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 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.