DNA methylation changes in whole blood is associated with exposure to the environmental contaminants, mercury, lead, cadmium and bisphenol A, in women undergoing ovarian stimulation for IVF
Bibliographic record
Abstract
BACKGROUND: Changes in DNA methylation may play an important role in the deleterious reproductive effects reported in association with exposure to environmental pollutants. In this pilot study, we identify candidate methylation changes associated with exposure to pollutants in women undergoing in vitro fertilization (IVF). METHODS: Blood and urine were collected from women on the day of oocyte retrieval. Whole blood was analyzed for mercury and lead, and urine for cadmium using inductively coupled plasma mass spectrometry. Unconjugated bisphenol A (BPA) was analyzed in serum using high-performance liquid chromatography with Coularray detection. Participants were dichotomized as higher or lower exposure groups by median concentrations. Using the Illumina GoldenGate Methylation Cancer Panel I, DNA methylation in whole blood from 43 women was assessed at 1505 CpG sites for association with exposure levels of each pollutant. Candidate CpG sites were identified using a Diff Score >|13| (P< 0.05) and an absolute difference >10% which were confirmed using bisulfite pyrosequencing. RESULTS: Methylation of the GSTM1/5 promoter was increased for women with higher mercury exposure (P= 0.04); however, no correlation was observed (r= 0.17, P= 0.27). Reduced methylation was detected in the COL1A2 promoter in women with higher exposure to lead (P= 0.004), and an inverse correlation was observed (r = - 0.45, P= 0.03). Lower methylation of a promoter CpG site at the TSP50 gene was detected in women with higher BPA exposure (P= 0.005), and again an inverse correlation was identified (r = - 0.51, P= 0.001). CONCLUSIONS: Altered DNA methylation at various CpG sites was associated with exposure to mercury, lead or BPA, providing candidates to be investigated using a larger study sample, as the results may reflect an independently associated predictor (e.g. socioeconomic status, diet, genetic variants, altered blood cell composition). Further studies accommodating variations in these factors will be needed to confirm these associations and identify their underlying causes.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".