Quality control and statistical modeling for environmental epigenetics: A study on<i>in utero</i>lead exposure and DNA methylation at birth
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Bibliographic record
Abstract
DNA methylation data assayed using pyrosequencing techniques are increasingly being used in human cohort studies to investigate associations between epigenetic modifications at candidate genes and exposures to environmental toxicants and to examine environmentally-induced epigenetic alterations as a mechanism underlying observed toxicant-health outcome associations. For instance, in utero lead (Pb) exposure is a neurodevelopmental toxicant of global concern that has also been linked to altered growth in human epidemiological cohorts; a potential mechanism of this association is through alteration of DNA methylation (e.g., at growth-related genes). However, because the associations between toxicants and DNA methylation might be weak, using appropriate quality control and statistical methods is important to increase reliability and power of such studies. Using a simulation study, we compared potential approaches to estimate toxicant-DNA methylation associations that varied by how methylation data were analyzed (repeated measures vs. averaging all CpG sites) and by method to adjust for batch effects (batch controls vs. random effects). We demonstrate that correcting for batch effects using plate controls yields unbiased associations, and that explicitly modeling the CpG site-specific variances and correlations among CpG sites increases statistical power. Using the recommended approaches, we examined the association between DNA methylation (in LINE-1 and growth related genes IGF2, H19 and HSD11B2) and 3 biomarkers of Pb exposure (Pb concentrations in umbilical cord blood, maternal tibia, and maternal patella), among mother-infant pairs of the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) cohort (n = 247). Those with 10 μg/g higher patella Pb had, on average, 0.61% higher IGF2 methylation (P = 0.05). Sex-specific trends between Pb and DNA methylation (P < 0.1) were observed among girls including a 0.23% increase in HSD11B2 methylation with 10 μg/g higher patella Pb.
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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 it