Dataset Information

Epigenome-wide association study of total serum immunoglobulin E in children: a life course approach.

ABSTRACT: Background:IgE-mediated sensitization may be epigenetically programmed in utero, but early childhood environment may further alter complex traits and disease phenotypes through epigenetic plasticity. However, the epigenomic footprint underpinning IgE-mediated type-I hypersensitivity has not been well-understood, especially under a longitudinal early-childhood life-course framework. Methods:We used epigenome-wide DNA methylation (IlluminaHumanMethylation450 BeadChip) in cord blood and mid-childhood peripheral blood to investigate pre- and post-natal methylation marks associated with mid-childhood (age 6.7-10.2) total serum IgE levels in 217 mother-child pairs in Project Viva-a prospective longitudinal pre-birth cohort in eastern Massachusetts, USA. We identified methylation sites associated with IgE using covariate-adjusted robust linear regressions. Results:Nineteen methylation marks in cord blood were associated with IgE in mid-childhood (FDR

SUBMITTER: Peng C

PROVIDER: S-EPMC5905182 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Epigenome-wide association study of total serum immunoglobulin E in children: a life course approach.

Peng Cheng C Cardenas Andres A Rifas-Shiman Sheryl L SL Hivert Marie-France MF Gold Diane R DR Platts-Mills Thomas A TA Lin Xihong X Oken Emily E Baccarelli Andrea A AA Litonjua Augusto A AA DeMeo Dawn L DL

Clinical epigenetics 20180417

<h4>Background</h4>IgE-mediated sensitization may be epigenetically programmed in utero, but early childhood environment may further alter complex traits and disease phenotypes through epigenetic plasticity. However, the epigenomic footprint underpinning IgE-mediated type-I hypersensitivity has not been well-understood, especially under a longitudinal early-childhood life-course framework.<h4>Methods</h4>We used epigenome-wide DNA methylation (IlluminaHumanMethylation450 BeadChip) in cord blood ...[more]

PMID: 29692868

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Project description:BackgroundIn DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both.ResultsWe present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results.ConclusionsThe usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.

Dataset Information

Epigenome-wide association study of total serum immunoglobulin E in children: a life course approach.

Publications

Epigenome-wide association study of total serum immunoglobulin E in children: a life course approach.

Similar Datasets

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