The systemic complexity of a monogenic disease: the molecular network of spinal muscular atrophy.

ABSTRACT

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 to identify critical disease-driving molecules. Here, we analyzed the systemic characteristics of SMA employing proteomics, phosphoproteomics, translatomics and interactomics from two mouse models with different disease-severities and genetics. This systems approach revealed sub-networks 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.