University Children's Hospital, University Medical Center Hamburg Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Department of Molecular Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University Munich, Lindwurmstrasse 4, 80336, Munich, Germany.
J Inherit Metab Dis. 2018 May;41(3):285-296. doi: 10.1007/s10545-018-0140-0. Epub 2018 Feb 5.
The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.
先天性代谢缺陷(IEM)群体表现出明显的异质性,IEM 几乎可以影响人体的所有功能和器官;然而,IEM 的共同点是它们相关的蛋白质在代谢中发挥作用。大多数蛋白质通过与其他蛋白质相互作用来执行细胞功能,因此它们被组织在生物网络中。因此,疾病很少是单个基因突变的结果,而是相关细胞网络中受到干扰的结果。将多组学和数据库信息整合到生物网络中的系统方法成功地扩展了我们对复杂疾病的认识,但基于网络的策略很少应用于 IEM 的研究。我们在蛋白质组范围内分析了 IEM,发现 IEM 相关蛋白在人类蛋白质相互作用的相互作用组中作为相互连接的模块网络组织,即 IEM 相互作用组。某些 IEM 疾病组形成了自成一体的疾病模块,这些模块高度相互关联。另一方面,我们观察到 IEM 相互作用组中包含来自许多不同疾病组的蛋白质的疾病模块。此外,我们探讨了 IEM 和非 IEM 疾病基因之间的重叠,并应用网络医学方法研究共同的生物学途径、临床症状和与药物靶点的联系。提供的资源可能有助于阐明新的 IEM 的分子机制,揭示与疾病相关的突变的意义,识别新的生物标志物,并开发新的治疗策略。