Suppr超能文献

生物信息学方法鉴定骨质疏松症的潜在治疗靶点和分子调控机制。

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods.

机构信息

Department of Geriatrics, The Municipal Hospital of Suzhou, Jiangsu, China.

Department of orthopedics, The First Affiliated Hospital of Soochow University, Jiangsu, China.

出版信息

Biomed Res Int. 2021 Mar 10;2021:8851421. doi: 10.1155/2021/8851421. eCollection 2021.

Abstract

BACKGROUND

Osteoporosis is characterized by low bone mass, deterioration of bone tissue structure, and susceptibility to fracture. New and more suitable therapeutic targets need to be discovered.

METHODS

We collected osteoporosis-related datasets (GSE56815, GSE99624, and GSE63446). The methylation markers were obtained by differential analysis. Degree, DMNC, MCC, and MNC plug-ins were used to screen the important methylation markers in PPI network, then enrichment analysis was performed. ROC curve was used to evaluate the diagnostic effect of osteoporosis. In addition, we evaluated the difference in immune cell infiltration between osteoporotic patients and control by ssGSEA. Finally, differential miRNAs in osteoporosis were used to predict the regulators of key methylation markers.

RESULTS

A total of 2351 differentially expressed genes and 5246 differentially methylated positions were obtained between osteoporotic patients and controls. We identified 19 methylation markers by PPI network. They were mainly involved in biological functions and signaling pathways such as apoptosis and immune inflammation. HIST1H3G, MAP3K5, NOP2, OXA1L, and ZFPM2 with higher AUC values were considered key methylation markers. There were significant differences in immune cell infiltration between osteoporotic patients and controls, especially dendritic cells and natural killer cells. The correlation between MAP3K5 and immune cells was high, and its differential expression was also validated by other two datasets. In addition, NOP2 was predicted to be regulated by differentially expressed hsa-miR-3130-5p.

CONCLUSION

Our efforts aim to provide new methylation markers as therapeutic targets for osteoporosis to better treat osteoporosis in the future.

摘要

背景

骨质疏松症的特征是骨量低、骨组织结构恶化以及易骨折。需要发现新的、更合适的治疗靶点。

方法

我们收集了骨质疏松症相关数据集(GSE56815、GSE99624 和 GSE63446)。通过差异分析获得甲基化标记物。使用 Degree、DMNC、MCC 和 MNC 插件筛选 PPI 网络中的重要甲基化标记物,然后进行富集分析。使用 ROC 曲线评估骨质疏松症的诊断效果。此外,我们通过 ssGSEA 评估骨质疏松症患者和对照者之间免疫细胞浸润的差异。最后,使用骨质疏松症中的差异 miRNA 预测关键甲基化标记物的调节剂。

结果

在骨质疏松症患者和对照组之间获得了 2351 个差异表达基因和 5246 个差异甲基化位置。通过 PPI 网络鉴定了 19 个甲基化标记物。它们主要涉及凋亡和免疫炎症等生物功能和信号通路。具有较高 AUC 值的 HIST1H3G、MAP3K5、NOP2、OXA1L 和 ZFPM2 被认为是关键的甲基化标记物。骨质疏松症患者和对照组之间的免疫细胞浸润存在显著差异,尤其是树突细胞和自然杀伤细胞。MAP3K5 与免疫细胞的相关性较高,并且通过另外两个数据集也验证了其差异表达。此外,预测 NOP2 受差异表达的 hsa-miR-3130-5p 调控。

结论

我们的努力旨在提供新的甲基化标记物作为骨质疏松症的治疗靶点,以便将来更好地治疗骨质疏松症。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b826/7969088/a67e396d5142/BMRI2021-8851421.001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验