Network Medicine has improved the mechanistic understanding of disease, offering quantitative insights into disease mechanisms, comorbidities, and novel diagnostic tools and therapeutic treatments. Yet, most network-based approaches rely on a comprehensive map of protein-protein interactions, ignoring interactions mediated by non-coding RNAs (ncRNAs). Here, we systematically combine experimentally confirmed binding interactions mediated by ncRNA with protein-protein interactions, constructing the first comprehensive network of all physical interactions in the human cell. We find that the inclusion of ncRNA, expands the number of genes in the interactome by 46% and the number of interactions by 107%, significantly enhancing our ability to identify disease modules. Indeed, we find that 132 diseases, lacked a statistically significant disease module in the protein-based interactome, but have a statistically significant disease module after inclusion of ncRNA-mediated interactions, making these diseases accessible to the tools of network medicine. We show that the inclusion of ncRNAs helps unveil disease-disease relationships that were not detectable before and expands our ability to predict comorbidity patterns between diseases. Taken together, we find that including non-coding interactions improves both the breath and the predictive accuracy of network medicine.
翻译:网络医学提高了对疾病的机械理解,提供了对疾病机制、发病率和新型诊断工具及治疗方法的定量洞察力。然而,大多数网络方法依赖于蛋白质-蛋白质互动的全面图,忽视了由非编码RNAs(ncRNAs)调解的相互作用。 在这里,我们系统地将NcRNA与蛋白质-蛋白互动的经实验确认的束缚性互动与蛋白质-蛋白互动相结合,构建了人类细胞中所有物理互动的第一个综合网络。我们发现,纳入ncRNA有助于披露互动中46%的基因数量和107%的互动数量,大大增强了我们识别疾病模块的能力。 事实上,我们发现有132种疾病,在以蛋白质为基础的互动体中缺乏具有统计意义的疾病模块,但在纳入NcRNA调解的相互作用之后,有一个具有统计意义的疾病模块,使这些疾病能够被网络医学工具所利用。我们发现,纳入NcRNAs有助于披露以前无法检测到的疾病-困扰关系以及107%的互动数量,大大增强了我们识别疾病模式的能力。