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Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity

Obesity has become a major public health issue which is caused by a combination of genetic and environmental factors. Genome-wide DNA methylation studies have identified that DNA methylation at Cytosine-phosphate-Guanine (CpG) sites are associated with obesity. However, subsequent functional validat...

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Autores principales: Guo, Qingjie, Zheng, Ruonan, Huang, Jiarui, He, Meng, Wang, Yuhan, Guo, Zonghao, Sun, Liankun, Chen, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305755/
https://www.ncbi.nlm.nih.gov/pubmed/30619480
http://dx.doi.org/10.3389/fgene.2018.00663
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author Guo, Qingjie
Zheng, Ruonan
Huang, Jiarui
He, Meng
Wang, Yuhan
Guo, Zonghao
Sun, Liankun
Chen, Peng
author_facet Guo, Qingjie
Zheng, Ruonan
Huang, Jiarui
He, Meng
Wang, Yuhan
Guo, Zonghao
Sun, Liankun
Chen, Peng
author_sort Guo, Qingjie
collection PubMed
description Obesity has become a major public health issue which is caused by a combination of genetic and environmental factors. Genome-wide DNA methylation studies have identified that DNA methylation at Cytosine-phosphate-Guanine (CpG) sites are associated with obesity. However, subsequent functional validation of the results from these studies has been challenging given the high number of reported associations. In this study, we applied an integrative analysis approach, aiming to prioritize the drug development candidate genes from many associated CpGs. Association data was collected from previous genome-wide DNA methylation studies and combined using a sample-size-weighted strategy. Gene expression data in adipose tissues and enriched pathways of the affiliated genes were overlapped, to shortlist the associated CpGs. The CpGs with the most overlapping evidence were indicated as the most appropriate CpGs for future studies. Our results revealed that 119 CpGs were associated with obesity (p ≤ 1.03 × 10(−7)). Of the affiliated genes, SOCS3 was the only gene involved in all enriched pathways and was differentially expressed in both visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). In conclusion, our integrative analysis is an effective approach in highlighting the DNA methylation with the highest drug development relevance. SOCS3 may serve as a target for drug development of obesity and its complications.
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spelling pubmed-63057552019-01-07 Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity Guo, Qingjie Zheng, Ruonan Huang, Jiarui He, Meng Wang, Yuhan Guo, Zonghao Sun, Liankun Chen, Peng Front Genet Genetics Obesity has become a major public health issue which is caused by a combination of genetic and environmental factors. Genome-wide DNA methylation studies have identified that DNA methylation at Cytosine-phosphate-Guanine (CpG) sites are associated with obesity. However, subsequent functional validation of the results from these studies has been challenging given the high number of reported associations. In this study, we applied an integrative analysis approach, aiming to prioritize the drug development candidate genes from many associated CpGs. Association data was collected from previous genome-wide DNA methylation studies and combined using a sample-size-weighted strategy. Gene expression data in adipose tissues and enriched pathways of the affiliated genes were overlapped, to shortlist the associated CpGs. The CpGs with the most overlapping evidence were indicated as the most appropriate CpGs for future studies. Our results revealed that 119 CpGs were associated with obesity (p ≤ 1.03 × 10(−7)). Of the affiliated genes, SOCS3 was the only gene involved in all enriched pathways and was differentially expressed in both visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). In conclusion, our integrative analysis is an effective approach in highlighting the DNA methylation with the highest drug development relevance. SOCS3 may serve as a target for drug development of obesity and its complications. Frontiers Media S.A. 2018-12-19 /pmc/articles/PMC6305755/ /pubmed/30619480 http://dx.doi.org/10.3389/fgene.2018.00663 Text en Copyright © 2018 Guo, Zheng, Huang, He, Wang, Guo, Sun and Chen. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Guo, Qingjie
Zheng, Ruonan
Huang, Jiarui
He, Meng
Wang, Yuhan
Guo, Zonghao
Sun, Liankun
Chen, Peng
Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity
title Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity
title_full Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity
title_fullStr Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity
title_full_unstemmed Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity
title_short Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity
title_sort using integrative analysis of dna methylation and gene expression data in multiple tissue types to prioritize candidate genes for drug development in obesity
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305755/
https://www.ncbi.nlm.nih.gov/pubmed/30619480
http://dx.doi.org/10.3389/fgene.2018.00663
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