Department of Gastroenterology & Multidisciplinary Research Laboratory, Federal University of Rio de Janeiro, Rio de Janeiro 21941-913, Brazil.
Department of Pathobiology, Lerner Research Institute, Department of Gastroenterology and Hepatology, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA.
Nat Rev Gastroenterol Hepatol. 2017 Dec;14(12):739-749. doi: 10.1038/nrgastro.2017.110. Epub 2017 Aug 23.
Crohn's disease and ulcerative colitis are prototypical complex diseases characterized by chronic and heterogeneous manifestations, induced by interacting environmental, genomic, microbial and immunological factors. These interactions result in an overwhelming complexity that cannot be tackled by studying the totality of each pathological component (an '-ome') in isolation without consideration of the interaction among all relevant -omes that yield an overall 'network effect'. The outcome of this effect is the 'IBD interactome', defined as a disease network in which dysregulation of individual -omes causes intestinal inflammation mediated by dysfunctional molecular modules. To define the IBD interactome, new concepts and tools are needed to implement a systems approach; an unbiased data-driven integration strategy that reveals key players of the system, pinpoints the central drivers of inflammation and enables development of targeted therapies. Powerful bioinformatics tools able to query and integrate multiple -omes are available, enabling the integration of genomic, epigenomic, transcriptomic, proteomic, metabolomic and microbiome information to build a comprehensive molecular map of IBD. This approach will enable identification of IBD molecular subtypes, correlations with clinical phenotypes and elucidation of the central hubs of the IBD interactome that will aid discovery of compounds that can specifically target the hubs that control the disease.
克罗恩病和溃疡性结肠炎是典型的复杂疾病,其特征为慢性和异质性表现,由相互作用的环境、基因组、微生物和免疫学因素引起。这些相互作用导致了压倒性的复杂性,如果不考虑所有相关组学之间的相互作用,而仅仅研究每个病理成分(一个“组学”)的整体,就无法解决这种复杂性。这种相互作用的结果是“炎症性肠病相互作用组”,定义为一种疾病网络,其中单个“组学”的失调导致由功能失调的分子模块介导的肠道炎症。为了定义炎症性肠病相互作用组,需要新的概念和工具来实施系统方法;这是一种无偏见的数据驱动的整合策略,可揭示系统的关键参与者,确定炎症的中心驱动因素,并能够开发靶向治疗方法。现已有能够查询和整合多个“组学”的强大生物信息学工具,从而能够整合基因组、表观基因组、转录组、蛋白质组、代谢组和微生物组信息,以构建炎症性肠病的综合分子图谱。这种方法将能够识别炎症性肠病的分子亚型,与临床表型相关联,并阐明炎症性肠病相互作用组的中心枢纽,这将有助于发现可以特异性靶向控制疾病的枢纽的化合物。
Nat Rev Gastroenterol Hepatol. 2017-8-23
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