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Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray

BACKGROUND: Osteoporosis affects 200 million people worldwide and places an enormous economic burden on society. We aim to identify the feature genes that are related to osteoprotegerin in osteoporosis and to perform function analysis with DNA microarray from human bone marrow. METHODS: We downloade...

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Autores principales: Wu, Xiaoming, Guo, Shuzhang, Shen, Guanghao, Ma, Xing, Tang, Chi, Xie, Kangning, Liu, Juan, Guo, Wei, Yan, Yili, Luo, Erping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3735399/
https://www.ncbi.nlm.nih.gov/pubmed/23731710
http://dx.doi.org/10.1186/2047-783X-18-15
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author Wu, Xiaoming
Guo, Shuzhang
Shen, Guanghao
Ma, Xing
Tang, Chi
Xie, Kangning
Liu, Juan
Guo, Wei
Yan, Yili
Luo, Erping
author_facet Wu, Xiaoming
Guo, Shuzhang
Shen, Guanghao
Ma, Xing
Tang, Chi
Xie, Kangning
Liu, Juan
Guo, Wei
Yan, Yili
Luo, Erping
author_sort Wu, Xiaoming
collection PubMed
description BACKGROUND: Osteoporosis affects 200 million people worldwide and places an enormous economic burden on society. We aim to identify the feature genes that are related to osteoprotegerin in osteoporosis and to perform function analysis with DNA microarray from human bone marrow. METHODS: We downloaded the gene expression profile GSE35957 from Gene Expression Omnibus database including nine gene chips from bone marrow mesenchymal stem cells of five osteoporotic and four non-osteoporotic subjects. The differentially expressed genes between normal and disease samples were identified by LIMMA package in R language. The interactions among the osteoprotegerin gene (OPG) and differentially expressed genes were searched and visualized by Cytoscape. MCODE and Bingo were used to perform module analysis. Finally, GENECODIS was used to obtain enriched pathways of genes in an interaction network. RESULTS: A total of 656 genes were identified as differentially expressed genes between osteoporotic and non-osteoporotic samples. IL17RC, COL1A1, and ESR1 were identified to interact with OPG directly from the protein-protein interaction network. A module containing ERS1 was screened out, and this module was most significantly enriched in organ development. Pathway enrichment analysis suggested genes in the interaction network were related to focal adhesion. CONCLUSIONS: The expression pattern of IL17RC, COL1A1, and ESR1 can be useful in osteoporosis detection, which may help in identifying those populations at high risk for osteoporosis, and in directing treatment of osteoporosis.
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spelling pubmed-37353992013-08-07 Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray Wu, Xiaoming Guo, Shuzhang Shen, Guanghao Ma, Xing Tang, Chi Xie, Kangning Liu, Juan Guo, Wei Yan, Yili Luo, Erping Eur J Med Res Research BACKGROUND: Osteoporosis affects 200 million people worldwide and places an enormous economic burden on society. We aim to identify the feature genes that are related to osteoprotegerin in osteoporosis and to perform function analysis with DNA microarray from human bone marrow. METHODS: We downloaded the gene expression profile GSE35957 from Gene Expression Omnibus database including nine gene chips from bone marrow mesenchymal stem cells of five osteoporotic and four non-osteoporotic subjects. The differentially expressed genes between normal and disease samples were identified by LIMMA package in R language. The interactions among the osteoprotegerin gene (OPG) and differentially expressed genes were searched and visualized by Cytoscape. MCODE and Bingo were used to perform module analysis. Finally, GENECODIS was used to obtain enriched pathways of genes in an interaction network. RESULTS: A total of 656 genes were identified as differentially expressed genes between osteoporotic and non-osteoporotic samples. IL17RC, COL1A1, and ESR1 were identified to interact with OPG directly from the protein-protein interaction network. A module containing ERS1 was screened out, and this module was most significantly enriched in organ development. Pathway enrichment analysis suggested genes in the interaction network were related to focal adhesion. CONCLUSIONS: The expression pattern of IL17RC, COL1A1, and ESR1 can be useful in osteoporosis detection, which may help in identifying those populations at high risk for osteoporosis, and in directing treatment of osteoporosis. BioMed Central 2013-06-03 /pmc/articles/PMC3735399/ /pubmed/23731710 http://dx.doi.org/10.1186/2047-783X-18-15 Text en Copyright © 2013 Wu 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.
spellingShingle Research
Wu, Xiaoming
Guo, Shuzhang
Shen, Guanghao
Ma, Xing
Tang, Chi
Xie, Kangning
Liu, Juan
Guo, Wei
Yan, Yili
Luo, Erping
Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray
title Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray
title_full Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray
title_fullStr Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray
title_full_unstemmed Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray
title_short Screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with DNA microarray
title_sort screening of osteoprotegerin-related feature genes in osteoporosis and functional analysis with dna microarray
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3735399/
https://www.ncbi.nlm.nih.gov/pubmed/23731710
http://dx.doi.org/10.1186/2047-783X-18-15
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