Capturing sex-specific and hypofertility-linked effects of assisted reproductive technologies on the cord blood DNA methylome
Bibliographic record
Abstract
BACKGROUND: Children conceived through assisted reproduction are at an increased risk for growth and genomic imprinting disorders, often linked to DNA methylation defects. It has been suggested that assisted reproductive technology (ART) and underlying parental infertility can induce epigenetic instability, specifically interfering with DNA methylation reprogramming events during germ cell and preimplantation development. To date, human studies exploring the association between ART and DNA methylation defects have reported inconsistent or inconclusive results, likely due to population heterogeneity and the use of technologies with limited coverage of the epigenome. In our study, we explored the epigenetic risk of ART by comprehensively profiling the DNA methylome of 73 human cord blood samples of singleton pregnancies (n = 36 control group, n = 37 ART/hypofertile group) from a human prospective longitudinal birth cohort, the 3D (Design, Develop, Discover) Study, using a high-resolution sequencing-based custom capture panel that examines over 2.4 million autosomal CpGs in the genome. RESULTS: We identified evidence of sex-specific effects of ART/hypofertility on cord blood DNA methylation patterns. Our genome-wide analyses identified ~ 46% more CpGs affected by ART/hypofertility in female than in male infant cord blood. We performed a detailed analysis of three imprinted genes which have been associated with altered DNA methylation following ART (KCNQ1OT1, H19/IGF2 and GNAS) and found that female infant cord blood was associated with DNA hypomethylation. When compared to less invasive procedures such as intrauterine insemination, more invasive ARTs (in vitro fertilization, intracytoplasmic sperm injection, embryo culture) resulted in more marked and distinct effects on the cord blood DNA methylome. In the in vitro group, we found a close to fourfold higher proportion of significantly enriched Gene Ontology terms involved in development than in the in vivo group. CONCLUSIONS: Our study highlights the ability of a sensitive, targeted, sequencing-based approach to uncover DNA methylation perturbations in cord blood associated with hypofertility and ART and influenced by offspring sex and ART technique invasiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".