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The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers

BACKGROUND: DNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI or predictive of future BMI. Here, we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometa...

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Autores principales: Reed, Zoe E., Suderman, Matthew J., Relton, Caroline L., Davis, Oliver S. P., Hemani, Gibran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106582/
https://www.ncbi.nlm.nih.gov/pubmed/32228717
http://dx.doi.org/10.1186/s13148-020-00841-5
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author Reed, Zoe E.
Suderman, Matthew J.
Relton, Caroline L.
Davis, Oliver S. P.
Hemani, Gibran
author_facet Reed, Zoe E.
Suderman, Matthew J.
Relton, Caroline L.
Davis, Oliver S. P.
Hemani, Gibran
author_sort Reed, Zoe E.
collection PubMed
description BACKGROUND: DNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI or predictive of future BMI. Here, we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometabolic traits. METHODS: Analyses were conducted across the life course using the ARIES cohort of mothers (n = 792) and children (n = 906), for whom DNA methylation and genetic profiles and BMI at multiple time points (3 in children at birth, in childhood and in adolescence; 2 in mothers during pregnancy and in middle age) were available. Genetic and DNA methylation scores for BMI were derived using published associations between BMI and DNA methylation and genotype. Causal relationships between methylation and BMI were assessed using Mendelian randomisation and cross-lagged models. RESULTS: The DNA methylation scores in adult women explained 10% of extant BMI variance. However, less extant variance was explained by scores generated in the same women during pregnancy (2% BMI variance) and in older children (15–17 years; 3% BMI variance). Similarly, little extant variance was explained in younger children (at birth and at 7 years; 1% and 2%, respectively). These associations remained following adjustment for smoking exposure and education levels. The DNA methylation score was found to be a poor predictor of future BMI using linear and cross-lagged models, suggesting that DNA methylation variation does not cause later variation in BMI. However, there was some evidence to suggest that BMI is predictive of later DNA methylation. Mendelian randomisation analyses also support this direction of effect, although evidence is weak. Finally, we find that DNA methylation scores for BMI are associated with extant cardiometabolic traits independently of BMI and genetic score. CONCLUSION: The age-specific nature of DNA methylation associations with BMI, lack of causal relationship and limited predictive ability of future BMI indicate that DNA methylation is likely influenced by BMI and might more accurately be considered a biomarker of BMI and related outcomes rather than a predictor. Future epigenome-wide association studies may benefit from further examining associations between early DNA methylation and later health outcomes.
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spelling pubmed-71065822020-04-01 The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers Reed, Zoe E. Suderman, Matthew J. Relton, Caroline L. Davis, Oliver S. P. Hemani, Gibran Clin Epigenetics Research BACKGROUND: DNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI or predictive of future BMI. Here, we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometabolic traits. METHODS: Analyses were conducted across the life course using the ARIES cohort of mothers (n = 792) and children (n = 906), for whom DNA methylation and genetic profiles and BMI at multiple time points (3 in children at birth, in childhood and in adolescence; 2 in mothers during pregnancy and in middle age) were available. Genetic and DNA methylation scores for BMI were derived using published associations between BMI and DNA methylation and genotype. Causal relationships between methylation and BMI were assessed using Mendelian randomisation and cross-lagged models. RESULTS: The DNA methylation scores in adult women explained 10% of extant BMI variance. However, less extant variance was explained by scores generated in the same women during pregnancy (2% BMI variance) and in older children (15–17 years; 3% BMI variance). Similarly, little extant variance was explained in younger children (at birth and at 7 years; 1% and 2%, respectively). These associations remained following adjustment for smoking exposure and education levels. The DNA methylation score was found to be a poor predictor of future BMI using linear and cross-lagged models, suggesting that DNA methylation variation does not cause later variation in BMI. However, there was some evidence to suggest that BMI is predictive of later DNA methylation. Mendelian randomisation analyses also support this direction of effect, although evidence is weak. Finally, we find that DNA methylation scores for BMI are associated with extant cardiometabolic traits independently of BMI and genetic score. CONCLUSION: The age-specific nature of DNA methylation associations with BMI, lack of causal relationship and limited predictive ability of future BMI indicate that DNA methylation is likely influenced by BMI and might more accurately be considered a biomarker of BMI and related outcomes rather than a predictor. Future epigenome-wide association studies may benefit from further examining associations between early DNA methylation and later health outcomes. BioMed Central 2020-03-30 /pmc/articles/PMC7106582/ /pubmed/32228717 http://dx.doi.org/10.1186/s13148-020-00841-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Reed, Zoe E.
Suderman, Matthew J.
Relton, Caroline L.
Davis, Oliver S. P.
Hemani, Gibran
The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers
title The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers
title_full The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers
title_fullStr The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers
title_full_unstemmed The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers
title_short The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers
title_sort association of dna methylation with body mass index: distinguishing between predictors and biomarkers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106582/
https://www.ncbi.nlm.nih.gov/pubmed/32228717
http://dx.doi.org/10.1186/s13148-020-00841-5
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