A methodological pipeline to generate an epigenetic marker of prenatal exposure to air pollution indicators

Ya Wang1,2, Frederica Perera1,3, Jia Guo1,2

  • 1Columbia Center for Children's Environmental Health, Mailman School of Public Health, Columbia University, New York, New York.

Epigenetics
|January 19, 2021
PubMed

Insights

Researchers developed a new method using DNA methylation in cord blood to predict prenatal exposure to air pollution, aiding early identification of children at risk for developmental disorders.

Area of Science:

  • Environmental Health
  • Epigenetics
  • Pediatrics

Background:

  • Lack of early-warning systems for childhood illness and developmental disorders.
  • Prenatal exposure to environmental toxins, like air pollution, is a known risk factor.
  • DNA methylation alterations are linked to environmental exposures.

Purpose of the Study:

  • Develop a methodology to identify biomarkers for early detection of risks from prenatal toxic exposures.
  • Utilize DNA methylation signatures in cord blood as predictors of prenatal air pollution exposure.
  • Establish a predictive model for identifying newborns at elevated risk.

Main Methods:

  • Developed a screening and three-part pipeline (selection, testing, validation) for DNA methylation analysis.
  • Measured DNA methylation signatures in umbilical cord blood from NYC birth cohorts.
  • Used air pollution indicators: nitrogen dioxide (NO2) and particulate matter (PM2.5) across pregnancy trimesters.

Main Results:

  • Cord blood DNA methylation successfully predicted high vs. low average pregnancy NO2 exposure (AUC=0.60).
  • Prediction accuracy was similar for high vs. low third-trimester NO2 exposure.
  • Validated the predictive capability of DNA methylation for prenatal air pollution exposure.

Conclusions:

  • DNA methylation in cord blood can serve as a predictor of prenatal exposure to air pollutants (NO2, PM2.5).
  • The developed analytic pipeline is generalizable for predicting prenatal exposure to various contaminants.
  • This approach holds potential for identifying children at risk of adverse health outcomes due to prenatal exposures.

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