Genome-Wide DNA Methylation Profiles of Neurodevelopmental Disorder Genes in Mouse Placenta and Fetal Brain Following Prenatal Exposure to Polychlorinated Biphenyls
Bibliographic record
Abstract
Abstract Background Polychlorinated biphenyls (PCBs) are developmental neurotoxicants implicated as environmental risk factors for neurodevelopmental disorders (NDD), including autism spectrum disorders (ASD). Objective We examined the effects of prenatal exposure to a human-relevant mixture of PCBs on the DNA methylome of fetal mouse brain and placenta to determine if there was a shared subset of differentially methylated regions (DMRs). Methods A PCB mixture formulated to model the 12 most abundant congeners detected in the serum of pregnant women from a prospective high-risk ASD cohort was administered to female mice prior to and during pregnancy. Whole-genome bisulfite sequencing (WGBS) was performed to assess genome-wide DNA methylation profiles of placenta and brain on gestational day 18. Results We found thousands of significant (empirical p < 0.05) DMRs distinguishing placentas and brains from PCB-exposed embryos from sex-matched vehicle controls. In both placenta and brain, PCB-associated DMRs were significantly ( p < 0.005) enriched for functions related to neurodevelopment, cellular adhesion, and cellular signaling, and significantly (Odds Ratio > 2.4, q < 0.003) enriched for bivalent chromatin marks. The placenta and brain PCB DMRs overlapped significantly (Z-score = 4.5, p = 0.0001) by genomic coordinate and mapped to a shared subset of genes significantly ( q < 0.05) enriched for Wnt signaling, Slit/Robo signaling, and genes differentially expressed in multiple NDD/ASD models. The placenta and brain DMRs also significantly ( q < 0.05) overlapped by genomic coordinate with brain samples from humans with Rett syndrome and Dup15q syndrome. Discussion These results demonstrate that placenta can be used as a surrogate for embryonic brain DNA methylation changes over genes relevant to NDD/ASD in a mouse model of prenatal PCB exposure.
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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 | 0.001 | 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) | 0.001 | 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".