中国组织工程研究

中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (35): 6615-6618.doi: 10.3969/j.issn.1673-8225.2011.35.037

• 骨与关节学术探讨 academic discussion of the bone and joint • 上一篇    下一篇

挖掘与类风湿病相关基因功能模块及模块的拓扑性质

华  琳，周  萍，刘  红   

  1. 首都医科大学生物医学工程学院，北京市  100069
  • 收稿日期:2011-03-16 修回日期:2011-07-06 出版日期:2011-08-27 发布日期:2011-08-27
  • 作者简介:华琳☆，女，1973年生，北京市人，汉族，2010年首都医科大学毕业，博士，讲师，主要从事生物统计与生物信息学方面的研究。 hualin7750@yahoo.com.cn
  • 基金资助:

    北京市教育委员会科技计划面上项目(已获批：KM201210025)。

Mining gene functional modules associated with rheumatoid arthritis and their corresponding topological properties analysis

Hua Lin, Zhou Ping, Liu Hong   

  1. School of Biomedical Engineering, Capital Medical University, Beijing  100069, China
  • Received:2011-03-16 Revised:2011-07-06 Online:2011-08-27 Published:2011-08-27
  • About author:Hua Lin☆, Doctor, Lecturer, School of Biomedical Engineering, Capital Medical University, Beijing 100069, China hualin7750@yahoo.com.cn
  • Supported by:

    the Science and Technology General Program of Beijing Education Committee, No. KM201210025*

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摘要：

背景：类风湿病是一种复杂的多基因遗传病，很多传统的遗传学方法难以分析高通量的类风湿病数据，从而挖掘出与疾病相关的遗传标记。
目的：挖掘与类风湿病相关的基因功能模块及研究基因功能模块的拓扑性质。
方法：对类风湿性病数据(WTCCC数据)先提取风险SNP并将风险SNP通过UCSC数据库映射到基因上，此后又将基因映射到蛋白质网络中，通过对网络结构的分析获得基因功能模块，特别对一些显著的基因功能模块进行了拓扑性质的研究。
结果与结论：这些风险基因功能模块的拓扑性质与参考的KEGG通路数据库有显著的不同。

关键词: 类风湿, 基因模块, 拓扑性质, 蛋白质网络, KEGG通路数据库

Abstract:

BACKGROUND: Rheumatoid arthritis (RA) is a complex polygene genetic disease. High throughput SNP genotype data made traditional genetics analysis get into trouble to identify important markers associated with disease.
OBJECTIVE: To mine gene functional modules associated with RA and to perform their corresponding topological properties analysis.
METHODS: For GWA data set-Wellcome Trust Case Control Consortium (WTCCC) for RA, we extracted risk SNPs firstly and mapped these risk SNPs to genes with UCSC database. The acquired risk genes were mapped to protein-protein interaction network and the gene function modules were extracted by analyzing the structure of network. Especially, for some significant risk gene modules, we focused on their topological properties analysis.
RESULTS AND CONCLUSION: When comparing the network topological properties of the gene function modules with pathways from the KEGG database, we found that they clearly differ from those of most disease-related KEGG pathways.

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