Cognitive Decline and Alzheimer's Disease Risk in Women with Bilateral Oophorectomy
Bibliographic record
Abstract
There are marked sex differences in Alzheimer’s disease (AD), with women comprising two-thirds of individuals with AD. Sex-specific risk factors for women conferring 17β-estradiol (E2) loss have been proposed as key contributors. The effects of early E2 loss on cognitive decline and AD risk are well-demonstrated in a range of contexts. In animal models, E2 loss leads to rapid and reversible neuronal decline, and in older, spontaneously menopausal women, the loss of E2 is associated with cognitive and structural decline. Importantly, women with early E2 loss via bilateral oophorectomy show decrements to cognition and brain structure post-oophorectomy and an increased risk of AD in later life. This thesis aimed to investigate cognitive decline and AD risk in women with bilateral oophorectomy across a variety of life stages and cohorts. Study 1 investigated subjective cognitive decline (SCD) in midlife women with bilateral oophorectomy. We determined that women with bilateral oophorectomy experience SCD at an earlier age than is typically observed, however we did not detect SCD-associated differences in cognitive tasks or brain structure. Study 2 investigated longitudinal decline in cognition and brain structure in women with bilateral oophorectomy from midlife to older age. We found that, compared to women with spontaneous menopause, women with bilateral oophorectomy had greater longitudinal decline in visual memory. This suggests that women with bilateral oophorectomy may experience a worsening of visual memory performance that extends over multiple decades. Study 3 investigated AD risk and resilience factors for women with bilateral oophorectomy, concluding that an APOE4 allele further elevates risk, while use of hormone therapy and increased education reduces risk. Overall, these findings suggest that the early loss of E2 in women with bilateral oophorectomy is a relevant contributor to cognitive decline and AD risk in later life, and propose additional directions for research, awareness, and prevention. More broadly, the results of this thesis provide further insight into E2 loss as a factor towards understanding sex differences in AD and how early and midlife events affecting E2 may shape women’s future cognitive outcomes.
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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 | 0.001 |
| 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".