et al.,2004). However, these effects have been recently re‐evaluated as additional factors may affect the amount of risk or benefit—such as duration of HT use and the proximity of HT initiation to menopause (Girard, Metereau, Thomas, et al.,2017; Savolainen‐Peltonen, Rahkola‐Soisalo, Hoti, et al.,2019).

Given the biological complexity of estrogen effects on the brain and AD risk, we tested the following hypothesis: if history of estrogen use is present and protective in older women, this variable may be associated with larger brain volumes, as measured using MRI. Addressing this hypothesis is an important step to understand how HT may influence brain aging and cognitive performance, perhaps motivating an approach to AD risk reduction in clinical practice.

2 METHODS

2.1 Participants

The cardiovascular health study (CHS) is a multisite, population‐based longitudinal study of coronary heart disease and stroke in individuals 65 and older (Fried et al., 1991). CHS recruitment was based on the Medicare eligibility lists in four communities: Forsyth County, North Carolina; Sacramento County, California; Washington County, Maryland; and Pittsburgh (Allegheny County), Pennsylvania. In a first wave, 5,201 participants were recruited in the baseline year (1989–1990) of the study. In a second assessment, 687 African–Americans were recruited in year 5 (1992–1993) leading to a cohort of 5,888 participants. The institutional review board at each site approved the study methods, and all participants gave written informed consent.

Participant demographics are shown in Table 1. A separate column identifies, for a particular variable, whether a statistically significant difference (p < .05) exists between study sites, based upon one‐way ANOVA (continuous) or a chi‐squared test (categorical), together with effect size. Differences between sites include variation in socioeconomic and health‐related factors, as noted with significant differences for ethnicity, high school completion, diagnosis of AD/MCI and burden of white matter lesions. These factors may contribute to the differences in the prevalence of estrogen use across studies (Council TWH, n.d.).

o reduce potential bias, we ran a sensitivity analysis excluding the Forsyth County cohort given their small sample size (N = 7) and excluding two subjects whose ethnicities differed from the remaining participant population (neither white nor African American). Significance was unaffected and these records were retained in the full sample.

Of the 562 participants included, APOE4 genotype was available for 528 and 143 of these (27.1%) carried at least one APOE4 haplotype (APOE4 positive). Of these, 10 were homozygous and the remainder were heterozygous. Full methods for obtaining the APOE4 genotypes are reported elsewhere (Kuller et al., 1998).

2.2 The CHS memory study

By year 4 (1991–1992), 3,608 of the CHS enrollees participated in the CHS Memory Study (CHS‐MS) and all had undergone a low‐resolution brain MRI scan. In the final year of the study, year 11 (1998–1999), a follow‐up high‐resolution MRI scan and neurobehavioral evaluations were completed for all available, living participants (n = 2,101) (Kuller et al., 2003; Riverol, Becker, Lopez, et al., 2015). Due to the late inclusion of the high‐resolution 3D T1‐weighted spoiled gradient‐recalled echo (SPGR) MRI sequence into the scanning protocol, not all participants had high‐resolution anatomical imaging. Here we analyzed brain MRI data from 562 female participants (mean age: 79.4 ± 4.2; range: 71–94 years) who had a high‐resolution SPGR MRI scan that met quality control standards.

Neurobehavioral evaluations were made by an Adjudication Committee of experts in dementia who had access to the historical CHS cognitive test scores, primarily the Modified Mini Mental State Examination (3MSE) (Teng & Chui, 1987), Benton Visual Retention Test (BVRT) (Benton, 1945), and the Digital Symbol Substitution Test (DSST) (Salthouse, 1978), as well as the Center for Epidemiologic Studies Depression Scale (CES‐D) scores (Irwin, Artin, & Oxman, 1999). Participants were classified as having normal cognition, mild cognitive impairment (MCI), or AD, with specific subtypes of MCI examined in detail only at the Pittsburgh center (Lopez et al., 2003). Dementia classification was based on deficits in performance in two or more cognitive domains that were sufficiently severe to affect activities of daily living and their history of normal intellectual function before the onset of cognitive abnormalities; a memory deficit was not required for the diagnosis of dementia. The committee also reviewed data from vision and hearing tests, history of alcohol intake, activities of daily living questionnaire (Rosano et al., 2005), Informant Questionnaire on the Cognitive Decline of the Elderly (IQ‐CODE) (Diesfeldt, 2007), Dementia Questionnaire (Kawas, Segal, Stewart, Corrada, & Thal, 1994), vital status, date of death if relevant, history of hospitalizations, medications to treat dementia, findings from MRI scans, results of neuropsychological assessments, and hospital records (Lopez, Jagust, DeKosky, et al., 2003).

2.3 Assessment of hormone therapy

HT was assessed annually and included present and when available past estrogen use, “excluding vaginal creams”. The decision to exclude this particular type of medication was based on the fact that vaginal cream has local but very little systemic effect due to irregular absorption (Santen, Mirkin, Bernick, & Constantine, 2020). In addition, the use of these creams is typically intermittent. Present estrogen users were defined as women with prescriptions for oral estrogen recorded by medical inventory, regardless of self‐reported past use, and this information was reported as binary data at each annual time point of the CHS study. Dosage was not made available. Past estrogen users were women responding positively to ever having taken Premarin or other estrogens for hot flashes or other symptoms of menopause and not having a current prescription (Manolio et al., 1993). Past usage was available in data collected from years 4 through 6 (1994–1996) only. Past and present use of Premarin, or CEE’s, was reported at baseline (1989–1990) only and was collected in the same way as estrogen use.

For these analyses, we examined present nonspecific estrogen use reported in year 11 (1998–1999) as it corresponds with the year that the high‐resolution MRI data were acquired. We evaluated estrogen use from other time points for consistency with results from our main analysis. This included present estrogen use at baseline (1989–1990) as it corresponded with the availability of other relevant data such as age of menopause, hysterectomy and oophorectomy; past and present (combined) HT use from year 6 (1993–1994); and use of Premarin (ever), or CEE’s, from baseline (1989–1990) as this was the only CHS study time point in which these data were available.

2.4 Structural MRI

Brain MRI using the SPGR sequence was completed at each of the four sites using 1.5 T scanners, as detailed elsewhere (Bryan, Manolio, Scertz, et al., 1994). The scanning protocol used in year 11 (1998–1999) included a sagittal T1‐weighted localizer sequence, an axial T1‐weighted proton‐density, and T2‐weighted images. The axial images were 5 mm thick without interslice gaps. White matter hyperintensities, an imaging marker of small vessel ischemic disease, were visually determined using a standardized semi‐quantitative 10‐point white matter grade (WMG) going from 0 (least) to 10 (most), as described previously (Longstreth et al., 1996). CHS quality control measures included visual review of scans by a neuroradiologist, to ensure that no large space‐occupying lesions existed that could hinder analysis (Bryan et al., 1997; Raji, Lopez, Kuller, Carmichael, & Becker, 2009). We also performed our own visual assessment confirming the absence of cropping of brain tissue from the scan field of view and corruption of MR images in the tensor‐based morphometry (TBM) image processing stream. For the TBM methods used to process the brain images, refer to Supplementary Data S1.

2.5 Voxel‐wise linear regressions

At each voxel in the brain, a linear regression model (Calabrese, Schneider, Paninski, et al., 2011; Chu, Cui, & Dinov, 2009; Chu & Dinov, 2009) was fit to model relationships between regional brain volumes, our trait of interest and other factors that have demonstrated over time to have an impact on brain structure. Covariates in the analysis included body mass index (BMI) and physical activity as defined and measured in our previous work which identified a significant relationship between these variables and brain volume in a mixed gender superset of the CHS cohort analyzed here (Boyle et al., 2015). Our 16 predictors included: (1–3) site of data acquisition (dummy variables: x1, x2, x3), (4) age at year 11 of the study (x4), (5) ethnicity (white vs. non‐white; x5), (6) years of education (≤/> high school; x6), (7‐8) clinical diagnosis (dummy variables: x7, x8), (9) heart disease (x9), (10) type 2 diabetes mellitus (x10), (11) hypertension (x11), (12) white matter lesions (</≥ WMG 3; x12), (13) BMI—year 9 (x13), (14) physical activity—year 10 (weekly blocks walked; x14), (15) APOE4 status (x15) and (16) estrogen use—year 11 (x16). We statistically assessed these covariates of interest that predicted volumetric differences across the brain using multiple linear regression:

Here y represents the voxel‐wise volumetric measurement, bo is the y‐axis intercept