Dual effects of superovulation: loss of maternal and paternal imprinted methylation in a dose-dependent manner
Bibliographic record
Abstract
Superovulation or ovarian stimulation is currently an indispensable assisted reproductive technology (ART) for human subfertility/infertility treatment. Recently, increased frequencies of imprinting disorders have been correlated with ARTs. Significantly, for Angelman and Beckwith-Wiedemann Syndromes, patients have been identified where ovarian stimulation was the only procedure used by the couple undergoing ART. In many cases, increased risk of genomic imprinting disorders has been attributed to superovulation in combination with inherent subfertility. To distinguish between these contributing factors, carefully controlled experiments are required on spontaneously ovulated, in vivo-fertilized oocytes and their induced-ovulated counterparts, thereby minimizing effects of in vitro manipulations. To this end, effects of superovulation on genomic imprinting were evaluated in a mouse model, where subfertility is not a confounding issue. This work represents the first comprehensive examination of the overall effects of superovulation on imprinted DNA methylation for four imprinted genes in individual blastocyst stage embryos. We demonstrate that superovulation perturbed genomic imprinting of both maternally and paternally expressed genes; loss of Snrpn, Peg3 and Kcnq1ot1 and gain of H19 imprinted methylation were observed. This perturbation was dose-dependent, with aberrant imprinted methylation more frequent at the high hormone dosage. Superovulation is thought to primarily affect oocyte development; thus, effects were expected to be limited to maternal alleles. Our study revealed that maternal as well as paternal H19 methylation was perturbed by superovulation. We postulate that superovulation has dual effects during oogenesis, disrupting acquisition of imprints in growing oocytes, as well as maternal-effect gene products subsequently required for imprint maintenance during pre-implantation development.
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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 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".