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基于数据挖掘和生物信息学分析的强直性脊柱炎相关骨质疏松症的计算药物发现。

Computational Drug Discovery in Ankylosing Spondylitis-Induced Osteoporosis Based on Data Mining and Bioinformatics Analysis.

机构信息

Department of Orthopedics, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.

Department of Orthopedics, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.

出版信息

World Neurosurg. 2023 Jun;174:e8-e16. doi: 10.1016/j.wneu.2023.01.092. Epub 2023 Jan 28.

DOI:10.1016/j.wneu.2023.01.092
PMID:36716856
Abstract

BACKGROUND

Ankylosing spondylitis (AS) and osteoporosis (OP) are both prevalent illnesses in spine surgery, with OP being a possible consequence of AS. However, the mechanism of AS-induced OP (AS-OP) remains unknown, limiting etiologic research and therapy of the illness. To mine targetable medicine for the prevention and treatment of AS-OP, this study analyzes public data sets using bioinformatics to identify genes and biological pathways relevant to AS-OP.

METHODS

First, text mining was used to identify common genes associated with AS and OP, after which functional analysis was carried out. The STRING database and Cytoscape software were used to create protein-protein interaction networks. Hub genes and potential drugs were discovered using drug-gene interaction analysis and transcription factors-gene interaction analysis.

RESULTS

The results of text mining showed 241 genes common to AS and OP, from which 115 key symbols were sorted out by functional analysis. As options for treating AS-OP, protein-protein interaction analysis yielded 20 genes, which may be targeted by 13 medications.

CONCLUSIONS

Carlumab, bermekimab, rilonacept, rilotumumab, and ficlatuzumab were first identified as the potential drugs for the treatment of AS-OP, proving the value of text mining and pathway analysis in drug discovery.

摘要

背景

强直性脊柱炎(AS)和骨质疏松症(OP)都是脊柱外科中常见的疾病,OP 可能是 AS 的后果之一。然而,AS 导致的 OP(AS-OP)的机制尚不清楚,限制了对该疾病的病因研究和治疗。为了挖掘针对 AS-OP 的预防和治疗的靶向药物,本研究使用生物信息学分析公共数据集,以识别与 AS-OP 相关的基因和生物学途径。

方法

首先,使用文本挖掘技术识别与 AS 和 OP 相关的常见基因,然后进行功能分析。使用 STRING 数据库和 Cytoscape 软件创建蛋白质-蛋白质相互作用网络。使用药物-基因相互作用分析和转录因子-基因相互作用分析发现潜在药物和关键基因。

结果

文本挖掘的结果显示,AS 和 OP 共有 241 个基因,其中 115 个关键符号通过功能分析被筛选出来。作为治疗 AS-OP 的选择,蛋白质-蛋白质相互作用分析产生了 20 个基因,这些基因可能被 13 种药物靶向。

结论

首次发现卡尔单抗、贝美单抗、利那洛肽、利妥昔单抗和 ficlatuzumab 可能是治疗 AS-OP 的潜在药物,证明了文本挖掘和途径分析在药物发现中的价值。

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