Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients

Objective: The aim of this study was to gain a better understanding of the molecular mechanisms and identify more critical genes associated with the pathogenesis of postmenopausal osteoporosis (PMOP). Materials and Methods: Microarray data of GSE13850 were download from the Gene Expression Omnibus d...

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Main Authors: Min Ma, Shulin Luo, Wei Zhou, Liangyu Lu, Junfeng Cai, Feng Yuan, Feng Yin
Format: Article
Language:English
Published: Elsevier 2017-04-01
Series:Taiwanese Journal of Obstetrics & Gynecology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1028455917300086
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author Min Ma
Shulin Luo
Wei Zhou
Liangyu Lu
Junfeng Cai
Feng Yuan
Feng Yin
author_facet Min Ma
Shulin Luo
Wei Zhou
Liangyu Lu
Junfeng Cai
Feng Yuan
Feng Yin
author_sort Min Ma
collection DOAJ
description Objective: The aim of this study was to gain a better understanding of the molecular mechanisms and identify more critical genes associated with the pathogenesis of postmenopausal osteoporosis (PMOP). Materials and Methods: Microarray data of GSE13850 were download from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified either in B cells from postmenopausal female nonsmokers with high bone mineral density (BMD) compared with those with low BMD (defined as DEG1 group) or in B cells from postmenopausal female smokers with high BMD compared with postmenopausal female nonsmokers with high BMD (defined as DEG2 group). Gene ontology and immune-related functional enrichment analysis of DEGs were performed. Additionally, the protein–protein interaction network of all DEGs was constructed and subnetworks of the hub genes were extracted. Results: A total of 51 DEGs were identified in the DEG1 group, including 30 up- and 21 downregulated genes. Besides, 86 DEGs were identified in the DEG2 group, of which 46 were upregulated and 40 were downregulated. Immune enrichment analysis showed DEGs were mainly enriched in functions of CD molecules and chemokines and receptor, and the upregulated gene interleukin 4 receptor (IL-4R) was significantly enriched. Moreover, guanine nucleotide-binding protein G (GNAI2), filamin A alpha (FLNA), and transforming growth factor-β1 (TGFB1) were hub proteins in the protein–protein interaction network. Conclusion: IL-4R, GNAI2, FLNA, and TGFB1 may be potential target genes associated with the pathogenesis of PMOP. In particular, FLNA, and TGFB1 may be affected by smoking, a risk factor of PMOP.
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spelling doaj.art-0e5687838c16465d94b638856651eef02022-12-21T20:04:44ZengElsevierTaiwanese Journal of Obstetrics & Gynecology1028-45592017-04-0156216517010.1016/j.tjog.2016.04.038Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patientsMin MaShulin LuoWei ZhouLiangyu LuJunfeng CaiFeng YuanFeng YinObjective: The aim of this study was to gain a better understanding of the molecular mechanisms and identify more critical genes associated with the pathogenesis of postmenopausal osteoporosis (PMOP). Materials and Methods: Microarray data of GSE13850 were download from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified either in B cells from postmenopausal female nonsmokers with high bone mineral density (BMD) compared with those with low BMD (defined as DEG1 group) or in B cells from postmenopausal female smokers with high BMD compared with postmenopausal female nonsmokers with high BMD (defined as DEG2 group). Gene ontology and immune-related functional enrichment analysis of DEGs were performed. Additionally, the protein–protein interaction network of all DEGs was constructed and subnetworks of the hub genes were extracted. Results: A total of 51 DEGs were identified in the DEG1 group, including 30 up- and 21 downregulated genes. Besides, 86 DEGs were identified in the DEG2 group, of which 46 were upregulated and 40 were downregulated. Immune enrichment analysis showed DEGs were mainly enriched in functions of CD molecules and chemokines and receptor, and the upregulated gene interleukin 4 receptor (IL-4R) was significantly enriched. Moreover, guanine nucleotide-binding protein G (GNAI2), filamin A alpha (FLNA), and transforming growth factor-β1 (TGFB1) were hub proteins in the protein–protein interaction network. Conclusion: IL-4R, GNAI2, FLNA, and TGFB1 may be potential target genes associated with the pathogenesis of PMOP. In particular, FLNA, and TGFB1 may be affected by smoking, a risk factor of PMOP.http://www.sciencedirect.com/science/article/pii/S1028455917300086differentially expressed genesgene ontologypostmenopausal osteoporosissmoking
spellingShingle Min Ma
Shulin Luo
Wei Zhou
Liangyu Lu
Junfeng Cai
Feng Yuan
Feng Yin
Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients
Taiwanese Journal of Obstetrics & Gynecology
differentially expressed genes
gene ontology
postmenopausal osteoporosis
smoking
title Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients
title_full Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients
title_fullStr Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients
title_full_unstemmed Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients
title_short Bioinformatics analysis of gene expression profiles in B cells of postmenopausal osteoporosis patients
title_sort bioinformatics analysis of gene expression profiles in b cells of postmenopausal osteoporosis patients
topic differentially expressed genes
gene ontology
postmenopausal osteoporosis
smoking
url http://www.sciencedirect.com/science/article/pii/S1028455917300086
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