Placental DNA methylation and fetal and pregnancy complications
Bibliographic record
Abstract
Placental function is among the most important determinants of fetal and pregnancy outcomes. In recent years, the importance of epigenetic regulation for placental function has received increasing attention. The most widely studied epigenetic mechanism is DNA methylation. This thesis aims to present a review of the current literature on the association between placental DNA methylation and three fetal and pregnancy outcomes: preterm birth, intrauterine growth restriction/small-for-gestational-age/low birthweight, and miscarriage/perinatal death. The literature review was conducted by searching MEDLINE for original articles published between 2012 and 2022 on placental DNA methylation and either of the three fetal/pregnancy outcomes. The included studies were epigenome-wide association studies (EWAS) with a relevant control group. Methodological quality was assessed using the Newcastle-Ottawa Quality Assessment Scale for case-control studies. The review identified a total of 11 papers, all case-control studies: four on preterm birth, six on intrauterine growth restriction/small-for-gestational-age/low birthweight, and one on miscarriage. Number of differentially methylated positions identified ranged from 296 to 13 426. The identified differentially methylated genes were most commonly involved in fetal and organismal survival and development. The gene families ZNF, CDH and SLC were differentially methylated in three or more of the studies. Although the studies were difficult to compare directly due to methodological differences, the findings support a role for epigenetic modifications of the placenta in fetal and pregnancy outcomes. The reviewed studies represent early efforts to explore this association. Future research should combine larger-scale EWAS with other research designs to further our understanding of these complex interactions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".