دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes
المؤلفون: 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, Alfonso Valencia
المصدر: Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
بيانات النشر: Nature Portfolio, 2024.
سنة النشر: 2024
المجموعة: LCC:Science
مصطلحات موضوعية: Science
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2041-1723
العلاقة: https://doaj.org/toc/2041-1723Test
DOI: 10.1038/s41467-024-45099-0
الوصول الحر: https://doaj.org/article/da340b3b30af42679f99a2df69ba8241Test
رقم الانضمام: edsdoj.340b3b30af42679f99a2df69ba8241
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20411723
DOI:10.1038/s41467-024-45099-0