Elucidating the molecular landscape of centronuclear myopathies in mouse models: an integrative multi-omics and network analysis

Simon, A.; Gineste, C.; Reiss, D.; Thompson, J.; Laporte, J.

doi:10.1101/2025.01.03.631202

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bioRxiv · 10.1101/2025.01.03.631202

Elucidating the molecular landscape of centronuclear myopathies in mouse models: an integrative multi-omics and network analysis

Simon, A.·Gineste, C.·Reiss, D.·Thompson, J.·Laporte, J.

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Abstract

Centronuclear myopathies (CNM) are rare inherited muscle disorders characterized by muscle atrophy, weakness, and altered muscle fiber structure, primarily due to mutations in genes like MTM1, DNM2, and BIN1. The pathomechanisms implicated in CNM are only partially understood, and no curative therapies are available for patients. This study exploits a unique multi-omics dataset and network-based analyses to elucidate the molecular pathways involved in CNM. First, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify gene modules correlated with CNM phenotypes. We find that modules correlated to a positive muscular phenotype were enriched for genes involved in muscle contraction, RNA processes and oxidative phosphorylation, while modules associated with impaired muscle structure and function were enriched in immune response, innervation, vascularization processes, and fatty acid oxidation. Next, we integrated transcriptomic, proteomic, and metabolomic data from the Mtm1-/y mouse model with public knowledge bases using a multilayer network approach and explored the network using a random walk with restart approach. This study revealed novel metabolites that could be targeted through dietary supplementation as potential therapeutic strategies. Our findings demonstrate how multi-omics network analyses can reveal new aspects of CNM pathomechanisms and identify avenues for intervention.

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Simon, A., Gineste, C., Reiss, D., Thompson, J., Laporte, J.. 2025-01-03. Elucidating the molecular landscape of centronuclear myopathies in mouse models: an integrative multi-omics and network analysis. https://doi.org/10.1101/2025.01.03.631202

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