Cargando…

Detection of type 2 diabetes related modules and genes based on epigenetic networks

BACKGROUND: Type 2 diabetes (T2D) is one of the most common chronic metabolic diseases characterized by insulin resistance and the decrease of insulin secretion. Genetic variation can only explain part of the heritability of T2D, so there need new methods to detect the susceptibility genes of the di...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Hui, Wang, Tongtong, Liu, Hongbo, Wei, Yanjun, Zhao, Guofeng, Su, Jianzhong, Wu, Qiong, Qiao, Hong, Zhang, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4080446/
https://www.ncbi.nlm.nih.gov/pubmed/24565181
http://dx.doi.org/10.1186/1752-0509-8-S1-S5
_version_ 1782323985836408832
author Liu, Hui
Wang, Tongtong
Liu, Hongbo
Wei, Yanjun
Zhao, Guofeng
Su, Jianzhong
Wu, Qiong
Qiao, Hong
Zhang, Yan
author_facet Liu, Hui
Wang, Tongtong
Liu, Hongbo
Wei, Yanjun
Zhao, Guofeng
Su, Jianzhong
Wu, Qiong
Qiao, Hong
Zhang, Yan
author_sort Liu, Hui
collection PubMed
description BACKGROUND: Type 2 diabetes (T2D) is one of the most common chronic metabolic diseases characterized by insulin resistance and the decrease of insulin secretion. Genetic variation can only explain part of the heritability of T2D, so there need new methods to detect the susceptibility genes of the disease. Epigenetics could establish the interface between the environmental factor and the T2D Pathological mechanism. RESULTS: Based on the network theory and by combining epigenetic characteristics with human interactome, the weighted human DNA methylation network (WMPN) was constructed, and a T2D-related subnetwork (TMSN) was obtained through T2D-related differentially methylated genes. It is found that TMSN had a T2D specific network structure that non-fatal metabolic disease causing genes were often located in the topological and functional periphery of network. Combined with chromatin modifications, the weighted chromatin modification network (WCPN) was built, and a T2D-related chromatin modification pattern subnetwork was obtained by the TMSN gene set. TCSN had a densely connected network community, indicating that TMSN and TCSN could represent a collection of T2D-related epigenetic dysregulated sub-pathways. Using the cumulative hypergeometric test, 24 interplay modules of DNA methylation and chromatin modifications were identified. By the analysis of gene expression in human T2D islet tissue, it is found that there existed genes with the variant expression level caused by the aberrant DNA methylation and (or) chromatin modifications, which might affect and promote the development of T2D. CONCLUSIONS: Here we have detected the potential interplay modules of DNA methylation and chromatin modifications for T2D. The study of T2D epigenetic networks provides a new way for understanding the pathogenic mechanism of T2D caused by epigenetic disorders.
format Online
Article
Text
id pubmed-4080446
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-40804462014-07-14 Detection of type 2 diabetes related modules and genes based on epigenetic networks Liu, Hui Wang, Tongtong Liu, Hongbo Wei, Yanjun Zhao, Guofeng Su, Jianzhong Wu, Qiong Qiao, Hong Zhang, Yan BMC Syst Biol Proceedings BACKGROUND: Type 2 diabetes (T2D) is one of the most common chronic metabolic diseases characterized by insulin resistance and the decrease of insulin secretion. Genetic variation can only explain part of the heritability of T2D, so there need new methods to detect the susceptibility genes of the disease. Epigenetics could establish the interface between the environmental factor and the T2D Pathological mechanism. RESULTS: Based on the network theory and by combining epigenetic characteristics with human interactome, the weighted human DNA methylation network (WMPN) was constructed, and a T2D-related subnetwork (TMSN) was obtained through T2D-related differentially methylated genes. It is found that TMSN had a T2D specific network structure that non-fatal metabolic disease causing genes were often located in the topological and functional periphery of network. Combined with chromatin modifications, the weighted chromatin modification network (WCPN) was built, and a T2D-related chromatin modification pattern subnetwork was obtained by the TMSN gene set. TCSN had a densely connected network community, indicating that TMSN and TCSN could represent a collection of T2D-related epigenetic dysregulated sub-pathways. Using the cumulative hypergeometric test, 24 interplay modules of DNA methylation and chromatin modifications were identified. By the analysis of gene expression in human T2D islet tissue, it is found that there existed genes with the variant expression level caused by the aberrant DNA methylation and (or) chromatin modifications, which might affect and promote the development of T2D. CONCLUSIONS: Here we have detected the potential interplay modules of DNA methylation and chromatin modifications for T2D. The study of T2D epigenetic networks provides a new way for understanding the pathogenic mechanism of T2D caused by epigenetic disorders. BioMed Central 2014-01-24 /pmc/articles/PMC4080446/ /pubmed/24565181 http://dx.doi.org/10.1186/1752-0509-8-S1-S5 Text en Copyright © 2014 Liu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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.
spellingShingle Proceedings
Liu, Hui
Wang, Tongtong
Liu, Hongbo
Wei, Yanjun
Zhao, Guofeng
Su, Jianzhong
Wu, Qiong
Qiao, Hong
Zhang, Yan
Detection of type 2 diabetes related modules and genes based on epigenetic networks
title Detection of type 2 diabetes related modules and genes based on epigenetic networks
title_full Detection of type 2 diabetes related modules and genes based on epigenetic networks
title_fullStr Detection of type 2 diabetes related modules and genes based on epigenetic networks
title_full_unstemmed Detection of type 2 diabetes related modules and genes based on epigenetic networks
title_short Detection of type 2 diabetes related modules and genes based on epigenetic networks
title_sort detection of type 2 diabetes related modules and genes based on epigenetic networks
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4080446/
https://www.ncbi.nlm.nih.gov/pubmed/24565181
http://dx.doi.org/10.1186/1752-0509-8-S1-S5
work_keys_str_mv AT liuhui detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT wangtongtong detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT liuhongbo detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT weiyanjun detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT zhaoguofeng detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT sujianzhong detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT wuqiong detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT qiaohong detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks
AT zhangyan detectionoftype2diabetesrelatedmodulesandgenesbasedonepigeneticnetworks