Association of Gene Polymorphisms with Polycystic Ovary Syndrome: A Meta-analysis
Bibliographic record
Abstract
Objectives: Polycystic ovary syndrome (PCOS) is a prevalent endocrine-metabolic disorder affecting reproductive-aged women. Genetic factors play a significant role in its development. This meta-analysis assesses the associations between specific gene polymorphisms (Vitamin D receptor [VDR] and adiponectin [ADIPOQ]) and PCOS susceptibility. Materials and Methods: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, Collecting data from published articles between 2013 to 2013. Eligible studies were selected based on inclusion and exclusion criteria, with quality assessment performed using the Newcastle–Ottawa scale. Data were extracted, and statistical analyses included odds ratios with 95% confidence intervals for gene polymorphisms. Heterogeneity was evaluated using I 2 tests, and publication bias was assessed using Begg’s and Egger’s tests. Results: A total of 33 articles involving 5677 cases and 5257 controls were included in the analysis. Significant associations were observed for VDR TaqI rs731236 polymorphism in the dominant and recessive models and VDR BsmI rs1544410 polymorphism in the dominant and recessive models. For ADIPOQ T45G rs2241766, a significant association was found in the heterozygous model. The results did not reveal any significant associations for ADIPOQ G276T rs1501299. Conclusion: This meta-analysis suggests associations between specific gene polymorphisms (VDR and ADIPOQ) and PCOS susceptibility. Further research is needed to validate these findings and unravel the complex genetic factors contributing to PCOS, potentially leading to improved diagnostic and therapeutic strategies.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.047 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".