A methodological pipeline to generate an epigenetic marker of prenatal exposure to air pollution indicators. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Wang, Ya; Perera, Frederica; Guo, Jia; Riley, Kylie W.; Durham, Teresa; Ross, Zev; Ananth, Cande V.; Baccarelli, Andrea; Wang, Shuang; Herbstman, Julie B.
• Is Part Of: Epigenetics. Volume 17:Issue 1(2022)
• Page Start: 32
• Page End: 40
• Publication Date: 2022-01-02
• Subjects: environmental health -- epidemiology -- air pollution -- prenatal period -- PM2.5; Epigenesis -- Periodicals; Epigenetica; 572.86505
• DOI: 10.1080/15592294.2021.1872926
• Languages: English
• ISSNs: 1559-2294

Abstract

ABSTRACT: A barrier in the children's environmental health field has been the lack of early-warning systems to identify risks of childhood illness and developmental disorders. We aimed to develop a methodology to identify an accessible biomarker measured in a small amount of blood to distinguish newborns at elevated risk from a toxic prenatal exposure, using air pollutants as a case study. Because air pollutants are associated with altered DNA methylation, we developed a pipeline using DNA methylation signatures measured in umbilical cord blood, which could be used as predictors of prenatal exposure. We used air pollution indicators, including modelled trimester-specific and pregnancy average NO2 and PM2.5, and DNA methylation signatures from Illumina arrays measured in two New York City-based longitudinal birth cohorts from the Columbia Centre for Children's Environmental Health. We developed a screening plus three-part pipeline that incorporates selection, testing, and validation to identify whether DNA methylation can be used to predict exposure to prenatal air pollution indicators, NO2 and PM2.5 . Applying this pipeline, we found that cord blood DNA methylation could be used to predict high vs. low average pregnancy NO2 (AUC = 0.60, 95% CI: 0.52–0.68, with validation AUC = 0.60). Similar results were found for high vs. low third trimester NO2 . In this proof of concept study using air pollutants as an example, we provide an approach (with a generalizable analytic pipeline) that can be used for prediction of prenatal exposure to contaminants. This approach has potential to identify children at risk of developmental disorders and illness resulting from prenatal exposure.