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Suetterlin K, Matthews E, Sud R, McCall S, Fialho D, Burge J, Jayaseelan D, Haworth A, Sweeney MG, Kullmann DM, Schorge S, Hanna MG, Männikkö R. Translating genetic and functional data into clinical practice: a series of 223 families with myotonia. Brain 2022; 145:607-620. [PMID: 34529042 PMCID: PMC9014745 DOI: 10.1093/brain/awab344] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 07/13/2021] [Accepted: 08/05/2021] [Indexed: 11/14/2022] Open
Abstract
High-throughput DNA sequencing is increasingly employed to diagnose single gene neurological and neuromuscular disorders. Large volumes of data present new challenges in data interpretation and its useful translation into clinical and genetic counselling for families. Even when a plausible gene is identified with confidence, interpretation of the clinical significance and inheritance pattern of variants can be challenging. We report our approach to evaluating variants in the skeletal muscle chloride channel ClC-1 identified in 223 probands with myotonia congenita as an example of these challenges. Sequencing of CLCN1, the gene that encodes CLC-1, is central to the diagnosis of myotonia congenita. However, interpreting the pathogenicity and inheritance pattern of novel variants is notoriously difficult as both dominant and recessive mutations are reported throughout the channel sequence, ClC-1 structure-function is poorly understood and significant intra- and interfamilial variability in phenotype is reported. Heterologous expression systems to study functional consequences of CIC-1 variants are widely reported to aid the assessment of pathogenicity and inheritance pattern. However, heterogeneity of reported analyses does not allow for the systematic correlation of available functional and genetic data. We report the systematic evaluation of 95 CIC-1 variants in 223 probands, the largest reported patient cohort, in which we apply standardized functional analyses and correlate this with clinical assessment and inheritance pattern. Such correlation is important to determine whether functional data improves the accuracy of variant interpretation and likely mode of inheritance. Our data provide an evidence-based approach that functional characterization of ClC-1 variants improves clinical interpretation of their pathogenicity and inheritance pattern, and serve as reference for 34 previously unreported and 28 previously uncharacterized CLCN1 variants. In addition, we identify novel pathogenic mechanisms and find that variants that alter voltage dependence of activation cluster in the first half of the transmembrane domains and variants that yield no currents cluster in the second half of the transmembrane domain. None of the variants in the intracellular domains were associated with dominant functional features or dominant inheritance pattern of myotonia congenita. Our data help provide an initial estimate of the anticipated inheritance pattern based on the location of a novel variant and shows that systematic functional characterization can significantly refine the assessment of risk of an associated inheritance pattern and consequently the clinical and genetic counselling.
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Affiliation(s)
- Karen Suetterlin
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
- AGE Research Group, NIHR Newcastle Biomedical Research Centre, Newcastle-upon-Tyne Hospitals NHS Foundation Trust and Newcastle University, Newcastle-upon-Tyne, UK
| | - Emma Matthews
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
- Atkinson Morley Neuromuscular Centre, Department of Neurology, St Georges University Hospitals NHS Foundation Trust, London, UK
| | - Richa Sud
- Neurogenetics Unit, UCL Queen Square Institute of Neurology, London, UK
| | - Samuel McCall
- Neurogenetics Unit, UCL Queen Square Institute of Neurology, London, UK
| | - Doreen Fialho
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
- Department of Clinical Neurophysiology, King’s College Hospital, London, UK
| | - James Burge
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
- Department of Clinical Neurophysiology, King’s College Hospital, London, UK
| | - Dipa Jayaseelan
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Andrea Haworth
- Neurogenetics Unit, UCL Queen Square Institute of Neurology, London, UK
| | - Mary G Sweeney
- Neurogenetics Unit, UCL Queen Square Institute of Neurology, London, UK
| | - Dimitri M Kullmann
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Stephanie Schorge
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Department of Pharmacology, UCL School of Pharmacy, London, UK
| | - Michael G Hanna
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Roope Männikkö
- MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, London, UK
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