Prof. Peter Claus
SMATHERIA gGmbH – Non-Profit Biomedical Research Institute, Hannover,
Germany & Center of Systems Neuroscience, Hannover, Germany

Abstract

Monogenic diseases are well-suited paradigms for the causal analysis of disease-driving molecular patterns. Spinal Muscular Atrophy (SMA) is a monogenic disease caused by mutations of the Survival of Motoneuron gene (SMN1). Deletion of SMN1 leads to decreased levels of the SMN protein and degeneration of the lower motoneurons in the spinal cord and brain stem. The severity of symptoms is correlated with the copy number of a back-up gene, SMN2. However, due to mutations in this gene, expression of SMN2 cannot fully compensate SMN1 loss. Interestingly, SMN protein is expressed ubiquitously and not restricted to the nervous system.

SMA was considered to be a neurodegenerative disease with a predominant neuromuscular phenotype. Recently, SMA has been described as multi-system disorder with new multi-organ phenotypes. Although SMA is a rare disease, three novel therapies have been recently developed and approved. Those therapies are effective, but there is yet no cure for SMA. Consequently, the need for a complementing therapy addressing peripheral signatures of novel SMA phenotypes increases.

Here, we analyzed the systemic character of SMA employing proteomics, phosphoproteomics, translatomics and interactomics from two mouse models with different disease-severities. This systems approach revealed sub-networks and proteins characterizing 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.