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通过全基因组基因表达分析揭示的与骨质疏松症相关的关键基因。

Key genes associated with osteoporosis revealed by genome wide gene expression analysis.

作者信息

Chen Jie, Wang Lei, Shen Yuhui, Yu Jian, Ye Tingjun, Zhuang Chengyu, Zhang Weibin

机构信息

Department of Orthopedics, Shanghai Institute of Traumatology and Orthopedics, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin Er Rd, Shanghai, 200025, People's Republic of China.

出版信息

Mol Biol Rep. 2014 Sep;41(9):5971-7. doi: 10.1007/s11033-014-3474-1. Epub 2014 Jul 4.

Abstract

Gene expression profiles of circulating monocytes were analyzed to identify key genes associated with osteoporosis. Raw microarray data were downloaded from gene expression omnibus under accession number GSE7158, including 8 microarray dataset for patients with high peak bone mass (PBM) and 8 for low PBM. Package linear models for microarray data of R was adopted to screen out differentially expressed genes (DEGs). Gene ontology enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed with plug-ins of cytoscape. Protein-protein interaction network was constructed using FunCoup. A total of 283 DEGs were identified in low-PBM group, including 135 up- and 148 down-regulated genes. A considerable part of DEGs were localized in plasma membrane. Several ion transport-related pathways were revealed, such as mineral absorption and carbohydrate digestion and absorption. A range of DEGs were identified and some of them were related to calcium transport as well as osteoporosis. These findings are helpful in disclosing the pathogenetic mechanisms of osteoporosis.

摘要

分析循环单核细胞的基因表达谱以鉴定与骨质疏松症相关的关键基因。原始微阵列数据从基因表达综合数据库下载,登录号为GSE7158,包括8个高骨峰值(PBM)患者的微阵列数据集和8个低PBM患者的微阵列数据集。采用R语言的微阵列数据线性模型软件包筛选差异表达基因(DEG)。利用Cytoscape插件进行基因本体富集分析和京都基因与基因组百科全书通路分析。使用FunCoup构建蛋白质-蛋白质相互作用网络。在低PBM组中总共鉴定出283个DEG,包括135个上调基因和148个下调基因。相当一部分DEG定位于质膜。揭示了几种与离子转运相关的途径,如矿物质吸收以及碳水化合物消化和吸收。鉴定出一系列DEG,其中一些与钙转运以及骨质疏松症有关。这些发现有助于揭示骨质疏松症的发病机制。

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