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
{"title":"来自ELEMENT队列的基因特异性DNA甲基化和非靶向代谢组学数据的综合分析。","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","doi":"10.1177/2516865720977888","DOIUrl":null,"url":null,"abstract":"<p><p>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 (<i>IGF2, H19, HSD11B2</i>) were assessed by mixed effects models, adjusting for sex, age, and puberty status. After false discovery rate correction (FDR <i>q</i> < 0.05), 76 metabolites were significantly associated with LINE-1 DNA methylation, 27 with <i>HSD11B2</i>, 103 with <i>H19</i>, and 4 with <i>IGF2</i>. The ten identifiable metabolites included dicarboxylic fatty acids (five associated with LINE-1 or <i>H19</i> methylation at <i>q</i> < 0.05) and 1-octadecanoyl-rac-glycerol (<i>q</i> < 0.0001 for association with <i>H19</i> and <i>q</i> = 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 (<i>P</i> < .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 <i>H19</i> 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.</p>","PeriodicalId":41996,"journal":{"name":"Epigenetics Insights","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/2516865720977888","citationCount":"3","resultStr":"{\"title\":\"Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort.\",\"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\",\"doi\":\"10.1177/2516865720977888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 (<i>IGF2, H19, HSD11B2</i>) were assessed by mixed effects models, adjusting for sex, age, and puberty status. After false discovery rate correction (FDR <i>q</i> < 0.05), 76 metabolites were significantly associated with LINE-1 DNA methylation, 27 with <i>HSD11B2</i>, 103 with <i>H19</i>, and 4 with <i>IGF2</i>. The ten identifiable metabolites included dicarboxylic fatty acids (five associated with LINE-1 or <i>H19</i> methylation at <i>q</i> < 0.05) and 1-octadecanoyl-rac-glycerol (<i>q</i> < 0.0001 for association with <i>H19</i> and <i>q</i> = 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 (<i>P</i> < .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 <i>H19</i> 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.</p>\",\"PeriodicalId\":41996,\"journal\":{\"name\":\"Epigenetics Insights\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/2516865720977888\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epigenetics Insights\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/2516865720977888\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epigenetics Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/2516865720977888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
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 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.