[1]李祖涛,阿布都艾尼·热吾提,车立新,等.应用生物信息学技术鉴定并验证绝经后骨质疏松症中靶点基因[J].中华老年骨科与康复电子杂志,2025,(04):193-200.[doi:DOI：10.3877/cma.j.issn.2096-0263.2025.04.001]
　Li Zutao,Abuduaini· ReWT,Che Lixin,et al.Identification and validation of target genes in postmenopausal osteoporosis based on bioinformaticstechnology[J].Chin J Geriatr Orthop Rehabil(Electronic Edition),2025,(04):193-200.[doi:DOI：10.3877/cma.j.issn.2096-0263.2025.04.001]
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应用生物信息学技术鉴定并验证绝经后骨质疏松症中靶点基因()
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中华老年骨科与康复电子杂志[ISSN:1674-3911/CN:11-9292/R]

卷:
期数:
2025年04
页码:
193-200
栏目:
基础研究
出版日期:
2025-08-05

文章信息/Info

Title:
Identification and validation of target genes in postmenopausal osteoporosis based on bioinformaticstechnology
作者:
李祖涛; 阿布都艾尼·热吾提; 车立新; 徐江波; 赵清斌
8300011 乌鲁木齐，新疆维吾尔自治区人民医院骨科中心创伤病区
Author(s):
Li Zutao;  Abuduaini· ReWT;  Che Lixin;  Xu Jiangbo;  Zhao Qingbin.
Department of Orthopedics, People’s Hospital of Xin jiang Uygur Autonomous Region, Urumqi 830001, China
关键词:
绝经后骨质疏松;  微小核糖核苷酸;  生物信息学
Keywords:
Postmenopausal osteoporosis;  Micro-ribonucleic acid;  Bioinformatics
DOI:
DOI：10.3877/cma.j.issn.2096-0263.2025.04.001
文献标志码:
A
摘要:
目的 应用生物信息学方法鉴定绝经后骨质疏松症的差异表达的基因并收集临床样本进行验证。方法 利用 GEO 数据库筛选绝经后骨质疏松症患者和健康对照组基因表达谱芯片。采用GEO2R筛选出差异表达的miRNAs，利用miRDB、miRTarBase、Targetscan在线数据库进行靶基因预测，利用DAVID数据库对靶基因进行GO富集分析以及KEGG信号通路分析，并利用STRING在线网站构建蛋白质-蛋白质相互作用（PPI）网络并在Cytoscape软件中进行可视化。使用MCODE插件对PPI网络进行了模块分析，使用Hubba插件以关联度＞10为标准筛选Hub基因。收集临床样本应用qRT-PCR和Western blot在基因和蛋白水平验证上述鉴定出的关键基因。结果 本研究共鉴定出46个差异表达的miRNAs，利用miRDB、miRTarBase、Targetscan在线数据库进行靶基因预测，并对预测的结果进行多个数据库的筛选、并取交集，最终挑选出三个数据库共筛选出的靶基因97个。经过GO、KEGG富集分析，观察到差异表达的基因在生物学过程中主要富集在横纹肌调控；在细胞定位中，基因主要富集在细胞质和核质中；分子功能上看，基因主要集中转录共激活因子结合；在信号通路方面基因主要富集在FoxO信号通路等。利用STRING在线网站构建PPI网络并在Cytoscape软件中进行可视化，得出PPI网络中的Hub基因分别为：CCND1、FOSL1、JUNB、IGF1R、BTG2等。用qRT-PCR和Western blot方法验证临床样本中上述鉴定出的基因，其中：BTG2、CCND1、JUNB、IGF1R在骨质疏松组表达增高，差异有统计学意义（P＜0.05），而FOSL1表达两组无统计学意义（P＞0.05）。结论 本研究应用生物信息学方法鉴定得出了差异表达的关键基因并收集临床样本进行验证，有助于探索绝经后骨质疏松症新的诊断和治疗靶点，为研究绝经后骨质疏松症的临床诊断和治疗提供新的切入点。
Abstract:
Objective The differentially expressed genes of postmenopausal osteoporosis were identified by bioinformatics and clinical samples were collected for verification. Methods The gene expressionmicroarray of postmenopausal osteoporosis patients and healthy controls was screened by GEO database; thedifferentially expressed miRNAs was screened by GEO2R, and the target genes were predicted by miRDB,miRTarBase and Targetscan online databases; the target genes were analyzed by GO enrichment analysis andKEGG signal pathway analysis by DAVID database; protein-protein interaction (PPI) network was constructed by STRING online website and visualized in Cytoscape software. The MCODE plug-in was used to analyze the PPI network, and the Hubba plug-in was used to screen the Hub gene with the correlation degree >10 as the standard. Collect clinical samples and use qRT-PCR and Westernblot to verify the key genes identified above at gene and protein level. Results In this study, 46 differentially expressed miRNAs were identified, and the target genes were predicted by miRDB, miRTarBase and Targetscan online databases. The predicted results were screened and intersected by multiple databases, and 97 target genes were selected from the three databases. Through GO and KEGG enrichment analysis, it was observed that differentially expressed genes were mainly enriched in striated muscle regulation in biological process; in Cellular Component, genes were mainly enriched in cytoplasm and nucleus; in terms of molecular function, genes were mainly concentrated in transcriptional coactivator binding; in signal pathway, genes were mainly enriched inFoxO signal pathway and so on. Using STRING online website to build PPI network and visualization in Cytoscape software, it is concluded that the Hub genes in PPI network are CCND1, FOSL1, JUNB, IGF1R,BTG2 and so on. QRT-PCR and Westernblot methods were used to verify the above identified genes in clinical samples. Among them, the expression of BTG2, CCND1, JUNB and IGF1R in osteoporosis group wassignificantly higher than that in osteoporosis group, but there was no significant difference in FOSL1 expression between the two groups. Conclusions In this study, the differentially expressed key genes were identified by bioinformatics methods and clinical samples were collected for verification, which is helpful to explore new targets for diagnosis and treatment of postmenopausal osteoporosis. It provides a new startingpoint for the clinical diagnosis and treatment of postmenopausal osteoporosis.

备注/Memo

备注/Memo:
基金项目：新疆维吾尔自治区自然科学基金（2019D01C106）
更新日期/Last Update: 2026-04-29