: 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.

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

Paganin, Martina;Sharma, Gaurav;Cieri, Federica;Santonicola, Pamela;Di Schiavi, Elia;Viero, Gabriella;
2024

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.
2024
Istituto di Bioscienze e Biorisorse - IBBR - Sede Secondaria Napoli
Istituto di Biofisica - IBF - Sede Secondaria Trento
Istituto di Biofisica - IBF
metabolomics
monogenic disease
network analysis
phosphoproteomics
spinal muscular atrophy
translatomics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/513873
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