摘要
目的通过生物信息学策略探讨骨质疏松症(OP)与炎症性肠病(IBD)间的基因相关性。方法分别以“osteoporosis”及“Inflammatory bowel disease”为关键词从网络疾病数据库(DisGeNET、TTD、OMIM、GeneCards)中遴选相关基因,去重后将两组靶基因进行映射得到交集靶点并使用R软件进行GO功能及KEGG通路富集分析,通过string网站分析得到蛋白相互作用网络图,通过cytoHubba插件中的MCC算法筛选出关键靶点,借助网络分析工具Networkanalyst预测关联miRNA并绘制网络图。结果获得OP和IBD相关靶点分别为1779和2779个,获得交集靶点869个,R软件富集得到4278项GO功能富集结果及173条KEGG信号通路,共筛选到10个关键靶点。结论IL6、IL10、IL17A、TNF、CSF2、IL4、IL1B、CXCL8、IFNG、IL13作用的炎症通路的激活可能是OP与IBD的共同病因,miR-98-5p、miR-335-5p、miR-24-3p和miR-106a-5p可能作为治疗IBD和OP的新手段。
Objective To explore the genetic association between osteoporosis(OP)and inflammatory bowel disease(IBD)by bioinformatics strategy.Methods We screened related genes in the disease databases,including DisGeNET,TTD,OMIM,and GeneCards,using key words"OP"and"IBD".After deduplicating,the two groups of target genes were mapped to obtain intersection targets,and R software was used for GO enrichment analysis and KEGG pathway analysis.The protein interaction network was obtained through string website,and the key targets were screened by MCC algorithm in cytoHubba plug-in.Network analysis tool Networkanalyst was used to predict associated miRNA and draw network diagram.Results A total of 1779 and 2779 targets related to OP and IBD were screened out respectively,and 869 intersection targets were obtained.In addition,4278 results of GO enrichment using R software and 173 KEGG signal pathways were obtained,and a total of 10 key targets were screened.Conclusion Activation of active inflammatory pathways measured by IL6,IL10,IL17A,TNF,CSF2,IL4,IL1B,CXCL8,IFNG,and IL13 may be the common cause of OP and IBD.Meanwhile,miR-98-5p,miR-335-5p,miR-24-3p and miR-106a-5p may be selected as new approaches in the treatments for IBD and OP.
作者
常裕绅
张子鸣
李振宇
安娟
何瀚威
匡建军
CHANG Yu-shen;ZHANG Zi-ming;LI Zhen-yu;AN Juan;HE Han-wei;KUANG Jian-jun(Graduate School of Hu'nan University of Traditional Chinese Medicine,Changsha 410208,China;Hu'nan Academy of Traditional Chinese Medicine,Changsha 410006,China)
出处
《解放军医药杂志》
CAS
2022年第9期50-54,共5页
Medical & Pharmaceutical Journal of Chinese People’s Liberation Army
基金
湖南省自然科学基金(2022JJ60076)
长沙市科技计划项目(kh2201063)。