Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan.
BMC Med Genet. 2012 Apr 5;13:25. doi: 10.1186/1471-2350-13-25.
BACKGROUND: The rise of systems biology and availability of highly curated gene and molecular information resources has promoted a comprehensive approach to study disease as the cumulative deleterious function of a collection of individual genes and networks of molecules acting in concert. These "human disease networks" (HDN) have revealed novel candidate genes and pharmaceutical targets for many diseases and identified fundamental HDN features conserved across diseases. A network-based analysis is particularly vital for a study on polygenic diseases where many interactions between molecules should be simultaneously examined and elucidated. We employ a new knowledge driven HDN gene and molecular database systems approach to analyze Inflammatory Bowel Disease (IBD), whose pathogenesis remains largely unknown. METHODS AND RESULTS: Based on drug indications for IBD, we determined sibling diseases of mild and severe states of IBD. Approximately 1,000 genes associated with the sibling diseases were retrieved from four databases. After ranking the genes by the frequency of records in the databases, we obtained 250 and 253 genes highly associated with the mild and severe IBD states, respectively. We then calculated functional similarities of these genes with known drug targets and examined and presented their interactions as PPI networks. CONCLUSIONS: The results demonstrate that this knowledge-based systems approach, predicated on functionally similar genes important to sibling diseases is an effective method to identify important components of the IBD human disease network. Our approach elucidates a previously unknown biological distinction between mild and severe IBD states.
背景:系统生物学的兴起和高度 curated 的基因和分子信息资源的可用性促进了一种全面的方法来研究疾病,因为它是一系列个体基因和协同作用的分子网络的累积有害功能。这些“人类疾病网络”(HDN)揭示了许多疾病的新候选基因和药物靶点,并确定了跨越疾病的基本 HDN 特征。网络分析对于多基因疾病的研究尤为重要,因为许多分子之间的相互作用应该同时进行检查和阐明。我们采用新的知识驱动的 HDN 基因和分子数据库系统方法来分析炎症性肠病(IBD),其发病机制在很大程度上仍然未知。
方法和结果:基于 IBD 的药物适应症,我们确定了 IBD 轻度和重度状态的兄弟姐妹疾病。从四个数据库中检索了大约 1000 个与兄弟姐妹疾病相关的基因。在按数据库中的记录频率对基因进行排序后,我们分别获得了与轻度和重度 IBD 状态高度相关的 250 和 253 个基因。然后,我们计算了这些基因与已知药物靶点的功能相似性,并检查和展示了它们作为 PPI 网络的相互作用。
结论:结果表明,这种基于对兄弟姐妹疾病重要的功能相似基因的知识驱动系统方法是识别 IBD 人类疾病网络重要组成部分的有效方法。我们的方法阐明了轻度和重度 IBD 状态之间以前未知的生物学区别。
BMC Med Genet. 2012-4-5
BMC Med Genomics. 2020-2-24
Eur Rev Med Pharmacol Sci. 2015-11
United European Gastroenterol J. 2024-12
J Crohns Colitis. 2022-8-30
World J Gastroenterol. 2011-7-14
Nature. 2011-6-15
J Crohns Colitis. 2008-3
Nucleic Acids Res. 2011-1
BMC Med Genomics. 2010-10-29