» Articles » PMID: 28362264

Small-Magnitude Effect Sizes in Epigenetic End Points Are Important in Children's Environmental Health Studies: The Children's Environmental Health and Disease Prevention Research Center's Epigenetics Working Group

Abstract

Background: Characterization of the epigenome is a primary interest for children's environmental health researchers studying the environmental influences on human populations, particularly those studying the role of pregnancy and early-life exposures on later-in-life health outcomes.

Objectives: Our objective was to consider the state of the science in environmental epigenetics research and to focus on DNA methylation and the collective observations of many studies being conducted within the Children's Environmental Health and Disease Prevention Research Centers, as they relate to the Developmental Origins of Health and Disease (DOHaD) hypothesis.

Methods: We address the current laboratory and statistical tools available for epigenetic analyses, discuss methods for validation and interpretation of findings, particularly when magnitudes of effect are small, question the functional relevance of findings, and discuss the future for environmental epigenetics research.

Discussion: A common finding in environmental epigenetic studies is the small-magnitude epigenetic effect sizes that result from such exposures. Although it is reasonable and necessary that we question the relevance of such small effects, we present examples in which small effects persist and have been replicated across populations and across time. We encourage a critical discourse on the interpretation of such small changes and further research on their functional relevance for children's health.

Conclusion: The dynamic nature of the epigenome will require an emphasis on future longitudinal studies in which the epigenome is profiled over time, over changing environmental exposures, and over generations to better understand the multiple ways in which the epigenome may respond to environmental stimuli.

Citing Articles

Lifecourse research in cancer: context, challenges, and opportunities when exploring exposures in early life and cancer risk in adulthood.

Baker J, Gordon-Dseagu V, Voortman T, Chan D, Herceg Z, Robinson S Health Open Res. 2025; 6:16.

PMID: 39974286 PMC: 11836561. DOI: 10.12688/healthopenres.13748.2.


Associations of maternal night shift work during pregnancy with DNA methylation in offspring: a meta-analysis in the PACE consortium.

Marques I, Domenech-Panicello C, Geurtsen M, Hoang T, Richmond R, Polinski K Clin Epigenetics. 2025; 17(1):12.

PMID: 39844285 PMC: 11756212. DOI: 10.1186/s13148-024-01810-y.


Characterizing DNA Methylation and Hydroxymethylation in Cord Blood and Identifying Sex-Specific Differences using the Illumina EPIC Array.

Petroff R, Dolinoy D, Padmanabhan V, Goodrich J Epigenet Rep. 2024; 2(1):1-7.

PMID: 39610770 PMC: 11600988. DOI: 10.1080/28361512.2024.2427955.


War Exposure and DNA Methylation in Syrian Refugee Children and Adolescents.

Smeeth D, Ecker S, Chervova O, McEwen F, Karam E, Beck S JAMA Psychiatry. 2024; 82(2):191-200.

PMID: 39565630 PMC: 11579893. DOI: 10.1001/jamapsychiatry.2024.3714.


Association between maternal perinatal stress and depression and infant DNA methylation in the first year of life.

Abrishamcar S, Zhuang B, Thomas M, Gladish N, MacIsaac J, Jones M Transl Psychiatry. 2024; 14(1):445.

PMID: 39438450 PMC: 11496819. DOI: 10.1038/s41398-024-03148-8.


References
1.
Maeder M, Angstman J, Richardson M, Linder S, Cascio V, Tsai S . Targeted DNA demethylation and activation of endogenous genes using programmable TALE-TET1 fusion proteins. Nat Biotechnol. 2013; 31(12):1137-42. PMC: 3858462. DOI: 10.1038/nbt.2726. View

2.
Murphy S, Adigun A, Huang Z, Overcash F, Wang F, Jirtle R . Gender-specific methylation differences in relation to prenatal exposure to cigarette smoke. Gene. 2011; 494(1):36-43. PMC: 3627389. DOI: 10.1016/j.gene.2011.11.062. View

3.
Paquette A, Lester B, Lesseur C, Armstrong D, Guerin D, Appleton A . Placental epigenetic patterning of glucocorticoid response genes is associated with infant neurodevelopment. Epigenomics. 2015; 7(5):767-79. PMC: 4772971. DOI: 10.2217/epi.15.28. View

4.
Tuglus C, van der Laan M . Repeated measures semiparametric regression using targeted maximum likelihood methodology with application to transcription factor activity discovery. Stat Appl Genet Mol Biol. 2011; 10:Article 2. PMC: 3122882. DOI: 10.2202/1544-6115.1553. View

5.
Leek J, Johnson W, Parker H, Jaffe A, Storey J . The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012; 28(6):882-3. PMC: 3307112. DOI: 10.1093/bioinformatics/bts034. View