Targeted genome-wide DNA methylation profiling of ovarian granulosa cells from women with PCOS
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is a complex endocrinopathy of obscure pathophysiologic origins, globally affecting 6-15% women of childbearing age. Emerging evidence on repercussions of environmental insults and changing lifestyles on fecundity and reproductive health have necessitated the study of tissue-specific epigenetic alterations in PCOS development. In semblance to follicular and oocyte defects observed in PCOS ovaries, targeted bisulfite sequencing was performed to generate the methylome signatures of ovarian granulosa cells (GCs) obtained from age-BMI matched women with PCOS (n=3) and healthy, regularly menstruating controls (n=3) using next generation sequencing approach. Paired end sequencing of samples was carried out on Illumina HiSeq 2500 platform and data were analyzed using the Bismark tool. Methylation levels of a few selected genes relevant to ovarian function were further validated in GCs obtained from 10 controls and 10 women with PCOS by pyrosequencing. Relative transcript levels of these genes were assessed by q-RT PCR using Taqman assays. In the methylome analysis, a total of 6486 CpG sites representing 3840 genes associated with pathways such as Wnt signaling, G-protein receptor signaling, angiogenesis, chemokine and cytokine mediated inflammation and integrin signaling showed differential methylation in PCOS. Of these, a total of 2977 CpG sites representing 2063 genes were identified as hypomethylated while 3509 CpG sites in 1777 genes were found to be hypermethylated. Additionally, differential methylation was also noted in several non-coding RNAs regulating vital ovarian functions and which are reported to be dysregulated in PCOS. This data provides compelling evidence in support of epigenetic alterations as etiopathogenic factors associated with ovarian dysfunction in PCOS.
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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 | 0.001 |
| 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".