EPIGENETIC ALTERATIONS ASSOCIATED WITH PREMATURE OVARIAN FAILURE
Bibliographic record
Abstract
Background/Purpose: Premature ovarian failure (POF) affects 1% of women with a largely idiopathic and poorly understood etiology. The objective of this study was to identify specific epigenetic alterations by measuring DNA methylation of gene regulatory regions in women with POF vs. controls. Methods: Blood samples were collected from idiopathic POFpatients (Amenorrhea for at least 3 months and 2 serum FSH levels of > 40mIU/ml obtained > 1 month apart prior to age 40) and control women (CW) (healthy pregnancy after age 37 with out a pregnancy loss). Genomic DNA was extracted from EDTA anticoagulated blood and bisulfite converted for analysis using the Illumina Golden Gate Methylation Panel which measures DNA methylation at 1506 CpG sites in the promoter regions of 807 genes in 10 POF and 12 CW. Candidate genes with altered epigenetic marks between POF and CW at a nominal P-value < 0.05 were identified using a t-testcomparison within the Illumina bead studio software. Genes of interest were further analyzed for quantitative methylation at specific CpG sites using pyrosequencing in 30 POF and 30 CW. Results: Comparison of DNA methylation profiles of our initial POF and CW groups identified several genes with statistically significanthyper- or hypo- methylation in the POF group (P < 0.05), including the Androgen Receptor (AR)promoter region, which was significantly hypermethylated. To further validate these results, DNA methylation of the AR gene promoter was quantified bypryosequencing in a larger group of POF and CW. Pyrosequencing further confirmed a significantly higher DNA methylation of the AR promoter region inPOF vs. CW (P=0.007). Conclusions: This is a novel study identifying epigenetic alterations in POF. The hypermethylation of the AR gene in POF patients may cause decreased level of the AR in these women. This is especially interesting given a recent report of induced POF in AR deficient mice^1. Specific epigenetic markers, as identified by DNA methylation array profiling in blood, may serve as useful biomarkers for POF and other fertility disorders. However, it will need to be determined if these methylation changes are present prior to diagnosis, or are a consequence of menopause itself. Reference: 1.Hiroko S. et al. Premature ovarian failure in androgenreceptor deficient mice. PNAS;103:224-9
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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) | 0.002 | 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".