DNA methylation differences associated with prenatal air pollution exposure in developmentally relevant tissues from two North American birth cohorts
Bibliographic record
Abstract
Prenatal air pollutant exposures are linked to childhood atopic diseases like wheeze and asthma. The molecular mechanisms are not fully understood, but likely involve lasting changes to epigenetic marks, such as DNA methylation (DNAm). Newborn cord blood and placenta DNAm differences have been demonstrated, but few studies interrogated their role in health outcomes. Additionally, these investigations primarily involved participants of European descent, limiting broader applicability. This thesis addresses these gaps using microarray data and an epigenome wide approach to profile cord blood and placenta DNAm differences associated with air pollutant exposures (NO2, PM2.5, and PM10) in two diverse North American cohorts. This work identified novel differentially methylated regions (DMRs) in both tissues and replicated previous findings in cohorts from similar backgrounds. Notably, a DMR in the lung development gene HOXA5 was observed in both cohorts, with DNAm differences likely driven by changes in biological males. Most DMRs were tissue-specific, reflecting the distinct roles of cord blood and placenta in development and disease, with minimal overlap between pollutants, suggesting unique mechanistic effects. Causal mediation analysis highlighted trends for cord blood DMRs in the association between PM2.5 exposure and transient wheeze, and placental DMRs in persistent wheeze with PM2.5, indicating different roles for these tissues in respiratory health. Additionally, this thesis examined the persistence of DNAm changes, finding that most cord blood DMRs associated with prenatal NO2 exposure remained significant at age one, implying greater potential to impact later health. This work also introduced a novel subtractive method leveraging repeated DNAm measures to identify a postnatal-specific DMR related to NO2 in the first year of life, reinforcing the susceptibility of early developmental stages to environmental factors. Finally, given that air pollution likely exerts its effects through oxidative stress and inflammation, this thesis examined buffering by maternal diets, observing reductions in the magnitude of cord blood and placenta DMRs with greater intake of protective foods like fruits and vegetables. Together, this work provides new insight into the molecular mechanisms connecting prenatal air pollution with respiratory health, highlights the need for diversity, and showcases maternal diet quality as a potential buffer against the effects of prenatal pollution.
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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) | 0.001 | 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".