The Endocrinological Basis for Polycystic Ovary Syndrome: An Evolutionary Perspective
Bibliographic record
Abstract
As a common endocrinopathy of reproductive-aged women, polycystic ovary syndrome (PCOS) is characterized by ovarian hyperandrogenism, insulin resistance, and preferential abdominal fat accumulation. These characteristics in normal-weight women with PCOS are accompanied by subcutaneous abdominal adipose stem cells that intrinsically exaggerate lipid accumulation during adipocyte development in vitro in combination with an increased amount of highly lipolytic visceral fat. PCOS-related adipose characteristics are intimately linked with hyperandrogenism through genetic inheritance and epigenetic events programmed during prenatal and postnatal life. Accordingly, evolutionary theory submits that such events in PCOS may have ancestral origins, providing survival advantages in 3 contexts: (1) food scarcity with risk of starvation; (2) infectious disease risks, alleviated by visceral and omental fat; and (3) benefits from increased muscularity. But such adaptations also involve costs, given that PCOS-related traits also tend to reduce reproduction, due to oligo-anovulation. This review examines the evolutionary origins of PCOS risk as a syndrome potentiated by environmental mismatches (especially contemporary obesity and low physical activity), combined with adaptive physiological systems governed by trade-offs between survival and reproduction. This hypothesis is supported by a plethora of recent studies on physiological and behavioral differences between subsistence-level and modern Westernized populations, and by analyses of survival-reproduction trade-offs in nonhuman mammals. Studies of PCOS models using prenatally testosterone-treated and naturally hyperandrogenic animal models provide crucial insights for understanding how today's illnesses likely emerged from ancient developmental-metabolic strategies, and how knowledge about the evolutionary past can help guide current research and the development of more effective therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".