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Capturing functional epigenomes for insight into metabolic diseases

BACKGROUND: Metabolic diseases such as obesity are known to be driven by both environmental and genetic factors. Although genome-wide association studies of common variants and their impact on complex traits have provided some biological insight into disease etiology, identified genetic variants hav...

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Detalles Bibliográficos
Autores principales: Allum, Fiona, Grundberg, Elin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300388/
https://www.ncbi.nlm.nih.gov/pubmed/32199819
http://dx.doi.org/10.1016/j.molmet.2019.12.016
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author Allum, Fiona
Grundberg, Elin
author_facet Allum, Fiona
Grundberg, Elin
author_sort Allum, Fiona
collection PubMed
description BACKGROUND: Metabolic diseases such as obesity are known to be driven by both environmental and genetic factors. Although genome-wide association studies of common variants and their impact on complex traits have provided some biological insight into disease etiology, identified genetic variants have been found to contribute only a small proportion to disease heritability, and to map mainly to non-coding regions of the genome. To link variants to function, association studies of cellular traits, such as epigenetic marks, in disease-relevant tissues are commonly applied. SCOPE OF THE REVIEW: We review large-scale efforts to generate genome-wide maps of coordinated epigenetic marks and their utility in complex disease dissection with a focus on DNA methylation. We contrast DNA methylation profiling methods and discuss the advantages of using targeted methods for single-base resolution assessments of methylation levels across tissue-specific regulatory regions to deepen our understanding of contributing factors leading to complex diseases. MAJOR CONCLUSIONS: Large-scale assessments of DNA methylation patterns in metabolic disease-linked study cohorts have provided insight into the impact of variable epigenetic variants in disease etiology. In-depth profiling of epigenetic marks at regulatory regions, particularly at tissue-specific elements, will be key to dissect the genetic and environmental components contributing to metabolic disease onset and progression.
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spelling pubmed-73003882020-06-22 Capturing functional epigenomes for insight into metabolic diseases Allum, Fiona Grundberg, Elin Mol Metab Review BACKGROUND: Metabolic diseases such as obesity are known to be driven by both environmental and genetic factors. Although genome-wide association studies of common variants and their impact on complex traits have provided some biological insight into disease etiology, identified genetic variants have been found to contribute only a small proportion to disease heritability, and to map mainly to non-coding regions of the genome. To link variants to function, association studies of cellular traits, such as epigenetic marks, in disease-relevant tissues are commonly applied. SCOPE OF THE REVIEW: We review large-scale efforts to generate genome-wide maps of coordinated epigenetic marks and their utility in complex disease dissection with a focus on DNA methylation. We contrast DNA methylation profiling methods and discuss the advantages of using targeted methods for single-base resolution assessments of methylation levels across tissue-specific regulatory regions to deepen our understanding of contributing factors leading to complex diseases. MAJOR CONCLUSIONS: Large-scale assessments of DNA methylation patterns in metabolic disease-linked study cohorts have provided insight into the impact of variable epigenetic variants in disease etiology. In-depth profiling of epigenetic marks at regulatory regions, particularly at tissue-specific elements, will be key to dissect the genetic and environmental components contributing to metabolic disease onset and progression. Elsevier 2020-02-14 /pmc/articles/PMC7300388/ /pubmed/32199819 http://dx.doi.org/10.1016/j.molmet.2019.12.016 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Allum, Fiona
Grundberg, Elin
Capturing functional epigenomes for insight into metabolic diseases
title Capturing functional epigenomes for insight into metabolic diseases
title_full Capturing functional epigenomes for insight into metabolic diseases
title_fullStr Capturing functional epigenomes for insight into metabolic diseases
title_full_unstemmed Capturing functional epigenomes for insight into metabolic diseases
title_short Capturing functional epigenomes for insight into metabolic diseases
title_sort capturing functional epigenomes for insight into metabolic diseases
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300388/
https://www.ncbi.nlm.nih.gov/pubmed/32199819
http://dx.doi.org/10.1016/j.molmet.2019.12.016
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