Barcelona Supercomputing Center (BSC), Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain.
MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK.
Nat Commun. 2024 Feb 28;15(1):1227. doi: 10.1038/s41467-024-45099-0.
Exploring the molecular basis of disease severity in rare disease scenarios is a challenging task provided the limitations on data availability. Causative genes have been described for Congenital Myasthenic Syndromes (CMS), a group of diverse minority neuromuscular junction (NMJ) disorders; yet a molecular explanation for the phenotypic severity differences remains unclear. Here, we present a workflow to explore the functional relationships between CMS causal genes and altered genes from each patient, based on multilayer network community detection analysis of complementary biomedical information provided by relevant data sources, namely protein-protein interactions, pathways and metabolomics. Our results show that CMS severity can be ascribed to the personalized impairment of extracellular matrix components and postsynaptic modulators of acetylcholine receptor (AChR) clustering. This work showcases how coupling multilayer network analysis with personalized -omics information provides molecular explanations to the varying severity of rare diseases; paving the way for sorting out similar cases in other rare diseases.
探索罕见病情况下疾病严重程度的分子基础是一项具有挑战性的任务，因为数据可用性有限。先天性肌无力综合征（CMS）是一组不同的神经肌肉接头（NMJ）疾病，其致病基因已被描述；然而，对于表型严重程度差异的分子解释仍不清楚。在这里，我们提出了一种工作流程，基于通过相关数据源（即蛋白质-蛋白质相互作用、途径和代谢组学）提供的互补生物医学信息的多层次网络社区检测分析，来探索 CMS 致病基因与每个患者中改变基因之间的功能关系。我们的结果表明，CMS 的严重程度可以归因于细胞外基质成分和乙酰胆碱受体（AChR）聚集的突触后调节剂的个性化损伤。这项工作展示了如何将多层次网络分析与个性化组学信息相结合，为罕见病的不同严重程度提供分子解释；为在其他罕见病中梳理类似病例铺平了道路。
