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A nomenclature and classification for the congenital myasthenic syndromes: preparing for FAIR data in the genomic era

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dc.contributor.author Thompson, Rachel
dc.contributor.author Abicht, Angela
dc.contributor.author Beeson, David
dc.contributor.author Engel, Andrew G.
dc.contributor.author Eymard, Bruno
dc.contributor.author Maxime, Emmanuel
dc.contributor.author Lochmüller, Hanns
dc.date.accessioned 2019-11-28T08:29:19Z
dc.date.available 2019-11-28T08:29:19Z
dc.date.issued 2018
dc.identifier.citation Thompson R, Abicht A, Beeson D, Engel AG, Eymard B, Maxime E, Lochmüller H. A nomenclature and classification for the congenital myasthenic syndromes: preparing for FAIR data in the genomic era. Orphanet J Rare Dis. 2018; 13(1):211. DOI 10.1186/s13023-018-0955-7
dc.identifier.issn 1750-1172
dc.identifier.uri http://hdl.handle.net/10230/43028
dc.description.abstract Background: Congenital myasthenic syndromes (CMS) are a heterogeneous group of inherited neuromuscular disorders sharing the common feature of fatigable weakness due to defective neuromuscular transmission. Despite rapidly increasing knowledge about the genetic origins, specific features and potential treatments for the known CMS entities, the lack of standardized classification at the most granular level has hindered the implementation of computer-based systems for knowledge capture and reuse. Where individual clinical or genetic entities do not exist in disease coding systems, they are often invisible in clinical records and inadequately annotated in information systems, and features that apply to one disease but not another cannot be adequately differentiated. Results: We created a detailed classification of all CMS disease entities suitable for use in clinical and genetic databases and decision support systems. To avoid conflict with existing coding systems as well as with expert-defined group-level classifications, we developed a collaboration with the Orphanet nomenclature for rare diseases, creating a clinically understandable name for each entity and placing it within a logical hierarchy that paves the way towards computer-aided clinical systems and improved knowledge bases for CMS that can adequately differentiate between types and ascribe relevant expert knowledge to each. Conclusions: We suggest that data science approaches can be used effectively in the clinical domain in a way that does not disrupt preexisting expert classification and that enhances the utility of existing coding systems. Our classification provides a comprehensive view of the individual CMS entities in a manner that supports differential diagnosis and understanding of the range and heterogeneity of the disease but that also enables robust computational coding and hierarchy for machine-readability. It can be extended as required in the light of future scientific advances, but already provides the starting point for the creation of FAIR (Findable, Accessible, Interoperable and Reusable) knowledge bases of data on the congenital myasthenic syndromes.
dc.description.sponsorship RT and HL received funding from the European Union, FP7 Grant No. 30544: RD-Connect and Horizon 2020 Grant No. 779257: Solve-RD, and the UK Medical Research Council (MRC) Centre for Neuromuscular Diseases (G1002274, grant ID 98482). AE received funding from NIH Grant NS109491. The funding bodies had no role in study design or execution or in writing the manuscript.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher BioMed Central
dc.relation.ispartof Orphanet J Rare Dis. 2018; 13(1):211
dc.rights © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title A nomenclature and classification for the congenital myasthenic syndromes: preparing for FAIR data in the genomic era
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1186/s13023-018-0955-7
dc.subject.keyword CMS
dc.subject.keyword Classification
dc.subject.keyword Coding
dc.subject.keyword Congenital myasthenic syndromes
dc.subject.keyword Neuromuscular disease
dc.subject.keyword Neuromuscular junction
dc.subject.keyword Nomenclature
dc.subject.keyword Nosology
dc.subject.keyword Ontology
dc.subject.keyword Rare disease
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/779257
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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