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- W2913403141 abstract "This review demonstrates the growing body of evidence connecting DNA methylation to prior exposure. It highlights the potential to use DNA methylation patterns as a feasible, stable, and accurate biomarker of past exposure, opening new opportunities for environmental and gene-environment interaction studies among existing banked samples.We present the evidence for association between past exposure, including prenatal exposures, and DNA methylation measured at a later time in the life course. We demonstrate the potential utility of DNA methylation-based biomarkers of past exposure using results from multiple studies of smoking as an example. Multiple studies show the ability to accurately predict prenatal smoking exposure based on DNA methylation measured at birth, in childhood, and even adulthood. Separate sets of DNA methylation loci have been used to predict past personal smoking exposure (postnatal) as well. Further, it appears that these two types of exposures, prenatal and previous personal exposure, can be isolated from each other. There is also a suggestion that quantitative methylation scores may be useful for estimating dose. We highlight the remaining needs for rigor in methylation biomarker development including analytic challenges as well as the need for development across multiple developmental windows, multiple tissue types, and multiple ancestries.If fully developed, DNA methylation-based biomarkers can dramatically shift our ability to carry out environmental and genetic-environmental epidemiology using existing biobanks, opening up unprecedented opportunities for environmental health." @default.
- W2913403141 created "2019-02-21" @default.
- W2913403141 creator A5002407483 @default.
- W2913403141 creator A5026159095 @default.
- W2913403141 date "2019-02-01" @default.
- W2913403141 modified "2023-10-14" @default.
- W2913403141 title "DNA Methylation Signatures as Biomarkers of Prior Environmental Exposures" @default.
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- W2913403141 doi "https://doi.org/10.1007/s40471-019-0178-z" @default.
- W2913403141 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6481677" @default.
- W2913403141 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31032172" @default.
- W2913403141 hasPublicationYear "2019" @default.
- W2913403141 type Work @default.