An epigenetic pathway approach to investigating associations between prenatal exposure to maternal mood disorder and newborn neurobehavior
Bibliographic record
Abstract
Following recent advances in behavioral and psychiatric epigenetics, researchers are increasingly using epigenetic methods to study prenatal exposure to maternal mood disorder and its effects on fetal and newborn neurobehavior. Despite notable progress, various methodological limitations continue to obscure our understanding of the epigenetic mechanisms underpinning prenatal exposure to maternal mood disorder on newborn neurobehavioral development. Here we detail this problem, discussing limitations of the currently dominant analytical approaches (i.e., candidate epigenetic and epigenome-wide association studies), then present a solution that retains many benefits of existing methods while minimizing their shortcomings: epigenetic pathway analysis. We argue that the application of pathway-based epigenetic approaches that target DNA methylation at transcription factor binding sites could substantially deepen our mechanistic understanding of how prenatal exposures influence newborn neurobehavior.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".