Association of APOE Gene Variants with Cognitive Dysfunction in Polycystic Ovary Syndrome
Bibliographic record
Abstract
Objective: To investigate the relationship between APOE polymorphisms and cognitive function in PCOS women and identify potential genetic biomarkers for cognitive risk stratification. Methods and Materials: This cross-sectional study included 120 women with PCOS. Hormonal profiling (FSH, LH, total and free testosterone), metabolic parameters (insulin, HbA1c, HOMA-IR), and cognitive assessment using Montreal Cognitive Assessment (MoCA) were performed. APOE gene polymorphisms were analyzed to determine epsilon genotypes. Statistical analyses were performed by using SPSS software version 25.0 (SPSS, Chicago). Continuous data were presented as mean and standard deviation, and analyzed with Student t-test. Categorical variables were expressed as number and percentage and analyzed with Chi-square test. Binary logistic regression was used to determine the association between APOE gene polymorphism and cognitive impairment. Findings: PCOS patients with cognitive impairment were older with lower educational levels, demonstrating significantly higher testosterone, insulin levels, and HOMA-IR values. MoCA cognitive domains showed significant impairment. APOE epsilon genotype analysis revealed significant associations with cognitive status (p=0.022). The ε3ε3 genotype was more prevalent in cognitively intact PCOS, while ε2ε3 and ε3ε4 genotypes were significantly more frequent in cognitively impaired PCOS (p=0.030 and p=0.040, respectively). ε2ε3 carriers had 3.61-fold increased odds of cognitive impairment (95% CI: 1.14-11.5), while ε3ε4 carriers had 3.05-fold increased risk (95% CI: 1.05-8.81) compared to ε3ε3 carriers. Conclusion: This study demonstrates significant associations between APOE polymorphisms and cognitive function in PCOS patients. Both ε2ε3 and ε3ε4 genotypes confer increased cognitive impairment risk, while ε3ε3 appears protective. APOE genotyping could serve as a valuable tool for cognitive risk stratification in PCOS management after further validation.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".