Li Jinyu, Feng Guiyu, He Haoyang, Wang Haolin, Tang Jia, Han Aiqing, Mu Xiaohong, Zhu Weifeng
Department of Orthopedic, Dongzhimen Hospital, Beijing University of Chinese Medicine, No. 5 Haihaicang, Dongcheng District, Beijing, 100007, China.
Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Chin Med. 2022 Apr 15;17(1):47. doi: 10.1186/s13020-022-00596-6.
Precision medicine aims to address the demand for precise therapy at the gene and pathway levels. We aimed to design software to allow precise treatment of osteoporosis (OP) with Chinese medicines (CMs) at the gene and pathway levels.
PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP database), and the Wanfang database were searched to identify studies treating osteoporosis with CMs. The TCMSP was used to identify bioactive ingredients and related genes for each CM. Gene expression omnibus (GEO) database and the limma package were used to identify differentially expressed genes in osteoporosis. Perl software was used to identify the shared genes between the bioactive components in CM and osteoporosis. R packages and bioconductor packages were used to define the target relationship between shared genes and their related pathways. Third-party Python libraries were used to write program codes. Pyinstaller library was used to create an executable program file.
Data mining: a total of 164 CMs were included, but Drynariae Rhizoma (gusuibu) was used to present this process. We obtained 44 precise relationships among the bioactive ingredients of Drynariae Rhizoma, shared genes, and pathways. Python programming: we developed the software to show the precise relationship among bioactive ingredients, shared genes, and pathways for each CM, including Drynariae Rhizoma.
This study could increase the precision of CM, and could provide a valuable and convenient software for searching precise relationships among bioactive ingredients, shared genes, and pathways.
精准医学旨在满足基因和通路水平上精准治疗的需求。我们旨在设计一款软件,以便在基因和通路水平上实现用中药精准治疗骨质疏松症(OP)。
检索了PubMed、EMBASE、Cochrane图书馆、中国知网(CNKI)、中国科技期刊数据库(维普数据库)和万方数据库,以识别用中药治疗骨质疏松症的研究。利用中药系统药理学数据库与分析平台(TCMSP)识别每种中药的生物活性成分和相关基因。基因表达综合数据库(GEO)和limma软件包用于识别骨质疏松症中差异表达的基因。使用Perl软件识别中药生物活性成分与骨质疏松症之间的共享基因。使用R软件包和生物导体软件包定义共享基因与其相关通路之间的靶标关系。使用第三方Python库编写程序代码。使用Pyinstaller库创建可执行程序文件。
数据挖掘:共纳入164种中药,但以骨碎补为例展示此过程。我们获得了骨碎补生物活性成分、共享基因和通路之间的44种精确关系。Python编程:我们开发了该软件,以展示每种中药(包括骨碎补)的生物活性成分、共享基因和通路之间的精确关系。
本研究可提高中药治疗的精准性,并可为查找生物活性成分、共享基因和通路之间的精确关系提供一款有价值且便捷的软件。