Prenatal Environmental Determinants of Aromatase Brain-Promoter Methylation in Cord Blood: Chemical, Airborne, Pharmacological, and Nutritional Factors
Bibliographic record
Abstract
Abstract Aromatase, an enzyme encoded by the gene CYP19A1, plays central roles in neurodevelopment. In the brain, its function is to convert androgens into neuroestrogens, ensuring balanced hormonal signalling. Both animal experiments and human studies have shown that, in males, disruption of aromatase, either genetically or epigenetically, can increase symptoms of autism. Prenatal exposure to bisphenol A (BPA), a common plastic chemical, can increase levels of DNA methylation—a key epigenetic modification—at the brain-specific CYP19A1 promoter, P1.f, reducing CYP19A1 expression. However, the extent to which other neurodevelopmentally relevant environmental exposures influence P1.f methylation remains unclear. Here, in the Barwon Infant Study (BIS) birth cohort (N = 906), we analysed the association between 25 prenatal exposures (from five classes previously linked to neurodevelopmental outcomes: manufactured chemicals, air pollution, and pharmacological, nutrition and sunlight-related factors) and methylation of the CYP19A1 P1.f promoter using Weighted Quantile Sum (WQS) regression. We found that the WQS mixture index, a weighted combination of the prenatal exposures, was positively associated with higher P1.f methylation (Adjusted Mean Difference (AMD) = 0.71 (95% CI 0.11, 1.32), P = 0.021), indicating reduced brain aromatase activity. Prenatal exposures with the strongest contribution to the mixture effect included bisphenols (including BPA), reduced sunlight, household mould, phthalates, low folate intake, and air pollution. These findings highlight epigenetic modification of the aromatase gene as a biologically plausible, convergent mechanism through which multiple environmental risk factors for autism may exert effects.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".