Dataset Information

Untargeted metabolomics reveals multiple metabolites influencing smoking-related DNA methylation.

ABSTRACT:

Aim

We conducted a joint metabolomic-epigenomic study to identify patterns of epigenetic associations with smoking-related metabolites.

Patients & methods

We performed an untargeted metabolome-wide association study of smoking and epigenome-wide association studies of smoking-related metabolites among 180 male twins. We examined the patterns of epigenetic association linked to smoking-related metabolites using hierarchical clustering.

Results

Among 12 annotated smoking-related metabolites identified from a metabolome-wide association study, we observed significant hypomethylation associated with increased level of N-acetylpyrrolidine, cotinine, 5-hydroxycotinine and nicotine and hypermethylation associated with increased level of 8-oxoguanine. Hierarchical clustering revealed common and unique epigenetic-metabolic associations related to smoking.

Conclusion

Our study suggested that a joint metabolome-epigenome approach can reveal additional details in molecular responses to the environmental exposure to understand disease risk.

SUBMITTER: Huang Y

PROVIDER: S-EPMC5925442 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Publications

Untargeted metabolomics reveals multiple metabolites influencing smoking-related DNA methylation.

Huang Yunfeng Y Hui Qin Q Walker Douglas I DI Uppal Karan K Goldberg Jack J Jones Dean P DP Vaccarino Viola V Sun Yan V YV

Epigenomics 20180312 4

<h4>Aim</h4>We conducted a joint metabolomic-epigenomic study to identify patterns of epigenetic associations with smoking-related metabolites.<h4>Patients & methods</h4>We performed an untargeted metabolome-wide association study of smoking and epigenome-wide association studies of smoking-related metabolites among 180 male twins. We examined the patterns of epigenetic association linked to smoking-related metabolites using hierarchical clustering.<h4>Results</h4>Among 12 annotated smoking-rela ...[more]

PMID: 29528243

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Project description:Epigenetic modifications, such as DNA methylation, influence gene expression and cardiometabolic phenotypes that are manifest in developmental periods in later life, including adolescence. Untargeted metabolomics analysis provide a comprehensive snapshot of physiological processes and metabolism and have been related to DNA methylation in adults, offering insights into the regulatory networks that influence cellular processes. We analyzed the cross-sectional correlation of blood leukocyte DNA methylation with 3758 serum metabolite features (574 of which are identifiable) in 238 children (ages 8-14 years) from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study. Associations between these features and percent DNA methylation in adolescent blood leukocytes at LINE-1 repetitive elements and genes that regulate early life growth (IGF2, H19, HSD11B2) were assessed by mixed effects models, adjusting for sex, age, and puberty status. After false discovery rate correction (FDR q < 0.05), 76 metabolites were significantly associated with LINE-1 DNA methylation, 27 with HSD11B2, 103 with H19, and 4 with IGF2. The ten identifiable metabolites included dicarboxylic fatty acids (five associated with LINE-1 or H19 methylation at q < 0.05) and 1-octadecanoyl-rac-glycerol (q < 0.0001 for association with H19 and q = 0.04 for association with LINE-1). We then assessed the association between these ten known metabolites and adiposity 3 years later. Two metabolites, dicarboxylic fatty acid 17:3 and 5-oxo-7-octenoic acid, were inversely associated with measures of adiposity (P < .05) assessed approximately 3 years later in adolescence. In stratified analyses, sex-specific and puberty-stage specific (Tanner stage = 2 to 5 vs Tanner stage = 1) associations were observed. Most notably, hundreds of statistically significant associations were observed between H19 and LINE-1 DNA methylation and metabolites among children who had initiated puberty. Understanding relationships between subclinical molecular biomarkers (DNA methylation and metabolites) may increase our understanding of genes and biological pathways contributing to metabolic changes that underlie the development of adiposity during adolescence.

Dataset Information

Untargeted metabolomics reveals multiple metabolites influencing smoking-related DNA methylation.

Aim

Patients & methods

Results

Conclusion

Publications

Untargeted metabolomics reveals multiple metabolites influencing smoking-related DNA methylation.

Similar Datasets

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