Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort

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...

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Main Authors: Jaclyn M Goodrich, Emily C Hector, Lu Tang, Jennifer L LaBarre, Dana C Dolinoy, Adriana Mercado-Garcia, Alejandra Cantoral, Peter XK Song, Martha Maria Téllez-Rojo, Karen E Peterson
Format: Article
Language:English
Published: SAGE Publishing 2020-12-01
Series:Epigenetics Insights
Online Access:https://doi.org/10.1177/2516865720977888
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spelling doaj-9ed20cb87bcf4521bc45936d9fa7e5e12020-12-11T00:03:21ZengSAGE PublishingEpigenetics Insights2516-86572020-12-011310.1177/2516865720977888Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT CohortJaclyn M Goodrich0Emily C Hector1Lu Tang2Jennifer L LaBarre3Dana C Dolinoy4Adriana Mercado-Garcia5Alejandra Cantoral6Peter XK Song7Martha Maria Téllez-Rojo8Karen E Peterson9Deptartment of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USADeptartment of Statistics, North Carolina State University, USADeptartment of Biostatistics, University of Pittsburgh, USADeptartment of Nutritional Sciences, University of Michigan, Ann Arbor, MI, USADeptartment of Nutritional Sciences, University of Michigan, Ann Arbor, MI, USACenter for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, MéxicoCenter for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, MéxicoDeptartment of Biostatistics, University of Michigan, Ann Arbor, MI, USACenter for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, MéxicoDeptartment of Nutritional Sciences, University of Michigan, Ann Arbor, MI, USAEpigenetic 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.https://doi.org/10.1177/2516865720977888
collection DOAJ
language English
format Article
sources DOAJ
author Jaclyn M Goodrich
Emily C Hector
Lu Tang
Jennifer L LaBarre
Dana C Dolinoy
Adriana Mercado-Garcia
Alejandra Cantoral
Peter XK Song
Martha Maria Téllez-Rojo
Karen E Peterson
spellingShingle Jaclyn M Goodrich
Emily C Hector
Lu Tang
Jennifer L LaBarre
Dana C Dolinoy
Adriana Mercado-Garcia
Alejandra Cantoral
Peter XK Song
Martha Maria Téllez-Rojo
Karen E Peterson
Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort
Epigenetics Insights
author_facet Jaclyn M Goodrich
Emily C Hector
Lu Tang
Jennifer L LaBarre
Dana C Dolinoy
Adriana Mercado-Garcia
Alejandra Cantoral
Peter XK Song
Martha Maria Téllez-Rojo
Karen E Peterson
author_sort Jaclyn M Goodrich
title Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort
title_short Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort
title_full Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort
title_fullStr Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort
title_full_unstemmed Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort
title_sort integrative analysis of gene-specific dna methylation and untargeted metabolomics data from the element cohort
publisher SAGE Publishing
series Epigenetics Insights
issn 2516-8657
publishDate 2020-12-01
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.
url https://doi.org/10.1177/2516865720977888
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