Monogenic diseases are well-suited paradigms for the causal analysis of disease-driving molecular patterns. Spinal muscular atrophy (SMA) is one such monogenic model, caused by mutation or deletion of the survival of motor neuron 1 (SMN1) gene. Although several functions of the SMN protein have been studied, single functions and pathways alone do not allow the identification of crucial disease-driving molecules. Here, we analysed the systemic characteristics of SMA, using proteomics, phosphoproteomics, translatomics and interactomics, from two mouse models with different disease severities and genetics. This systems approach revealed subnetworks and proteins characterizing commonalities and differences of both models. To link the identified molecular networks with the disease-causing SMN protein, we combined SMN-interactome data with both proteomes, creating a comprehensive representation of SMA. By this approach, disease hubs and bottlenecks between SMN and downstream pathways could be identified. Linking a disease-causing molecule with widespread molecular dysregulations via multiomics is a concept for analyses of monogenic diseases.

中文翻译：

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单基因疾病的系统复杂性：脊髓性肌萎缩症的分子网络


单基因疾病非常适合对疾病驱动分子模式进行因果分析。脊髓性肌萎缩症 （SMA） 就是这样一种单基因模型，由运动神经元 1 （SMN1） 基因存活的突变或缺失引起。尽管已经研究了 SMN 蛋白的多种功能，但单独的功能和途径并不能识别关键的疾病驱动分子。在这里，我们使用蛋白质组学、磷酸化蛋白质组学、跨解剖学和昆虫间学分析了来自不同疾病严重程度和遗传学的两种小鼠模型的 SMA 的系统特征。这种系统方法揭示了表征两种模型的共性和差异性的子网络和蛋白质。为了将已鉴定的分子网络与致病的 SMN 蛋白联系起来，我们将 SMN 相互作用组数据与两个蛋白质组相结合，创建了 SMA 的全面表示。通过这种方法，可以确定 SMN 和下游途径之间的疾病中心和瓶颈。通过多组学将致病分子与广泛的分子失调联系起来是分析单基因疾病的一个概念。