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Uncovering disease mechanisms through network biology in the era of next generation sequencing.

机译:在下一代测序时代通过网络生物学揭示疾病机制。

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摘要

Characterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and to reveal both new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced contradictory results. Here we have explored the causes of these discrepancies and assessed the relationship between the network roles of disease genes and their tolerance to deleterious germline variants in human populations leveraging on: the abundance of interactome resources, a comprehensive catalog of disease genes and exome variation data. We found that the most salient network features of disease genes are driven by cancer genes and that genes related to different types of diseases play network roles whose centrality is inversely correlated to their tolerance to likely deleterious germline mutations. This proved to be a multiscale signature, including global, mesoscopic and local network centrality features. Cancer driver genes, the most sensitive to deleterious variants, occupy the most central positions, followed by dominant disease genes and then by recessive disease genes, which are tolerant to variants and isolated within their network modules.
机译:在生物网络的背景下表征疾病基因的行为,有可能阐明疾病的机制,并揭示新的候选疾病基因和治疗靶标。先前针对疾病基因网络特性的研究产生了矛盾的结果。在这里,我们利用以下方面评估了这些差异的原因,并评估了疾病基因的网络角色与其对人群中有害种系变异的耐受性之间的关系:交互作用资源丰富,疾病基因和外显子组变异数据的全面目录。我们发现,疾病基因的最显着网络特征是由癌症基因驱动的,而与不同类型疾病相关的基因则扮演着网络角色,其中心地位与其对可能有害的种系突变的耐受性成反比。事实证明,这是一个多尺度的签名,包括全球,介观和本地网络的中心性特征。对有害变异最敏感的癌症驱动基因占据最中心的位置,其次是显性疾病基因,然后是隐性疾病基因,它们对变异具有耐受性并被隔离在其网络模块中。

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