期刊
ENVIRONMENTAL RESEARCH
卷 144, 期 -, 页码 139-148出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2015.11.014
关键词
Epigenetics; Prenatal smoking exposure; Childhood; DNA methylation; Biomarker
资金
- Autism Speaks
- Centers for Disease Control and Prevention: Colorado Department of Public Health and Environment [U10DD000180]
- Kaiser Foundation Research Institute (CA) [U10DD000181]
- University of Pennsylvania [U10DD000182]
- Johns Hopkins University [U10DDD000183]
- University of North Carolina at Chapel Hill [U10DD000184]
- Michigan State University [U10DD000498]
- Lundbeck Foundation [R155-2014-1724] Funding Source: researchfish
- CENTERS FOR DISEASE CONTROL AND PREVENTION [U10DD000182, U10DD000180, U10DD000183, U10DD000181, U01DD000498, U10DD000184] Funding Source: NIH RePORTER
- National Center on Birth Defects and Developmental Disabilities [U01DD001214] Funding Source: NIH RePORTER
Prenatal exposure to tobacco smoke has lifelong health consequences. Epigenetic signatures such as differences in DNA methylation (DNAm) may be a biomarker of exposure and, further, might have functional significance for how in utero tobacco exposure may influence disease risk. Differences in infant DNAm associated with maternal smoking during pregnancy have been identified. Here we assessed whether these infant DNAm patterns are detectible in early childhood, whether they are specific to smoking, and whether childhood DNAm can classify prenatal smoke exposure status. Using the lnfinium 450 K array, we measured methylation at 26 CpG loci that were previously associated with prenatal smoking in infant cord blood from 572 children, aged 3-5, with differing prenatal exposure to cigarette smoke in the Study to Explore Early Development (SEED). Striking concordance was found between the pattern of prenatal smoking associated DNAm among preschool aged children in SEED and those observed at birth in other studies. These DNAm changes appear to be tobacco-specific. Support vector machine classification models and 10-fold cross-validation were applied to show classification accuracy for childhood DNAm at these 26 sites as a biomarker of prenatal smoking exposure. Classification models showed prenatal exposure to smoking can be assigned with 81% accuracy using childhood DNAm patterns at these 26 loci. These findings support the potential for blood-derived DNAm measurements to serve as biomarkers for prenatal exposure. (C) 2015 Elsevier Inc. All rights reserved.
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