Literature DB >> 30477555

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

Rachel Thompson1, Angela Abicht2, David Beeson3, Andrew G Engel4, Bruno Eymard5, Emmanuel Maxime6, Hanns Lochmüller7,8,9.   

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.

Entities:  

Keywords:  CMS; Classification; Coding; Congenital myasthenic syndromes; Neuromuscular disease; Neuromuscular junction; Nomenclature; Nosology; Ontology; Rare disease

Mesh:

Year:  2018        PMID: 30477555      PMCID: PMC6260762          DOI: 10.1186/s13023-018-0955-7

Source DB:  PubMed          Journal:  Orphanet J Rare Dis        ISSN: 1750-1172            Impact factor:   4.123


Background

Congenital myasthenic syndromes (CMS) are rare inherited neuromuscular disorders characterized by fatigable weakness of skeletal muscle owing to compromised function of the neuromuscular junction (NMJ). First described in the 1940s [1] as a potential rare “familial” form of infantile myasthenia contrasting with the more common autoimmune-mediated myasthenia gravis, the first genetic defects associated with the condition were reported in the 1990s [2]. With the advent of next-generation sequencing (NGS), the number of genetic defects reported as causative of a CMS phenotype has increased dramatically, with as many as 31 genes now implicated [3]. The known types of CMS range in frequency from more than 1000 individuals to single sporadic reported cases, and around 20 to 40% of cases remain without a genetic diagnosis after exome sequencing [3]. Although all CMS share the common features of NMJ pathology and fatigable weakness, the severity of the disease, its course of progression, specific phenotypic manifestations and even effective treatments are highly variable between the different types. Furthermore, different pathogenic changes within the same gene may result in different pathological processes and therefore markedly different disease manifestations and therapeutic options [4]. Within this complex environment, it is clear not only that precision in diagnosis is important in order to correctly define the disease and institute appropriate treatment, but that precision in coding or classification of this diagnosis is a prerequisite for any attempt at systematizing knowledge and linking it to a specific CMS type. Yet coding and classification has long been a vexed issue in the rare disease field as a whole, going far beyond CMS [5]. Where clinical or genetic entities do not have a named entry in disease coding systems, they are often invisible in clinical records and inadequately annotated in information systems, since features that apply to one disease but not another cannot be adequately differentiated [6]. Coinciding with the dramatic increase in genomic data and computational approaches to diagnosis, recent years have seen the emergence of new data science approaches and their application to clinical problems to allow the systematization of existing and newly generated clinical knowledge in a way that is more accessible to computational analysis. This has been termed the FAIR data approach, an acronym that stands for Findable, Accessible, Interoperable and Reusable and represents the concept that the utility of clinical and research data is dramatically increased if it can be made accessible to reuse by others [7]. Precision in nomenclature terms is just one aspect of making a dataset FAIR, but nevertheless a crucial one in order to attach the right knowledge to the right disease. Our present study aimed to create a comprehensive classification for all CMS disease entities as a starting point that will then allow generation of FAIR-compliant datasets of knowledge about each type.

Methods

We began by defining the CMS disease entities to be considered in the classification. We adopted a broad definition of CMS as any genetic neuromuscular condition manifesting with fatigable weakness of skeletal muscle and apparent NMJ involvement. We defined individual CMS “unique entities” at (a) gene level in cases where the presumed pathomechanism is identical for defects anywhere in a given gene, or (b) sub-gene level in cases where different defects in different regions of the same gene result in different disease manifestations due to differing pathomechanisms (e.g. to differentiate slow-channel from fast-channel syndromes within the same acetylcholine receptor gene). We did not split the classification to account for variable severity, age of onset or incomplete penetrance of phenotypic features where the underlying pathomechanism is the same, and we excluded non-CMS presentations of disorders caused by defects in the same genes that may also cause CMS presentation (e.g. kidney presentations of LAMB2 defects). In the case of genetic entities affecting ubiquitous metabolic pathways (glycosylation defects, mitochondrial defects), some specific mutations cause a primary neuromuscular transmission defect, and these are included in our classification, while other mutations cause wider organ involvement, where the neuromuscular transmission defect may become irrelevant or not detectable (e.g. syndromic congenital disorders of glycosylation, encephalomyopathy), and these are then classified elsewhere. The entities thus defined therefore aim to be those that from a data science perspective are sufficiently granular to allow the mapping of disease to feature and extend the range of knowledge about that specific disease entity. Based on this framework, through a literature review we developed a comprehensive listing of all unique CMS clinical and genetic entities described to date that met our criteria for inclusion. We captured the range of terminology used in the literature to describe or name each entity or group of entities. Using their publicly available online browsers, we then reviewed the most widely used medical and genetic coding systems to establish their coverage of these published CMS disease entities. Table 1 provides details of the coding systems analyzed, the browsers used and the summary results of the search.
Table 1

Coverage of congenital myasthenic syndromes by the major medical coding systems

Coding systemTerminology browser usedCoding for congenital myasthenic syndromes class/categoryCoding for individual CMS types
International Classification of Disease (ICD) Revision 11 https://icd.who.int/browse11/l-m/en 8C61: Congenital myasthenic syndromesNo coding but textual description of four categories:Congenital myasthenic syndrome with presynaptic defect, Synaptic basal lamina-associated CMS, Congenital myasthenia with postsynaptic defect, CMS with glycosylation deficiency, Unidentified CMS.
International Classification of Disease (ICD) Revision 10 http://apps.who.int/classifications/icd10/browse/2016/en G70.2: Congenital and developmental myastheniaNot present
Medical Subject Headings (MeSH) https://meshb.nlm.nih.gov/search C16.320.590: Myasthenic Syndromes, CongenitalNot present
Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT)http://browser.ihtsdotools.org/230672006: Congenital myasthenia (disorder)Not present
Orphanet nomenclature of rare diseases https://www.orpha.net/consor/cgi-bin/Disease.php?lng=EN ORPHA:590: Congenital myasthenic syndromeMost granular level is absent. Subclasses are defined:Postsynaptic congenital myasthenic syndromesPresynaptic congenital myasthenic syndromesSynaptic congenital myasthenic syndromesCongenital myasthenic syndromes with glycosylation defect
Online Mendelian Inheritance in Man (OMIM)http://omim.org/N/ACoding of 28 out of 39 entities with “phenotype MIM number” (for detail see Table 2)No hierarchies/ontological features
Coverage of congenital myasthenic syndromes by the major medical coding systems From the results of the initial stage of the research, we concluded that all existing coding systems had major gaps in coverage, in most cases caused by inadequate levels of granularity, with the most granular entities either completely or partially absent. Given the pressing need to define a fully granular classification for the “data science” purposes described above, we initiated a collaboration with Orphanet to extend the Orphanet nomenclature [8] to include our unique CMS disease entities. We aimed to avoid creation of a competing classification given the multiplicity of systems already in existence, and Orphanet was selected as the most suitable system for this collaboration because it aims to be a fully comprehensive coding system specifically designed for rare disease; it makes use of a hierarchical system or tree-like structure in which disease entities can be grouped in different logical ways; it includes mappings to many other coding systems at appropriate levels of granularity thus ensuring interoperability [9]; and it welcomes collaborations with domain experts for the purposes of extending its nomenclature. Orphanet has published a procedural document [10] for rare disease nomenclature in English that provides detailed guidance for naming entities, which states that names should be based on clinical practice, validated by experts in the field, comprehensive, consistent, and as stable as possible with regard to evolution of scientific knowledge. We therefore defined “descriptive names” for each entity in a manner consistent with the Orphanet guidelines, creating a clinically understandable name for each entity that should be stable notwithstanding the rapid advances in understanding the genetics of CMS. It is important to note that while the descriptive names are valuable from the perspective of human understanding, the essential point is that the disease entities are assigned unique identifiers within the coding system, which enables computer-readability and interoperability with other systems. At the initial stage, the full listing of unique clinical entities that are classed as a CMS according to our definition is a non-hierarchical nosology or “flat” table (Table 2) mapped to the existing coding systems as appropriate. However, since Orphanet allows the creation of a hierarchical classification in which individual disorders may be grouped into one or multiple parent groups based on specific features, we also created an additional table in which we grouped all the unique entities from Table 2 based on etiological or other features (Table 3).
Table 2

Nomenclature proposals for individual CMS disease entities and mapping to pre-existing classifications

Gene involvedProposed descriptive nameOMIM phenotype number and nameTreatment options [4, 11]Existing Orphanet name (group level)Names in literature (group level)Names in literature (entity level)
AGRN Congenital myasthenic syndrome due to agrin deficiency caused by pathogenic variants in AGRN615120: Myasthenic syndrome, congenital, 8; CMS8Alternative/former titles:Myasthenic syndrome, congenital, with pre- and postsynaptic defects; CMSPPDMyasthenic syndrome, congenital, due to agrin deficiencySalbutamol or ephedrine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes AND ORPHA:98914 Presynaptic congenital myasthenic syndromes• Defects in endplate development and maintenance• Agrin deficiency
ALG14 Congenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in ALG14616227: Myasthenic syndrome, congenital, 15; CMS15Alternative/former titles:Myasthenic syndrome, congenital, without tubular aggregates; CMSWTAPyridostigmine as first line; may benefit from addition of 3,4-diaminopyridineORPHA:353327 Congenital myasthenic syndromes with glycosylation defect• Limb-girdle-myasthenia with glycosylation deficiency• CMS due to abnormal glycosylation• Congenital defects of glycosylation• Defects in protein glycosylation• ALG14 myasthenia
ALG2 Congenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in ALG2616228: Myasthenic syndrome, congenital, 14; CMS14Alternative/former titles:Myasthenic syndrome, congenital, with tubular aggregates 3; CMSTA3Pyridostigmine as first line; may benefit from addition of 3,4-diaminopyridineORPHA:353327 Congenital myasthenic syndromes with glycosylation defect• Limb-girdle-myasthenia with glycosylation deficiency• CMS due to abnormal glycosylation• Congenital defects of glycosylation• Defects in protein glycosylation• ALG2 myasthenia
CHAT Congenital myasthenic syndrome due to endplate choline acetyltransferase deficiency caused by pathogenic variants in CHAT254210: Myasthenic syndrome, congenital, 6, presynaptic; CMS6Alternative/former titles:Myasthenic syndrome, presynaptic, congenital, associated with episodic apnea; CMSEACongenital myasthenic syndrome type Ia2, CMS1a2, CMS Ia2,Myasthenia, familial infantile, FIM,Myasthenia gravis, familial infantile, 2, FIMG2,Pyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineORPHA:98914 Presynaptic congenital myasthenic syndromes• CMS with episodic apnea• Synthesis and Recycling of Acetylcholine• Endplate choline acetyltransferase deficiency• CMS with episodic apnea
CHRNA1 Slow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNA1601462: Myasthenic syndrome, congenital, 1a, slow-channel; CMS1aAlternative/former titles:Myasthenic syndrome, congenital, type IIA, CMS2a, CMS 2aFluoxetine or quinidine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Slow-channel syndrome, SCS• Kinetic abnormalities of the AChR
CHRNA1 Fast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by pathogenic variants in CHRNA1608930: Myasthenic syndrome, congenital, 1b, fast-channel; CMS1bMyasthenic syndrome, congenital, 1b, fast-channel; CMS1bPyridostigmine as first line; may benefit from addition of salbutamol / ephedrine or 3,4-diaminopyridine. Avoid β2-adrenergic agonists (fluoxetine / quinidine)ORPHA:98913 Postsynaptic congenital myasthenic syndromes• Fast-channel syndrome, FCS• Kinetic abnormalities of the AChR
CHRNA1 Congenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRNA1N/APyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineN/A• Primary AChR deficiency
CHRNB1 Slow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNB1616313: Myasthenic syndrome, congenital, 2a, slow-channel; CMS2aFluoxetine or quinidine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Slow-channel syndrome, SCS• Kinetic abnormalities of the AChR
CHRNB1 Fast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by pathogenic variants in CHRNB1N/APyridostigmine as first line; may benefit from addition of salbutamol / ephedrine or 3,4-diaminopyridine. Avoid β2-adrenergic agonists (fluoxetine / quinidine)N/A• Fast-channel syndrome, FCS• Kinetic abnormalities of the AChR
CHRNB1 Congenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRNB1616314: Myasthenic syndrome, congenital, 2c, associated with acetylcholine receptor deficiency; CMS2cPyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineORPHA:98913 Postsynaptic congenital myasthenic syndromes• Primary AChR deficiency
CHRND Slow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRND616321: Myasthenic syndrome, congenital, 3a, slow-channel; CMS3aFluoxetine or quinidine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Slow-channel syndrome, SCS• Kinetic abnormalities of the AChR
CHRND Fast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by pathogenic variants in CHRND616322: Myasthenic syndrome, congenital, 3b, fast-channel; CMS3bPyridostigmine as first line; may benefit from addition of salbutamol / ephedrine or 3,4-diaminopyridine. Avoid β2-adrenergic agonists (fluoxetine / quinidine)ORPHA:98913 Postsynaptic congenital myasthenic syndromes• Fast-channel syndrome, FCS• Kinetic abnormalities of the AChR
CHRND Congenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRND616323: Myasthenic syndrome, congenital, 3c, associated with acetylcholine receptor deficiency; CMS3cPyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineORPHA:98913 Postsynaptic congenital myasthenic syndromes• Primary AChR deficiency
CHRND Congenital myasthenic syndrome due to defects in acetylcholine receptor clustering caused by pathogenic variants in CHRNDN/APyridostigmineN/A
CHRNE Slow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNE605809: Myasthenic syndrome, congenital, 4a, slow-channel; CMS4aAlternative/former titles:Congenital myasthenic syndrome type Ia1, CMS1a1, CMS Ia1Fluoxetine or quinidine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Slow-channel syndrome, SCS• Kinetic abnormalities of the AChR
CHRNE Fast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by pathogenic variants in CHRNE616324: Myasthenic syndrome, congenital, 4b, fast-channel; CMS4bPyridostigmine as first line; may benefit from addition of salbutamol / ephedrine or 3,4-diaminopyridine. Avoid β2-adrenergic agonists (fluoxetine / quinidine)ORPHA:98913 Postsynaptic congenital myasthenic syndromes• Fast-channel syndrome, FCS• Kinetic abnormalities of the AChR
CHRNE Congenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRNE608931: Myasthenic syndrome, congenital, 4c, associated with acetylcholine receptor deficiency; CMS4cAlternative/former titles:Myasthenic syndrome, congenital, type ID; CMS1D, CMS ID, Myasthenia, familial infantile, 1, FIM1,Pyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineORPHA:98913 Postsynaptic congenital myasthenic syndromes• Primary AChR deficiency
CHRNE Congenital myasthenic syndrome with kinetic defect due to reduced ion channel conductance caused by pathogenic variants in CHRNEN/APyridostigmineN/A• Kinetic abnormalities of the AChR• Reduced ion channel conductance
COL13A1 Congenital myasthenic syndrome due to collagen 13 defects caused by pathogenic variants in COL13A1616720: Myasthenic syndrome, congenital, 19; CMS19Salbutamol / ephedrine as first line; may benefit from addition of 3,4-diaminopyridine. Pyridostigmine likely ineffective.ORPHA:98913 Postsynaptic congenital myasthenic syndromes• Synaptic and basal-lamina associated syndromes• Synaptic space
COLQ Congenital myasthenic syndrome due to endplate acetylcholinesterase deficiency caused by pathogenic variants in COLQ603034: Myasthenic syndrome, congenital, 5; CMS5Alternative/former titles:Endplate acetylcholinesterase deficiency; EADEngel congenital myasthenic syndromeMyasthenic syndrome, congenital, Engel typeCongenital myasthenic syndrome type IC, CMS1c, CMS ICSalbutamol or ephedrine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98915 Synaptic congenital myasthenic syndromes• Synaptic and basal-lamina associated syndromes• Synaptic space• Endplate AChE deficiency• Endplate acetylcholinesterase deficiency
DOK7 Congenital myasthenic syndrome due to defects in docking protein 7 caused by pathogenic variants in DOK7254300: Myasthenic syndrome, congenital, 10; CMS10Alternative/former titles:Myasthenia, limb-girdle, familial, LGM,Congenital myasthenic syndrome type Ib, CMS1b, CMS Ib, Myasthenic myopathySalbutamol or ephedrine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Defects within the AChR-clustering pathway• Defects in endplate development and maintenance• DOK7-associated limb-girdle-myasthenia• DOK7 CMS• Dok-7 myasthenia
DPAGT1 Congenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in DPAGT1614750: Myasthenic syndrome, congenital, 13; CMS13Alternative/former titles:Myasthenic syndrome, congenital, with tubular aggregates 2; CMSta2Pyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineN/A• Limb-girdle-myasthenia with glycosylation deficiency• CMS due to abnormal glycosylation• Congenital defects of glycosylation• Defects in protein glycosylation• DPAGT1 myasthenia
GFPT1 Congenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in GFPT1610542: Myasthenic syndrome, congenital, 12; CMS12Alternative/former titles:Myasthenic syndrome, congenital, with tubular aggregates 1; CMSTA1Pyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineN/A• Limb-girdle-myasthenia with glycosylation deficiency• CMS due to abnormal glycosylation• Congenital defects of glycosylation• Defects in protein glycosylation• GFPT1 myasthenia
GMPPB Congenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in GMPPBN/A(615352 is for the LGMD phenotype minus the myasthenic features)Pyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineN/A• Limb-girdle-myasthenia with glycosylation deficiency• CMS due to abnormal glycosylation• Congenital defects of glycosylation• Defects in protein glycosylation• GMPPB myasthenia
LAMB2 Congenital myasthenic syndrome due to laminin beta 2 deficiency caused by pathogenic variants in LAMB2N/ASalbutamol or ephedrineORPHA:98915 Synaptic congenital myasthenic syndromes• Synaptic basal lamina-associated syndromes• Laminin beta2 deficiency
LRP4 Congenital myasthenic syndrome due to defects in low-density lipoprotein receptor-related protein 4 caused by pathogenic variants in LRP4616304: Myasthenic syndrome, congenital, 17; CMS17Salbutamol or ephedrine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Defects within the AChR-clustering pathway• Defects in endplate development and maintenance• LRP4 myasthenia
MUSK Congenital myasthenic syndrome due to defects in MuSK caused by pathogenic variants in MUSK616,325: Myasthenic syndrome, congenital, 9, associated with acetylcholine receptor deficiency; CMS9Salbutamol or ephedrine as first line; avoid pyridostigmine / acetylcholinesterase inhibitorsORPHA:98913 Postsynaptic congenital myasthenic syndromes• Defects within the AChR-clustering pathway• Defects in endplate development and maintenance• Congenital MuSK myasthenia• MuSK deficiency
MYO9A Congenital myasthenic syndrome due to a defect in Myosin 9A caused by pathogenic variants in MYO9AN/APyridostigmineORPHA:98914 Presynaptic congenital myasthenic syndromes• Axonal transport• Presynaptic• Myosin 9a deficiency
PLEC1 Congenital myasthenic syndrome due to plectin deficiency caused by pathogenic variants in PLEC1N/APyridostigmineN/A• Other myasthenic syndromes• Plectin deficiency
PREPL Congenital myasthenic syndrome caused by pathogenic variants in PREPL that predict reduced filling of synaptic vesicles with ACh616224: Myasthenic syndrome, congenital, 22; CMS22Alternative/former titles:PREPL deficiencyPyridostigmineN/A• Limb-girdle-myasthenia with glycosylation deficiency• Synthesis and Recycling of Acetylcholine• Other myasthenic syndromes• PREPL deletion syndrome• PREPL deficiency
RAPSN Congenital myasthenic syndrome due to endplate rapsyn deficiency caused by pathogenic variants in RAPSN616326: Myasthenic syndrome, congenital, 11, associated with acetylcholine receptor deficiency; CMS11Alternative/former titles:Myasthenic syndrome, congenital, Ie, CMS1e, CMS IePyridostigmine as first line; may benefit from addition of 3,4-diaminopyridine or salbutamol / ephedrineORPHA:98913 Postsynaptic congenital myasthenic syndromes• Defects within the AChR-clustering pathway• Defects in endplate development and maintenance• Endplate rapsyn deficiency• Rapsyn deficiency• Rapsyn CMS
SCN4A Congenital myasthenic syndrome due to a sodium channel 1.4 defect caused by pathogenic variants in SCN4A614198: Myasthenic syndrome, congenital, 16; CMS16Alternative/former titles:Myasthenic syndrome, congenital, acetazolamide-responsivePyridostigmine as first line; acetazolamide may be helpful for periodic paralysisORPHA:98913 Postsynaptic congenital myasthenic syndromes• Other myasthenic syndromes• Na channel myasthenia• Sodium channel myasthenia
SLC18A3 Congenital myasthenic syndrome due to a vesicular acetylcholine transporter defect caused by pathogenic variants in SLC18A3617239: Myasthenic syndrome, congenital, 21, presynaptic; CMS21PyridostigmineORPHA:98914 Presynaptic congenital myasthenic syndromes• Synthesis and recycling of acetylcholine• Vesicular ACh transporter deficiency
SLC25A1 Congenital myasthenic syndrome due to a mitochondrial citrate carrier defect caused by pathogenic variants in SLC25A1N/APyridostigmine as first line; may benefit from addition of 3,4-diaminopyridineORPHA:98914 Presynaptic congenital myasthenic syndromes• Other syndromes• Mitochondrial citrate carrier deficiency
SLC5A7 Congenital myasthenic syndrome due to a choline transporter defect caused by pathogenic variants in SLC5A7617143: Myasthenic syndrome, congenital, 20, presynaptic; CMS20Pyridostigmine as first line; may benefit from addition of salbutamol / ephedrineORPHA:98914 Presynaptic congenital myasthenic syndromes• Synthesis and recycling of acetylcholine• High-affinity presynaptic choline transporter
SNAP25B Congenital myasthenic syndrome due to a synaptosomal-associated protein 25 defect caused by pathogenic variants in SNAP25B616330: Myasthenic syndrome, congenital, 18; CMS18Alternative/former titles:Myasthenic syndrome, congenital, 18, with intellectual disability and ataxia3,4-diaminopyridineN/A• Synaptic vesicles exocytosis• Presynaptic• SNAP25-associated CMS• SNAP25B CMS• SNAP25B deficiency
SYT2 Congenital myasthenic syndrome due to a synaptotagmin defect caused by a pathogenic variant in SYT2616040: Myasthenic syndrome, congenital, 7, presynaptic; CMS7Alternative/former titles:Myasthenic syndrome, presynaptic, congenital, with or without motor neuropathy; MYSPC3,4-diaminopyridineORPHA:98914 Presynaptic congenital myasthenic syndromes• Synaptic vesicles exocytosis• Presynaptic• SYT2 CMS• Synaptotagmin 2 myasthenia
UNC13A Congenital myasthenic syndrome due to a mammalian uncoordinated-13 protein defect caused by a pathogenic variant in UNC13AN/A3,4-diaminopyridine as first line; may benefit from addition of pyridostigmineN/A• Synaptic vesicles exocytosis• Presynaptic• Munc13–1 myasthenia
VAMP1 Congenital myasthenic syndrome due to a vesicle associated membrane protein 1 defect caused by a pathogenic variant in VAMP1N/APyridostigmineN/A• Synaptic vesicles exocytosis• Presynaptic• Synaptobrevin-1 myasthenia
Table 3

Proposed revision of Orphanet hierarchy below ORPHA:590 (Congenital myasthenic syndrome)

ORPHA numberTypologyRootLevel 1Level 2Level 3Level 4
ORPHA:590Group of phenomesCongenital myasthenic syndrome
ORPHA:98913Group of phenomesPostsynaptic congenital myasthenic syndromes
NEWGroup of phenomesCongenital myasthenic syndromes with kinetic defect
NEWGroup of phenomesFast-channel congenital myasthenic syndromes
NEWDiseaseFast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNA1
NEWDiseaseFast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNB1
NEWDiseaseFast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRND
NEWDiseaseFast-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNE
NEWGroup of phenomesSlow-channel congenital myasthenic syndromes
NEWDiseaseSlow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNA1
NEWDiseaseSlow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNB1
NEWDiseaseSlow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRND
NEWDiseaseSlow-channel congenital myasthenic syndrome due to an acetylcholine receptor defect caused by a pathogenic variant in CHRNE
NEWGroup of phenomesCongenital myasthenic syndromes with kinetic defect due to reduced ion channel conductance
NEWDiseaseCongenital myasthenic syndrome with kinetic defect due to reduced ion channel conductance caused by pathogenic variants in CHRNE
NEWGroup of phenomesCongenital myasthenic syndromes with primary acetylcholine receptor deficiency
NEWDiseaseCongenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRNA1
NEWDiseaseCongenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRNB1
NEWDiseaseCongenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRND
NEWDiseaseCongenital myasthenic syndrome due to primary acetylcholine receptor deficiency caused by pathogenic variants in CHRNE
NEWGroup of phenomesCongenital myasthenic syndromes due to primary or secondary defects in acetylcholine receptor clustering
NEWDiseaseCongenital myasthenic syndrome due to defects in acetylcholine receptor clustering caused by pathogenic variants in CHRND
NEWDiseaseCongenital myasthenic syndrome due to endplate rapsyn deficiency caused by pathogenic variants in RAPSN
NEWGroup of phenomesCongenital myasthenic syndromes due to defects in endplate development and maintenance
NEWDiseaseCongenital myasthenic syndrome due to agrin deficiency caused by pathogenic variants in AGRN
NEWDiseaseCongenital myasthenic syndrome due to defects in low-density lipoprotein receptor-related protein 4 caused by pathogenic variants in LRP4
NEWDiseaseCongenital myasthenic syndrome due to defects in muscle-specific kinase caused by pathogenic variants in MUSK
NEWDiseaseCongenital myasthenic syndrome due to defects in docking protein 7 caused by pathogenic variants in DOK7
NEWDiseaseCongenital myasthenic syndrome due to plectin deficiency caused by pathogenic variants in PLEC1
NEWDiseaseCongenital myasthenic syndrome due to a sodium channel 1.4 defect caused by pathogenic variants in SCN4A
ORPHA:98914Group of phenomesPresynaptic congenital myasthenic syndromes
NEWGroup of phenomesCongenital myasthenic syndromes due to defective axonal transport
NEWDiseaseCongenital myasthenic syndrome due to a defect in Myosin 9A caused by pathogenic variants in MYO9A
NEWGroup of phenomesCongenital myasthenic syndromes due to defective synthesis or recycling of acetylcholine
NEWDiseaseCongenital myasthenic syndrome due to endplate choline acetyltransferase deficiency caused by pathogenic variants in CHAT
NEWDiseaseCongenital myasthenic syndrome caused by pathogenic variants in PREPL that predict reduced filling of synaptic vesicles with ACh
NEWDiseaseCongenital myasthenic syndrome due to a choline transporter defect caused by pathogenic variants in SLC5A7
NEWDiseaseCongenital myasthenic syndrome due to a vesicular acetylcholine transporter defect caused by pathogenic variants in SLC18A3
NEWGroup of phenomesCongenital myasthenic syndromes due to defective synaptic vesicles exocytosis
NEWDiseaseCongenital myasthenic syndrome due to a synaptosomal-associated protein 25 defect caused by pathogenic variants in SNAP25B
NEWDiseaseCongenital myasthenic syndrome due to a synaptotagmin defect caused by a pathogenic variant in SYT2
NEWDiseaseCongenital myasthenic syndrome due to a mammalian uncoordinated-13 protein defect caused by a pathogenic variant in UNC13A
NEWDiseaseCongenital myasthenic syndrome due to a vesicle associated membrane protein 1 defect caused by a pathogenic variant in VAMP1
NEWDiseaseCongenital myasthenic syndrome due to a mitochondrial citrate carrier defect caused by pathogenic variants in SLC25A1
ORPHA:98915Group of phenomesSynaptic and basal lamina associated congenital myasthenic syndromesa
NEWDiseaseCongenital myasthenic syndrome due to endplate acetylcholinesterase deficiency caused by pathogenic variants in COLQ
NEWDiseaseCongenital myasthenic syndrome due to collagen 13 defects caused by pathogenic variants in COL13A1
NEWDiseaseCongenital myasthenic syndrome due to laminin beta 2 deficiency caused by pathogenic variants in LAMB2
ORPHA:353327Group of phenomesCongenital myasthenic syndromes with glycosylation defect
NEWDiseaseCongenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in GFPT1
NEWDiseaseCongenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in DPAGT1
NEWDiseaseCongenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in ALG2
NEWDiseaseCongenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in ALG14
NEWDiseaseCongenital myasthenic syndrome due to a defect of glycosylation caused by pathogenic variants in GMPPB

aname of group updated from “synaptic congenital myasthenic syndromes”

Nomenclature proposals for individual CMS disease entities and mapping to pre-existing classifications Proposed revision of Orphanet hierarchy below ORPHA:590 (Congenital myasthenic syndrome) aname of group updated from “synaptic congenital myasthenic syndromes”

Results

We defined a total of 39 unique clinical/genetic CMS entities and provided descriptive names for each (Table 2). These were mapped to existing OMIM and Orphanet classifications and existing expert-defined descriptive terms for each were captured from the literature to aid in the definition of group-level classification. Treatment options were obtained from the literature [4, 11] and outlined in Table 2. We then placed the defined entities within the Orphanet classification and hierarchy below the pre-existing entry for congenital myasthenic syndrome, modifying one existing class name and adding 10 group-level phenotypic classes at various levels of the hierarchy and 39 unique disease entities (Table 3).

Discussion

CMS is classed within the European Union as a rare disease (defined as one that affects fewer than 1 in 2000 individuals) and many of the individual CMS entities are ultra-rare. This has substantial implications for knowledge management, since while much highly expert knowledge on CMS does exist, in common with many other rare diseases this knowledge is often “siloed” in individual research or clinical databases in a few expert centers [12]. Academic publishing still largely relies on “non-machine-readable” formats such as PDF and this again provides a barrier to easy access and reuse [13]. This means that not only do fewer clinicians who encounter CMS patients have the relevant experience themselves, but it is also more challenging and time-consuming for them to locate the information they need. Clinical, genetic and scientific experts in CMS have come together periodically to review and update classifications of the disease at workshops hosted by the European Neuromuscular Centre [14-16], in NCBI’s GeneReviews series [17] and several comprehensive recent review publications [3, 4, 18]. Broad classifications of CMS into presynaptic, synaptic and postsynaptic CMS and CMS with glycosylation defect were originally proposed in 2001 [15], but it is only with the very latest update to the International Classification of Disease (ICD), Revision 11 [19], that these subgroups even receive a mention (without, however, being allocated a classification number). Meanwhile, as the number and variety of CMS disease entities published in the literature has increased, expert-proposed groupings have been extended to include a new group containing defects of endplate development and maintenance [18]. However, the expert reviews have not attempted any standardization of nomenclature in the coding systems, and at the most granular level, individual “atomic” disease entities or subtypes are conspicuous in their absence from all the coding systems except the Online Mendelian Inheritance in Man (OMIM) database [20]. OMIM itself has good (although not entirely comprehensive) coverage of the individual disease entities, each represented by a “phenotype MIM number” and a sequentially numbered name, and is recognized as the authoritative reference for genetic disorders, but is not itself a nosology or ontology but rather a catalogue, which is thus complementary to (and mappable to) the classification we create here. To counter the problem of lack of representation of rare disease entities in knowledge systems, bringing data science approaches into the clinical domain has been the focus of a number of recent activities at the European and international level, including the Global Alliance for Genomics and Health (GA4GH) [21], the European Open Science Cloud [22], Big Data to Knowledge (BD2K) [23], the Monarch Initiative [24], GO-FAIR [25], RD-Connect [26] and the new European Joint Programme for Rare Disease to be launched in 2019. Making use of ontologies and coding systems when capturing clinical information and diagnoses is a key step in preparing data for reanalysis and machine-readability [27], but in order for this to be of benefit, the coding system must be fit for purpose – which means it must contain the relevant items in the correct relative positions and at appropriate levels of granularity. If this is not the case, data cannot be appropriately connected or connections may produce misleading results. For example, to a clinician familiar with CMS, it goes without saying that the connection between “congenital myasthenic syndrome” and “responsive to pyridostigmine” is true for CMS caused by RAPSN defects and false for that caused by defects in DOK7, but a database that only contains an entry for “congenital myasthenic syndrome” has no way of making that distinction. The result of this is that the specific knowledge that is so familiar to the disease experts cannot easily gain wider currency by being made part of online databases or clinical decision support systems, and furthermore the evidence gathered in a clinical setting in support of particular interventions or particular phenotypic associations cannot be fed back into wider practice by from medical or prescribing records, for example. Of course, no classification in such a rapidly evolving and heterogeneous field can ever be completely comprehensive, and there are always areas where different decisions could be made, such as about the level of granularity or the range of conditions to include. Our inclusion criteria were based primarily on clinical and phenotypic presentation together with some pathomechanistic insights, while a purely gene-based approach might have produced a classification not exclusively including CMS presentations but also kidney or skin disease presentations caused by different defects in the same genes. In addition, there are other neuromuscular conditions that do have detectable morphological and functional disturbances of the neuromuscular junction, but where these are considered to be secondary to the primary pathology or of minor clinical relevance as compared to the primary clinical manifestation (e.g. spinal muscular atrophy or myotubular myopathy). These conditions are classified in different systems and do not appear in our CMS classification. However, from a data science perspective, the choice of what to include or exclude can indeed be left to expert opinion and is of secondary importance compared to the depth and detail of what is covered, and crucially, its internal logic and relationships with other entities and other classification systems [27]. The CMS entities that we have defined fit perfectly as subclasses within the broader coding systems like ICD and SNOMED-CT and map at a 1:1 level to the phenotype MIM numbers where these exist (see Table 2). They can be grouped into preexisting etiological groups such as pre- and post-synaptic (Table 3), and are amenable to multiple other functional, phenotypic and therapeutic groupings as appropriate (“responsive to acetylcholinesterase inhibitors”, “with limb-girdle phenotype”, “associated with episodic apnea” or “characterized by tubular aggregates”, for example). To take full advantage of the classification developed here, it will be necessary that these next steps are taken, since the development of classification systems, even with names that aim to have some clinical relevance, is of limited diagnostic or therapeutic value in itself. Rather, it should be thought of as the essential foundation onto which more precise clinical and diagnostic pictures of each disease entity can be built, and it is this systematization of knowledge that can then be brought back into the diagnostic and clinical arena to result in improved diagnostic algorithms and clinical information systems. One future development well supported by Orphanet that is a logical extension of the classification to allow improved diagnostic algorithms is the mapping of entities from the classification to their individual phenotypic features using appropriate phenotypic descriptors from ontologies such as the Human Phenotype Ontology [28]. This creates a matrix of detailed information about each disease entity in both computer-accessible and human-readable formats, and is something that can now be achieved for CMS by a similar consensus process. In addition, since many CMSs are treatable, but the treatment varies by type, we can use the classification to differentiate treatments by type as shown in Table 3 and also now have the opportunity to take this further in a machine-readable manner through the development of pharmacogenomic algorithms that give clinicians easier access to specific treatment recommendations once a particular CMS type has been identified. Furthermore, although NGS techniques have still not solved every CMS case, as science advances, we can expect that new genetic defects will be uncovered that account for some of the remaining undiagnosed congenital myasthenic syndromes, and we have thus ensured that this present classification can easily be extended with new entities.

Conclusions

Knowledge about the full range, etiology and heterogeneity of the congenital myasthenic syndromes has increased rapidly in the NGS era. These diseases present specific challenges owing to their rarity and heterogeneity but also possess certain features – not the least of which is responsiveness to treatment – that make their unambiguous differentiation worthwhile. The benefits of developing a fully granular classification for this group of conditions are thus not purely academic. Although not designed as a diagnostic tool, the detailed classification in a single system of each individual CMS with a defect of neuromuscular transmission as the primary feature provides clinicians and geneticists with an overview of the currently recognized congenital myasthenic syndromes both as individual entities and as logical groupings and this can provide guidance towards the differential diagnoses for a patient with a broad CMS phenotypic presentation. Making use of an unambiguous clinically understandable descriptive name assists in the clinical differentiation of the different diseases, particularly by clinicians less familiar with these rare conditions, while attaching the descriptive name to a code within a recognized coding system enables existing knowledge to be better systematized, thus paving the way towards computer-aided clinical systems and machine-learning algorithms suitable for the NGS era. Through this collaboration between clinical experts and data science experts, we have shown that data science approaches can be used effectively in the clinical domain in a way that does not disrupt preexisting classification by experts and that enhances the utility of preexisting coding systems, building on both to create a more comprehensive result. The classification we have defined can be used in clinical administration systems as an integral part of the Orphanet nomenclature and can be used in scientific publications and clinical case reports to unambiguously define the CMS type in question. It can be extended and modified as required by future scientific advances, but already provides the starting point for the creation of FAIR knowledge bases of data related to the congenital myasthenic syndromes.
  23 in total

Review 1.  Harmonising phenomics information for a better interoperability in the rare disease field.

Authors:  Sylvie Maiella; Annie Olry; Marc Hanauer; Valérie Lanneau; Halima Lourghi; Bruno Donadille; Charlotte Rodwell; Sebastian Köhler; Dominik Seelow; Simon Jupp; Helen Parkinson; Tudor Groza; Michael Brudno; Peter N Robinson; Ana Rath
Journal:  Eur J Med Genet       Date:  2018-02-07       Impact factor: 2.708

Review 2.  Preparing Data at the Source to Foster Interoperability across Rare Disease Resources.

Authors:  Marco Roos; Estrella López Martin; Mark D Wilkinson
Journal:  Adv Exp Med Biol       Date:  2017       Impact factor: 2.622

Review 3.  Genetic basis and phenotypic features of congenital myasthenic syndromes.

Authors:  Andrew G Engel
Journal:  Handb Clin Neurol       Date:  2018

Review 4.  Natural History, Trial Readiness and Gene Discovery: Advances in Patient Registries for Neuromuscular Disease.

Authors:  Rachel Thompson; Agata Robertson; Hanns Lochmüller
Journal:  Adv Exp Med Biol       Date:  2017       Impact factor: 2.622

5.  Congenital myasthenic syndrome caused by prolonged acetylcholine receptor channel openings due to a mutation in the M2 domain of the epsilon subunit.

Authors:  K Ohno; D O Hutchinson; M Milone; J M Brengman; C Bouzat; S M Sine; A G Engel
Journal:  Proc Natl Acad Sci U S A       Date:  1995-01-31       Impact factor: 11.205

6.  The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.

Authors:  Ronald Margolis; Leslie Derr; Michelle Dunn; Michael Huerta; Jennie Larkin; Jerry Sheehan; Mark Guyer; Eric D Green
Journal:  J Am Med Inform Assoc       Date:  2014-07-09       Impact factor: 4.497

Review 7.  The Human Phenotype Ontology in 2017.

Authors:  Sebastian Köhler; Nicole A Vasilevsky; Mark Engelstad; Erin Foster; Julie McMurry; Ségolène Aymé; Gareth Baynam; Susan M Bello; Cornelius F Boerkoel; Kym M Boycott; Michael Brudno; Orion J Buske; Patrick F Chinnery; Valentina Cipriani; Laureen E Connell; Hugh J S Dawkins; Laura E DeMare; Andrew D Devereau; Bert B A de Vries; Helen V Firth; Kathleen Freson; Daniel Greene; Ada Hamosh; Ingo Helbig; Courtney Hum; Johanna A Jähn; Roger James; Roland Krause; Stanley J F Laulederkind; Hanns Lochmüller; Gholson J Lyon; Soichi Ogishima; Annie Olry; Willem H Ouwehand; Nikolas Pontikos; Ana Rath; Franz Schaefer; Richard H Scott; Michael Segal; Panagiotis I Sergouniotis; Richard Sever; Cynthia L Smith; Volker Straub; Rachel Thompson; Catherine Turner; Ernest Turro; Marijcke W M Veltman; Tom Vulliamy; Jing Yu; Julie von Ziegenweidt; Andreas Zankl; Stephan Züchner; Tomasz Zemojtel; Julius O B Jacobsen; Tudor Groza; Damian Smedley; Christopher J Mungall; Melissa Haendel; Peter N Robinson
Journal:  Nucleic Acids Res       Date:  2016-11-28       Impact factor: 16.971

Review 8.  Therapeutic strategies for congenital myasthenic syndromes.

Authors:  Manon Lee; David Beeson; Jacqueline Palace
Journal:  Ann N Y Acad Sci       Date:  2018-01       Impact factor: 5.691

9.  The FAIR Guiding Principles for scientific data management and stewardship.

Authors:  Mark D Wilkinson; Michel Dumontier; I Jsbrand Jan Aalbersberg; Gabrielle Appleton; Myles Axton; Arie Baak; Niklas Blomberg; Jan-Willem Boiten; Luiz Bonino da Silva Santos; Philip E Bourne; Jildau Bouwman; Anthony J Brookes; Tim Clark; Mercè Crosas; Ingrid Dillo; Olivier Dumon; Scott Edmunds; Chris T Evelo; Richard Finkers; Alejandra Gonzalez-Beltran; Alasdair J G Gray; Paul Groth; Carole Goble; Jeffrey S Grethe; Jaap Heringa; Peter A C 't Hoen; Rob Hooft; Tobias Kuhn; Ruben Kok; Joost Kok; Scott J Lusher; Maryann E Martone; Albert Mons; Abel L Packer; Bengt Persson; Philippe Rocca-Serra; Marco Roos; Rene van Schaik; Susanna-Assunta Sansone; Erik Schultes; Thierry Sengstag; Ted Slater; George Strawn; Morris A Swertz; Mark Thompson; Johan van der Lei; Erik van Mulligen; Jan Velterop; Andra Waagmeester; Peter Wittenburg; Katherine Wolstencroft; Jun Zhao; Barend Mons
Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

10.  RD-Connect, NeurOmics and EURenOmics: collaborative European initiative for rare diseases.

Authors:  Hanns Lochmüller; Dorota M Badowska; Rachel Thompson; Nine V Knoers; Annemieke Aartsma-Rus; Ivo Gut; Libby Wood; Tina Harmuth; Andre Durudas; Holm Graessner; Franz Schaefer; Olaf Riess
Journal:  Eur J Hum Genet       Date:  2018-02-27       Impact factor: 4.246

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  5 in total

1.  A novel fast-channel myasthenia caused by mutation in β subunit of AChR reveals subunit-specific contribution of the intracellular M1-M2 linker to channel gating.

Authors:  Xin-Ming Shen; Li Di; Shelley Shen; Yuying Zhao; Ann M Neumeyer; Duygu Selcen; Steven M Sine; Andrew G Engel
Journal:  Exp Neurol       Date:  2020-06-03       Impact factor: 5.330

2.  Determinants of the repetitive-CMAP occurrence and therapy efficacy in slow-channel myasthenia.

Authors:  Li Di; Hai Chen; Yan Lu; Duygu Selcen; Andrew G Engel; Yuwei Da; Xin-Ming Shen
Journal:  Neurology       Date:  2020-09-09       Impact factor: 9.910

3.  Targeted therapies for congenital myasthenic syndromes: systematic review and steps towards a treatabolome.

Authors:  Rachel Thompson; Gisèle Bonne; Paolo Missier; Hanns Lochmüller
Journal:  Emerg Top Life Sci       Date:  2019-01-28

4.  Slow-channel myasthenia due to novel mutation in M2 domain of AChR delta subunit.

Authors:  Xin-Ming Shen; Margherita Milone; Hang-Long Wang; Brenda Banwell; Duygu Selcen; Steven M Sine; Andrew G Engel
Journal:  Ann Clin Transl Neurol       Date:  2019-09-27       Impact factor: 4.511

5.  Long Term Follow-Up on Pediatric Cases With Congenital Myasthenic Syndromes-A Retrospective Single Centre Cohort Study.

Authors:  Adela Della Marina; Eva Wibbeler; Angela Abicht; Heike Kölbel; Hanns Lochmüller; Andreas Roos; Ulrike Schara
Journal:  Front Hum Neurosci       Date:  2020-12-07       Impact factor: 3.169

  5 in total

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