Díaz-Santiago, ElenaClaros, M. GonzaloYahyaoui, Raquelde Diego-Otero, YolandaCalvo, RocíoHoenicka, JanetPalau, FrancescRanea, Juan A. G.Perkins, James R.2022-05-242022-05-242021-04-19Díaz-Santiago E, Claros MG, Yahyaoui R, de Diego-Otero Y, Calvo R, Hoenicka J, et al. Decoding Neuromuscular Disorders Using Phenotypic Clusters Obtained From Co-Occurrence Networks. Front Mol Biosci. 2021 Apr 19;8:635074https://hdl.handle.net/10668/3667Neuromuscular disorders (NMDs) represent an important subset of rare diseases associated with elevated morbidity and mortality whose diagnosis can take years. Here we present a novel approach using systems biology to produce functionally-coherent phenotype clusters that provide insight into the cellular functions and phenotypic patterns underlying NMDs, using the Human Phenotype Ontology as a common framework. Gene and phenotype information was obtained for 424 NMDs in OMIM and 126 NMDs in Orphanet, and 335 and 216 phenotypes were identified as typical for NMDs, respectively. Elevated serum creatine kinase was the most specific to NMDs, in agreement with the clinical test of elevated serum creatinine kinase that is conducted on NMD patients. The approach to obtain co-occurring NMD phenotypes was validated based on co-mention in PubMed abstracts. A total of 231 (OMIM) and 150 (Orphanet) clusters of highly connected co-occurrent NMD phenotypes were obtained. In parallel, a tripartite network based on phenotypes, diseases and genes was used to associate NMD phenotypes with functions, an approach also validated by literature co-mention, with KEGG pathways showing proportionally higher overlap than Gene Ontology and Reactome. Phenotype-function pairs were crossed with the co-occurrent NMD phenotype clusters to obtain 40 (OMIM) and 72 (Orphanet) functionally coherent phenotype clusters. As expected, many of these overlapped with known diseases and confirmed existing knowledge. Other clusters revealed interesting new findings, indicating informative phenotypes for differential diagnosis, providing deeper knowledge of NMDs, and pointing towards specific cell dysfunction caused by pleiotropic genes. This work is an example of reproducible research that i) can help better understand NMDs and support their diagnosis by providing a new tool that exploits existing information to obtain novel clusters of functionally-related phenotypes, and ii) takes us another step towards personalised medicine for NMDs.enAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/ClusterCo-occurrence analysisNetwork analysisNeuromuscular disordersPhenotypeRare diseaseFenotipoEnfermedades rarasMedical Subject Headings::Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::HumansMedical Subject Headings::Chemicals and Drugs::Heterocyclic Compounds::Heterocyclic Compounds, 1-Ring::Azoles::Imidazoles::CreatinineMedical Subject Headings::Diseases::Pathological Conditions, Signs and Symptoms::Pathologic Processes::Disease Attributes::Rare DiseasesMedical Subject Headings::Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnosis, DifferentialMedical Subject Headings::Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biology::Genetics::Genetic Research::Gene OntologyMedical Subject Headings::Phenomena and Processes::Genetic Phenomena::Inheritance Patterns::Genetic PleiotropyMedical Subject Headings::Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biology::Computational Biology::Systems BiologyMedical Subject Headings::Information Science::Information Science::Medical Informatics::Medical Informatics Applications::Information Systems::Databases as Topic::Databases, Factual::Databases, GeneticMedical Subject Headings::Phenomena and Processes::Genetic Phenomena::PhenotypeMedical Subject Headings::Chemicals and Drugs::Enzymes and Coenzymes::Enzymes::Transferases::Phosphotransferases::Phosphotransferases Nitrogenous Group Acceptor::Creatine Kinaseresearch article34046427open accessFenotipoBases de Datos GenéticasFosfotransferasasBiología de SistemasOntología de GenesPleiotropía Genética10.3389/fmolb.2021.6350742296-889XPMC8147726