Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes

Iker Núñez-Carpintero, Maria Rigau, Mattia Bosio, Emily O’Connor, Sally Spendiff, Yoshiteru Azuma, Ana Topf, Rachel Thompson, Peter A. C. ’t Hoen, Teodora Chamova, Ivailo Tournev, Velina Guergueltcheva, Steven Laurie, Sergi Beltran, Salvador Capella-Gutiérrez, Davide Cirillo (), Hanns Lochmüller and Alfonso Valencia
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Iker Núñez-Carpintero: Barcelona Supercomputing Center (BSC)
Maria Rigau: Barcelona Supercomputing Center (BSC)
Mattia Bosio: Barcelona Supercomputing Center (BSC)
Emily O’Connor: Children’s Hospital of Eastern Ontario Research Institute
Sally Spendiff: Children’s Hospital of Eastern Ontario Research Institute
Yoshiteru Azuma: Yokohama City University Graduate School of Medicine
Ana Topf: Newcastle University
Rachel Thompson: Children’s Hospital of Eastern Ontario Research Institute
Peter A. C. ’t Hoen: Radboud university medical center
Teodora Chamova: Alexandrovska University Hospital, Medical University-Sofia
Ivailo Tournev: Alexandrovska University Hospital, Medical University-Sofia
Velina Guergueltcheva: Sofia University St. Kliment Ohridski
Steven Laurie: Barcelona Institute of Science and Technology (BIST)
Sergi Beltran: Barcelona Institute of Science and Technology (BIST)
Salvador Capella-Gutiérrez: Barcelona Supercomputing Center (BSC)
Davide Cirillo: Barcelona Supercomputing Center (BSC)
Hanns Lochmüller: Children’s Hospital of Eastern Ontario Research Institute
Alfonso Valencia: Barcelona Supercomputing Center (BSC)

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: Abstract Exploring the molecular basis of disease severity in rare disease scenarios is a challenging task provided the limitations on data availability. Causative genes have been described for Congenital Myasthenic Syndromes (CMS), a group of diverse minority neuromuscular junction (NMJ) disorders; yet a molecular explanation for the phenotypic severity differences remains unclear. Here, we present a workflow to explore the functional relationships between CMS causal genes and altered genes from each patient, based on multilayer network community detection analysis of complementary biomedical information provided by relevant data sources, namely protein-protein interactions, pathways and metabolomics. Our results show that CMS severity can be ascribed to the personalized impairment of extracellular matrix components and postsynaptic modulators of acetylcholine receptor (AChR) clustering. This work showcases how coupling multilayer network analysis with personalized -omics information provides molecular explanations to the varying severity of rare diseases; paving the way for sorting out similar cases in other rare diseases.

Date: 2024
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DOI: 10.1038/s41467-024-45099-0

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