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Translating genetic and functional data into clinical practice: a series of 223 families with myotonia.

Suetterlin, K; Matthews, E; Sud, R; McCall, S; Fialho, D; Burge, J; Jayaseelan, D; Haworth, A; Sweeney, MG; Kullmann, DM; et al. 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 (2022) Translating genetic and functional data into clinical practice: a series of 223 families with myotonia. Brain, 145 (2). pp. 607-620. ISSN 1460-2156 https://doi.org/10.1093/brain/awab344
SGUL Authors: Haworth, Andrea Matthews, Emma Louise

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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 (MC) as an example of these challenges. Sequencing of CLCN1, the gene that encodes CLC-1, is central to the diagnosis of MC. 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 standardised functional analyses and correlate this with clinical assessment and inheritance pattern. Such correlation is important to determine if functional data improves the accuracy of variant interpretation and likely mode of inheritance. Our data provide an evidence-based approach that functional characterisation of ClC-1 variants improves clinical interpretation of their pathogenicity and inheritance pattern and serve as reference for 34 previously unreported and 28 previously uncharacterised 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 MC. 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 characterisation can significantly refine the assessment of risk of an associated inheritance pattern and consequently the clinical and genetic counselling.

Item Type: Article
Additional Information: © The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: CLCN1, ClC-1, chloride channel, myotonia congenita, skeletal muscle channelopathy, skeletal muscle channelopathy, chloride channel, myotonia congenita, ClC-1, CLCN1, CLCN1, ClC-1, chloride channel, myotonia congenita, skeletal muscle channelopathy, Neurology & Neurosurgery, 11 Medical and Health Sciences, 17 Psychology and Cognitive Sciences
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Brain
ISSN: 1460-2156
Language: eng
Dates:
DateEvent
February 2022Published
16 September 2021Published Online
5 August 2021Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
MR/M01827X/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
2012-305121Seventh Framework Programmehttp://dx.doi.org/10.13039/501100004963
209583/Z/17/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
PubMed ID: 34529042
Web of Science ID: WOS:000761596400001
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/113743
Publisher's version: https://doi.org/10.1093/brain/awab344

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