Longitudinal analysis of DNA methylation in relation to gestational perfluoroalkyl substance exposure: An epigenome-wide association study
Bibliographic record
Abstract
BACKGROUND AND AIM: Alterations to DNA methylation may underlie the association between gestational exposure to perfluoroalkyl substances (PFAS) and adverse health outcomes in children. However, few studies have examined the association between gestational PFAS exposure and DNA methylation, and no studies have repeated DNA methylation data across childhood. We examined associations between gestational PFAS exposure and repeated measures of offspring peripheral leukocyte DNA methylation among 266 mother-child pairs enrolled in the HOME Study (Cincinnati, OH). METHODS: We quantified serum concentrations of perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), perfluorononanoate (PFNA), and perfluorohexane sulfonate (PFHxS) in mothers at ~16 weeks gestation. We measured DNA methylation at delivery (cord blood) and age 12 years using the Illumina HumanMethylation EPIC BeadChip. We analyzed the associations between log2-transformed PFAS concentrations and repeated DNA methylation measures using generalized estimating equations. Visit by PFAS interaction terms were used to test the stability of these differences across time. We performed Gene Ontology (GO) enrichment analysis to identify significant biological pathways. RESULTS:A total of 35 loci were significantly associated with PFAS (false discovery rate, q 0.05). Among the 5 loci for PFOS, 10 for PFOA, 7 for PFHxS, and 13 for PFNA (q 0.01), none overlapped. These loci mapped to genes (e.g., AGAP1, HPSE2, HABP2, RNF13, RADIL, and TMEM56) that are associated with cancers, cardiovascular disease, and cognitive function. We found little evidence that associations between PFAS and DNA methylation changed over time. The most significant GO pathways included homophilic cell adhesion, cell-cell adhesion and integral component of plasma membrane. CONCLUSIONS:Using longitudinal data, we identified loci associated with PFAS that have not been reported. Several loci were in genes linked to PFAS-associated health outcomes. Future studies are needed to confirm our findings and examine whether DNA methylation mediates associations between gestational PFAS exposure and offspring health. KEYWORDS: PFAS, Epigenomics, Biomarkers of exposure, Environmental epidemiology
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".