年龄对骨折愈合影响的生物信息学分析  

Using bioinformatics to analyze the effect of age on fracture healing

作　　者：王顺义[1] 李辉[1] 胡长清[1] 任东良[1] 马伟松[1] 李伟锋[1] 于涛[1] 

机构地区：[1]保定市第一中心医院骨一科,071000

出　　处：《天津医药》2015年第6期616-619,I0001,共5页Tianjin Medical Journal

摘　　要：目的探索年龄对骨折愈合速度的影响,并寻找在年龄对骨折愈合速度产生影响的过程中起重要作用的基因和通路。方法利用R编程语言,分别找到在各时间点(未骨折,骨折后3 d、1周、2周、4周和6周)26周龄大鼠和52周龄大鼠相对于6周龄大鼠的差异表达基因,通过比较这12组差异表达基因,找到能够使年龄对骨折愈合产生影响的基因,利用DAVID数据库对这些基因进行功能注释,并通过STRING数据库构建这些基因的PPI网络。结果未骨折、骨折后2周、4周、6周,52周龄大鼠的差异表达基因均多于26周龄大鼠;骨折后6周,26周龄大鼠只有4个差异表达基因,而52周龄大鼠中有99个。这99个差异表达基因主要富集于与骨骼生长、免疫和炎症等相关的生物过程,富集的KEGG通路有2条:ECM-receptor interaction和Arachidonic acid metabolism。Pcna、Casp3和Fn1等在PPI网络中与其他基因联系较密切。结论 Pcna、Casp3和Fn1等基因可能在骨折愈合中起重要作用,其可能通过影响ECM-receptor interaction和Arachidonic acid metabolism等通路来发挥作用。Objective To explore the effect of age on the fracture healing through bioinformatical analysis of gene ex-pression data in GEO, and to screen critical molecular targets and pathways involved in this process. Methods Through R programming language, we identified different expressed genes between 26/52 week old rats and 6 week old rats in every time points of the experiment （No fracture;3 days, 1 week, 2 weeks, 4 weeks and 6 weeks after fracture）. By comparison of these different expressed genes, those genes that may contribute to fracture healing were identified. Function annotation was conducted based on DAVID database and PPI network that was constructed via STRING database. Results Compared with 6 week old rat, 52 week old rat show more different genes at 2, 4 and 6 weeks after fracture as well as more than intact rats. At the time point of 6 weeks after fracture, 26 week old rat present 4 different genes while 52 week old rat present 99 differ-ent genes compared with 6 week old rat. We totally found 99 genes that might play important roles in the process of fracture healing. These genes involved in biological process related to bone healing, immune, inflammatory and etc. Also, two screened gene enriched KEGG pathways were identified： ECM-receptor interaction and Arachidonic acid metabolism. Through the analysis of PPI network, Pcna, Fn1, Casp3 and etc, who present high density connectivity in PPI network, were screened out. Conclusion Pcna, Casp3 and Fn1 and etc might play important roles in fracture healing through affecting ECM-receptor interaction and Arachidonic acid metabolism.

关 键 词：计算生物学 骨折 年龄因素 R编程语言 通路 PPI网络 

分 类 号：Q318.04[生物学—遗传学]