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基于网络的绝经后骨质疏松症全转录组表达研究。

Network-based Transcriptome-wide Expression Study for Postmenopausal Osteoporosis.

机构信息

Center for Biomedical informatics and Genomics, Department of Medicine, Tulane University, New Orleans, Louisiana.

Institute of Reproduction and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China.

出版信息

J Clin Endocrinol Metab. 2020 Aug 1;105(8):2678-91. doi: 10.1210/clinem/dgaa319.

Abstract

PURPOSE

Menopause is a crucial physiological transition during a woman's life, and it occurs with growing risks of health issues like osteoporosis. To identify postmenopausal osteoporosis-related genes, we performed transcriptome-wide expression analyses for human peripheral blood monocytes (PBMs) using Affymetrix 1.0 ST arrays in 40 Caucasian postmenopausal women with discordant bone mineral density (BMD) levels.

METHODS

We performed multiscale embedded gene coexpression network analysis (MEGENA) to study functionally orchestrating clusters of differentially expressed genes in the form of functional networks. Gene sets net correlations analysis (GSNCA) was applied to assess how the coexpression structure of a predefined gene set differs in high and low BMD groups. Bayesian network (BN) analysis was used to identify important regulation patterns between potential risk genes for osteoporosis. A small interfering ribonucleic acid (siRNA)-based gene silencing in vitro experiment was performed to validate the findings from BN analysis.

RESULT

MEGENA showed that the "T cell receptor signaling pathway" and the "osteoclast differentiation pathway" were significantly enriched in the identified compact network, which is significantly correlated with BMD variation. GSNCA revealed that the coexpression structure of the "Signaling by TGF-beta receptor complex pathway" is significantly different between the 2 BMD discordant groups; the hub genes in the postmenopausal low and high BMD group are FURIN and SMAD3 respectively. With siRNA in vitro experiments, we confirmed the regulation relationship of TGFBR2-SMAD7 and TGFBR1-SMURF2.

MAIN CONCLUSION

The present study suggests that biological signals involved in monocyte recruitment, monocyte/macrophage lineage development, osteoclast formation, and osteoclast differentiation might function together in PBMs that contribute to the pathogenesis of postmenopausal osteoporosis.

摘要

目的

绝经是女性生命中一个至关重要的生理过渡期,在此期间,骨质疏松等健康问题的风险日益增加。为了鉴定与绝经后骨质疏松症相关的基因,我们对 40 名高加索绝经后女性的外周血单核细胞(PBMs)进行了全转录组表达分析,使用 Affymetrix 1.0 ST 芯片,这些女性的骨密度(BMD)水平存在差异。

方法

我们进行多尺度嵌入式基因共表达网络分析(MEGENA),以研究功能上协调差异表达基因的功能网络。基因集网络相关性分析(GSNCA)用于评估高、低 BMD 组中预定义基因集的共表达结构差异。贝叶斯网络(BN)分析用于确定骨质疏松症潜在风险基因之间的重要调控模式。体外基于小干扰核糖核酸(siRNA)的基因沉默实验用于验证 BN 分析的结果。

结果

MEGENA 显示,在鉴定的紧密网络中,“T 细胞受体信号通路”和“破骨细胞分化途径”显著富集,与 BMD 变化显著相关。GSNCA 显示,“TGF-beta 受体复合物信号通路”的共表达结构在 2 个 BMD 不一致的组之间存在显著差异;绝经后低 BMD 和高 BMD 组的核心基因分别是 FURIN 和 SMAD3。通过体外 siRNA 实验,我们证实了 TGFBR2-SMAD7 和 TGFBR1-SMURF2 的调控关系。

主要结论

本研究表明,参与单核细胞募集、单核细胞/巨噬细胞谱系发育、破骨细胞形成和破骨细胞分化的生物学信号可能在 PBMs 中共同作用,从而导致绝经后骨质疏松症的发病机制。

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