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

Author:

Suetterlin Karen12,Matthews Emma13,Sud Richa4,McCall Samuel4,Fialho Doreen15,Burge James15,Jayaseelan Dipa1,Haworth Andrea4,Sweeney Mary G4,Kullmann Dimitri M6,Schorge Stephanie67,Hanna Michael G1,Männikkö Roope1

Affiliation:

1. MRC International Centre for Genomic Medicine in Neuromuscular Diseases, Department of Neuromuscular disease, UCL Queen Square Institute of Neurology, London, UK

2. AGE Research Group, NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, Newcastle upon Tyne, UK

3. Atkinson Morley Neuromuscular Centre, Department of Neurology, St Georges University Hospitals NHS Foundation Trust, London, UK

4. Neurogenetics Unit, UCL Queen Square Institute of Neurology, London, UK

5. Department of Clinical Neurophysiology, King’s College Hospital, London, UK

6. Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK

7. Department of Pharmacology, UCL School of Pharmacy, London, UK

Abstract

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.

Publisher

Oxford University Press (OUP)

Subject

Clinical Neurology

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