Cargando…
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...
Autores principales: | , |
---|---|
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 |
_version_ | 1783547578232602624 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7300388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT allumfiona capturingfunctionalepigenomesforinsightintometabolicdiseases AT grundbergelin capturingfunctionalepigenomesforinsightintometabolicdiseases |