Polymorphisms in FSHR modulating susceptibility to polycystic ovary syndrome: an updated meta-analysis
Bibliographic record
Abstract
BACKGROUND: Two polymorphisms, rs6165 and rs6166 located in the intracellular domain of FSHR has been reported to affect folliculogenesis, steroidogenesis and oocyte maturation. Several studies have highlighted the role of FSHR polymorphisms in PCOS but the findings are conflicting. A meta-analysis was carried out to decipher the emerging perspectives. METHODOLOGY: A comprehensive literature search was made using PubMed, PCOSkb, and Google Scholar. New Ottawa Scale has been utilized to evaluate the quality of each article. To evaluate the strength of association under different genetic models of rs6165 and rs6166 polymorphisms, odds ratio with a 95% confidence interval (CI) was calculated. RESULTS: A total of 20 articles were selected for the present study. In pooled analysis and after the stratification by ethnicity, polymorphism rs6165 remains unrelated to the onset of PCOS. Besides, rs6166 exhibits significant protection in the Indian population under recessive, additive, and allele models (OR = 0.7, CI: 0.54-0.9, p = 0.006, OR = 0.65, CI: 0.48-0.89, p = 0.006, OR = 0.82, CI: 0.7-0.95, p = 0.01, respectively) and low to moderate risk in the Caucasian population under allele model (OR = 1.17, CI: 1.04-1.32, p = 0.01). CONCLUSION: This meta-analysis suggests that GG genotype of rs6166 provides protection against PCOS, in a population-specific manner.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.026 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".