Effects of early surgical menopause on sleep, memory, and medial temporal lobe structure at midlife
Bibliographic record
Abstract
Abstract Background Women bear the greatest burden of Alzheimer’s disease (AD) with menopause‐associated estrogen (E) loss becoming increasingly implicated. Surgical menopause <45 years of age (via bilateral salpingo‐oophorectomy, BSO) is thought to further increase the risk (Rocca et al., 2007). Neurodegeneration and atrophy in medial temporal lobe (MTL) structures including the perirhinal (PRC) and entorhinal (ERC) cortices occur in the very early stages of AD (e.g. Khan et al., 2013; Wolk et al., 2017). Further, sleep disturbance is also implicated in AD progression (Lim et al., 2013). Unknown is whether BSO‐associated sleep disturbance contributes to reduced memory performance and MTL atrophy via sleep disturbance, and whether E2 supplementation influences this relation. Our study aimed to determine the effect of early hormone deprivation (via BSO) on MTL volume, visual recognition memory, and whether this is correlated with sleep disturbance. Method Demographic and cognitive measures were administered to women with an oophorectomy <45 years who were either taking estradiol‐based hormone therapy (BSO+E2: n=19), or not taking E2 (BSO no E2: n=15). Data was also collected from age‐matched premenopausal women (AMC: n=27). High‐resolution T2‐weighted scans were acquired using a Siemens 3T Prisma scanner, and hippocampal subfields, PRC, ERC, and parhippocampal cortex were manually segmented (Olsen et al., 2017) in FSLView. The interference match‐to‐sample (IMTS) task was used to asses and recognition memory (Watson et al., 2013). Sleep was assessed using an at‐home polysomnography device (Vitaport‐5/REMbo‐234, Temec Technologies). Result Relative to AMCs, the BSO no E2 group had smaller volumes in the dentate gyrus, CA2, and CA3 (DGCA23) (p<.05, d=1.03). Relative to BSO+E2 women with BSO no E2 had reduced recognition memory performance (p<.05; d=1.36) and their sleep was more disrupted, indicated by increased sleep latency (p<.05, d=.71), and cortical arousals ( p<.05, d=.87]. DGCA23 volume and nighttime arousals were correlated negatively (r=‐.503, p<.05). Conclusion Our findings demonstrate that HPC, recognition memory, and sleep are sensitive to E2 loss and suggest that reduced HPC volume relates to disrupted sleep. Taken together these findings begin to explicate the path from early menopause to late‐life dementia and the importance of E2 for women’s brain health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".