[1]姜 瑞,张 征,谭爱华.慢性阻塞性肺疾病与骨质疏松症的生物信息学分析[J].医学信息,2023,36(17):1-6.[doi:10.3969/j.issn.1006-1959.2023.17.001]
　JIANG Rui,ZHANG Zheng,TAN Ai-hua.Bioinformatics Analysis of Chronic Obstructive Pulmonary Disease and Osteoporosis[J].Journal of Medical Information,2023,36(17):1-6.[doi:10.3969/j.issn.1006-1959.2023.17.001]
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慢性阻塞性肺疾病与骨质疏松症的生物信息学分析()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年17期
页码:
1-6
栏目:
生物信息学
出版日期:
2023-09-01

文章信息/Info

Title:
Bioinformatics Analysis of Chronic Obstructive Pulmonary Disease and Osteoporosis
文章编号:
1006-1959（2023）17-0001-06
作者:
姜 瑞; 张 征; 谭爱华
（1.湖北中医药大学针灸骨伤学院，湖北 武汉 430065；2.湖北中医药大学附属黄冈市中医医院骨科，湖北 黄冈 438000；3.北京中医药大学博士后流动站，北京 100007）
Author(s):
JIANG Rui; ZHANG Zheng; TAN Ai-hua
(1.College of Acupuncture and Moxibustion and Orthopaedics,Hubei University of Chinese Medicine,Wuhan 430065,Hubei,China;2.Department of Orthopedics,Huanggang Hospital of Traditional Chinese Medicine Affiliated with Hubei University of Chinese Medicine, Huanggang 438000,Hubei,China;3.Beijing University of Chinese Medicine Postdoctoral Station,Beijing 100007,China)
关键词:
生物信息学; 骨质疏松症; 慢性阻塞性肺疾病; 靶基因
Keywords:
Bioinformatics; Osteoporosis; Chronic obstructive pulmonary disease; Target gene
分类号:
R259
DOI:
10.3969/j.issn.1006-1959.2023.17.001
文献标志码:
A
摘要:
目的 利用生物信息学分析慢性阻塞性肺疾病（COPD）与骨质疏松症（OP）的关系。方法 在Genecards、OMIM、DRUGBANK等数据库查找出COPD和OP的疾病基因靶点，将所获得靶点分别进行汇总、筛选、去重后分别得到两组疾病的最终基因靶点。将两组疾病的最终基因靶点取交集，将共同基因靶点导入STRING数据库构建蛋白互作（PPI）网络图，下载tsv格式的PPI网络，导入Cytoscape3.9.1软件，通过插件cytoHubba，筛选出Degree前20位的目标靶基因。利用DAVID数据库对两种疾病的共同靶基因进行GO和KEGG富集分析。结果 筛选出COPD相关基因393个、OP相关基因1389个，取交集后获得共同靶点基因172个，根据PPI网络图可知，STAT3、IL6、AKT1、CTNNB1、IL10、MAPK1、IL17、TNF等为COPD与OP的共同关键靶基因，GO富集显示其主要与雌激素代谢、炎症反应、细胞对缺氧的反应、免疫反应、增龄等相关，KEGG信号通路包括JAK-STAT信号通路、HIF-1信号通路、IL-17信号通路等。结论 通过COPD与OP的共同关键基因和涉及的信号通路，为了解两种疾病相关性及为后续相关研究提供了一定的理论基础。
Abstract:
Objective To analyze the relationship between chronic obstructive pulmonary disease (COPD) and osteoporosis (OP) by bioinformatics.Methods The disease gene targets of COPD and OP were identified in Genecards, OMIM, DRUGBANK and other databases, and the obtained targets were aggregated, screened and de-duplicated to obtain the final gene targets of the two groups of diseases, respectively. The final gene targets of the two groups were intersected, and the common gene targets were imported into the STRING database to construct a protein interaction (PPI) network diagram. The tsv format PPI network was downloaded and imported into Cytoscape 3.9.1 software. The top 20 target genes of Degree were screened by the plug-in cytoHubba. GO and KEGG enrichment analysis of the common target genes of the two diseases was performed using the DAVID database.Results A total of 393 COPD-related genes and 1389 OP-related genes were screened out, and 172 common target genes were obtained after intersection. According to the PPI network diagram, STAT3, IL6, AKT1, CTNNB1, IL10, MAPK1, IL17 and TNF were the common key target genes of COPD and OP. GO enrichment was mainly related to estrogen metabolism, inflammatory response, cell response to hypoxia, immune response and aging. KEGG signaling pathways included JAK-STAT signaling pathway, HIF-1 signaling pathway and IL-17 signaling pathway.Conclusion Through the common key genes and signaling pathways involved in COPD and OP, it provides a theoretical basis for understanding the correlation between the two diseases and for subsequent related research.

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更新日期/Last Update: 1900-01-01