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Article

A National French Consensus on Gene List for the Diagnosis of Charcot–Marie–Tooth Disease and Related Disorders Using Next-Generation Sequencing

by
Thibaut Benquey
1,†,
Emmanuelle Pion
2,3,†,
Mireille Cossée
3,4,‡,
Martin Krahn
5,6,‡,
Tanya Stojkovic
7,
Aurélien Perrin
4,
Mathieu Cerino
5,6,
Annamaria Molon
8,
Anne-Sophie Lia
9,
Corinne Magdelaine
9,
Bruno Francou
10,11,
Anne Guiochon-Mantel
10,11,
Marie-Claire Malinge
12,
Eric Leguern
13,
Nicolas Lévy
5,6,
Shahram Attarian
5,14,
Philippe Latour
1 and
Nathalie Bonello-Palot
5,6,*
1
Service de Biochimie et Biologie Moléculaire Grand Est, Hospices Civils de Lyon, LBMMS, 69002 Lyon, France
2
Filnemus, CHRU Montpellier, 34093 Montpellier, France
3
Laboratoire de Génétique Moléculaire, Centre Hospitalier Universitaire de Montpellier, 34093 Montpellier, France
4
PhyMedExp, Université de Montpellier, INSERM, CNRS, 34093 Montpellier, France
5
Marseille Medical Genetics, INSERM, UMR 1251, Aix-Marseille Université, 13005 Marseille, France
6
Département de Génétique Médicale, APHM, Hôpital Timone Enfants, 13005 Marseille, France
7
Institut de Myologie, Centre de Référence des Maladies Neuromusculaires Nord/Est/Ile de France, Hôpital Pitié-Salpêtrière, Sorbonne Université, 75013 Paris, France
8
Filnemus, APHM, 13005 Marseille, France
9
Service de Biochimie et de Génétique Moléculaire, Centre de Biologie et de Recherche en Santé, CHU Limoges, 87042 Limoges, France
10
Service de Génétique Moléculaire, Pharmacogénétique et Hormonologie, Centre Hospitalier Universitaire Bicêtre, Assistance Publique-Hôpitaux de Paris, 94270 Le Kremlin-Bicêtre, France
11
INSERM UMR1185, Faculté de médecine Paris Saclay, Université Paris-Saclay, 94270 Le Kremlin-Bicêtre, France
12
Département de Biochimie Génétique, UF de Biologie Moléculaire, CHU d’Angers, 49100 Angers, France
13
Centre de Génétique Moléculaire et Chromosomique, UF de Neurogénétique Moléculaire et Cellulaire APHP, 75651 Paris, France
14
Reference Centres for Neuromuscular Diseases and ALS, Hôpital Timone Adultes, Assistance Publique Hôpitaux de Marseille, 13005 Marseille, France
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
Genes 2022, 13(2), 318; https://doi.org/10.3390/genes13020318
Submission received: 5 January 2022 / Revised: 1 February 2022 / Accepted: 3 February 2022 / Published: 9 February 2022
(This article belongs to the Special Issue Genetics of Muscular Disorders)

Abstract

:
Next generation sequencing (NGS) is strategically used for genetic diagnosis in patients with Charcot–Marie–Tooth disease (CMT) and related disorders called non-syndromic inherited peripheral neuropathies (NSIPN) in this paper. With over 100 different CMT-associated genes involved and ongoing discoveries, an important interlaboratory diversity of gene panels exists at national and international levels. Here, we present the work of the French National Network for Rare Neuromuscular Diseases (FILNEMUS) genetic diagnosis section which coordinates the seven French diagnosis laboratories using NGS for peripheral neuropathies. This work aimed to establish a unique, simple and accurate gene classification based on literature evidence. In NSIPN, three subgroups were usually distinguished: (1) HMSN, Hereditary Motor Sensory Neuropathy, (2) dHMN, distal Hereditary Motor Neuropathy, and (3) HSAN, Hereditary Sensory Autonomic Neuropathy. First, we reported ClinGen evaluation, and second, for the genes not evaluated yet by ClinGen, we classified them as “definitive” if reported in at least two clinical publications and associated with one report of functional evidence, or “limited” otherwise. In total, we report a unique consensus gene list for NSIPN including the three subgroups with 93 genes definitive and 34 limited, which is a good rate for our gene’s panel for molecular diagnostic use.

Graphical Abstract

1. Introduction

1.1. CMT Is a Heterogeneous Genetic Disease

Charcot–Marie–Tooth disease (CMT) encompasses Hereditary Motor and Sensory Neuropathies (HMSN). They represent the most frequent inherited peripheral neuropathy. Related disorders with overlapping clinical findings include distal Hereditary Motor Neuropathies (dHMN), Hereditary Sensory Autonomic Neuropathies (HSAN), among others. Collectively termed non-syndromic inherited peripheral neuropathies (NSIPN) in this article, these disorders represent the most common group of inherited neuromuscular diseases with an estimated prevalence of 1 in 2500 [1]. Over the past 30 years, a huge revolution in molecular genetics and genomics has occurred. Consequently, more than 100 NSIPN causing genes were identified with many different types of mutations and the number is still increasing [2,3]. In addition, several genes involved in one type of neuropathy were identified later in other phenotypes. For example, SPTLC1, reported for the first time as HSAN1A, was recently involved in the HMSN phenotype [4].

1.2. Molecular Diagnosis Is Positive around 40% of Cases

NSIPN represent a number of challenges for molecular diagnostic in laboratories, due to the clinical and genetic heterogeneity. To date, numerous studies worked on the rate of molecular diagnosis since the beginning of NGS analysis. In our previous study, we were able to make a molecular diagnosis in 40% (49/123 patients) with a gene panel list of 81 genes which were consistent with others studies [5]. Hartley et al. found 24% of diagnosis (12/50 families) by using whole exome sequencing (WES) [6]. Gonzagua-Jauregui et al. were able to have a positive rate in 46% (17/37 families) by WES [7]. Dorhn et al. used a targeted panel between 54–84 genes and identified the genetic cause in 19.8% (121/612 patients) [8]. By associating Multiplex-ligation-dependent-probe-amplification (MLPA) for PMP22/GJB1/MPZ and GJB1/MPZ/PMP22, Sanger sequencing, and targeted panel sequencing exclusively on CMT axonal, Padilha et al. found a molecular diagnosis in 55% of families (33/55) with a gene list panel of 104 genes [9]. Taghizadeh et al. were able to find a molecular diagnosis in 46.6% patients (27/58) by WES [10]. Cortese et al. found two diagnosis rates depending on regions, 32% in London with a panel of 50 genes and 30% in Iowa with a panel of 51 ± 23 genes [11].
The 60% undiagnosed cases might be caused by other types of mutations in known genes not identified, such as deep intronic variations and indels or by mutations in unknown genes.

1.3. Next Generation Sequencing Technologies Increase the Rate of Molecular Diagnosis

Next generation sequencing (NGS) has revolutionized genomic research. Nowadays, NGS has been implemented and is largely used in day to day clinical practice. It provides possibilities for a more efficient genetic diagnostic service to patients with hereditary neuropathies [5]. Indeed, NGS platforms can perform parallel sequencing of millions of small DNA fragments. Furthermore, the NGS sequencing cost for large batches of samples is permanently decreasing and its efficiency growing regarding the time taken to sequence genetic material compared with the traditional Sanger sequencing method. To summarize, NGS method allows rapid and relatively cheap parallel sequencing of multiple genomic loci and the detection of a larger spectrum in DNA variations, providing unknown genetic variants, which is essential in the context of the genetic heterogeneity of CMT.
In clinical CMT practices, customized targeted panels of disease-relevant gene is the most commonly used method for the NGS approach and offers a high degree of coverage of the selected genes [12]. However, because the mutational screening capacities in the field of neuropathies are exponentially increasing and the analysis of a gene list from a targeted panel associated with specific disease groups evolves rapidly.
Due to the overlapping phenotypes of numerous genes in NSIPN, we choose the NGS analysis of a unique gene panel including genes involved in the three different subgroups.

2. Materials and Methods

Identical Gene List Panel Must Be Performed in Expert Laboratories
In France, several genetic diagnostic laboratories are using NGS for targeted panels of disease-relevant genes in the NSIPN diagnosis. However, depending on their laboratory expertise and local history, these gene panels can be slightly different from one institute to another.
FILNEMUS (Filière Nationale des Maladies Rares Neuromusculaires) was created in 2014 with the National Network for Rare Disease. One of its multiple missions has been to standardize the NGS diagnostic approach in order to standardize the testing procedure for patients from different regions. In this context, the nine French genetic diagnostic laboratories using NGS for myopathies recently published a consensual gene list [13]. Similarly, in this study, we aimed to establish a simple and accurate gene classification, more comprehensible and accessible for the whole clinical community, to provide a recommended specific “NSIPN-related disease gene list” to the reference diagnostic centres. We present an updated list of genes called “unique gene panel” based on the recommendation from seven specialized neuropathies diagnostic laboratories in France for NSIPN, including the three subgroups: HMSN, dHMN, and HSAN.

3. Results and Discussion

3.1. The FILNEMUS Consortium Implemented a Unique Gene Panel for NSIPN

The FILNEMUS consortium was a real springboard for the seven French neuropathy diagnostic laboratories using the NGS approach for NSIPN.
A concerted decision was achieved to identify a unique gene panel including genes involved in one or several of the three subgroups: (1) HMSN, (2) dHMN, and (3) HSAN. Each gene was selected through the Gene Table of Neuropathological Disorders [14], the practical experience from each of the seven diagnosis groups, and finally the available literature. Following these criteria, 127 genes were classified into NSIPN; 81 genes reported in HMSN, 26 in dHMN, and 20 in HSAN (Table 1) with overlap between the different subgroups. For example, TRPV4 is reported in CMT and dHMN, SCN9A in HSAN and congenital insensitivity and more (see column “Diseases” in supplementary data Table S1, from references 1 to 281).

3.2. Molecular Strategy Is Based on Four Steps

For NSIPN, the standardized strategy consists in first (1) performing a rapid and reliable detection of duplication/deletion of the PMP22 gene in patients with relevant phenotype as HMSN (Figure 1).
In case of duplication, PMP22 absence and depending on the prescription and clinical data, (2) an NGS analysis of a unique gene panel is performed.
Clinical data of NSIPN, family history, and conduction velocity of the median nerve are documented to help biologists interpret NGS data. NGS results generate a variants list classified according to American college of medical genetics ACMG criteria [15]. (3) Diagnostic pluridisciplinary meetings between clinicians and geneticists are organised to discuss the result and the pursuit or not of a molecular diagnosis for the patient. More precisely, in case we identify a class IV variant (likely pathogenic) or a class V variant (pathogenic) variant according to the ACMG classification, the analysis is stopped and we correlate the genotype with the phenotype of the patient. When a class III variant is identified (Variant of Unknown Significance), we discuss about the potentiality of this variant to be linked to the phenotype of the patient. If correlation occurs, we ask for familial study and functional experiments (if available). If no correlation takes place, we ask for additional investigations. In the absence of a potential variant or if the variant does not correspond to the phenotype, the meeting discussion turns toward the identification of new genes, (4) by performing WES or Whole Genome sequencing (WGS).

3.3. Genes Are Classified Depending on Literature Evidence Based on Strande Publication and ClinGen Evaluation

We reported first the ClinGen evaluation (https://www.clinicalgenome.org/, accessed on 15 December 2021). ClinGen classified gene as definitive when a strict correlation is well established between the phenotype and the genotype, limited when not, and moderate when between both. For the genes not evaluated yet by ClinGen, we classified them as “definitive” if a minimum of two clinical studies were reported, associated with one report of functional evidence [16], such as, for example, for the MPZ (Myelin Protein Zero) gene. We chose papers reporting genes involving several families and we took into account the pathogenicity of the variants described with low or absence gnomAD (https://gnomad.broadinstitute.org/, accessed on 15 December 2021) occurrence. We classified genes as “limited” if there was not enough bibliographic data (one or two clinical cases without functional evidence/one clinical case and one functional evidence), such as, for example, the PNKP (Polynucleotide Kinase Phosphatase) gene. An important point is that some genes are involved in different phenotypes and can be “definitive” in one type of neuropathy and “limited” in another. For example, DYNC1H1 is classified as “limited” in HMSN and “definitive” in dHMN. There is a broad clinical overlap in axonal HMSN and dHMN with some common genes involved as DYNC1H1, GARS1, HSPB1, HSPB8, IGHMBP2, MFN2, and PLEKHG5, as represented in Figure 2. This point led us to consider a unique gene panel for this disease’s group. We also observed a phenotypic overlap between NSIPN, but also with other diseases, such as distal myopathies or hereditary spastic paraplegia (HSP), as described in Pipis et al. [12,17]. A limitation of this classification is that some genes with strong clinical evidence are classified as “limited” due to poor functional evidence, such as HK1. Another important point to notice is that two genes MED25 and KIF1B were disputed and no more involved in HMSN and “replaced” by PNKP and MFN2 in their locus.

3.4. This Classification Allows Stratification of Variant Analysis

At least, 93 genes can be classified as “definitive” with, in detail: 55/81 genes in the HMSN group (68%), 21/26 in the dHMN group (81%), and 17/20 genes in the HSAN group (85%) leading to an overall 73% of genes having enough scientific evidence (Table 1). Compared to the myopathy consensus which defined 70% of definitive genes [13], we have the same literature proof for the molecular diagnosis of NSIPN. Through this classification, an accurate initial determination of the patient’s entry diagnosis allows the genetic screening of the most relevant genes potentially involved. This consensual diagnostic strategy was validated by the expert clinician group and geneticists and adopted by all participating laboratories.

4. Conclusions

How Does This Consortium Helps Molecular Diagnosis in NSIPN?

This consensus is likely to increase the diagnostic rate and further our understanding of the genetic basis of NSIPN diseases as well. The burden of variable interpretation is considerable, and robust filtering strategies that use all the available clinical, genetic, and bioinformatics informations are required to classify variants.
Thanks to the nationwide FILNEMUS genetic diagnosis working-group, a yearly update of the consensual gene lists will be done. In this regard, the aim of this working group is to gradually classify all “gene-related diseases” associations according to the published ClinGen Clinical Validity framework.
Within the next four years, we believe that the rapid expansion of NGS platforms across France with the implementation of bioinformatics tools to analyse the large volume of data generated will allow us to combine the WES and WGS strategy to the diagnosis of NSIPN, using this unique gene panel for an in silico first-step variant analysis. These techniques are very useful to increase the diagnostic yield in NSIPN. However, accurate and precise phenotyping of patients are mandatory for the NGS approach. Skipping this step leads to false diagnoses and increases diagnostic wavering.
This unique gene panel recommendation is thought to be a real improvement for the diagnosis. Our goal is to provide access to accurate diagnosis and appropriate treatment.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes13020318/s1, Table S1: National French consensual gene lists for the genetic diagnosis of NSIPN.

Author Contributions

Conceptualization, T.B., N.B.-P., P.L., M.K. and M.C. (Mireille Cossée); Supervision, N.B.-P. and P.L.; Formal analysis, T.B., N.B.-P. and P.L.; E.P.; Investigation T.B., E.P., M.C. ( Mathieu Cerino), M.K., T.S., A.P., A.M., A.-S.L., C.M., B.F., A.G.-M., M.-C.M., E.L., N.L., S.A., P.L., N.B.-P.; Writing—original draft preparation E.P., T.B.; N.B.-P.; Writing—review and editing, E.P., N.B.-P., T.S, E.P., M.C. (Mireille Cossée); Supervision N.B.-P. All authors participated in critical revisions of the manuscript and can take responsibility for its integrated and the accuracy of the data analysis. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by Marseille University Hospital (AP-HM) and Aix-Marseille University. EP is funded by FILNEMUS.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are not available freely. Enquiries and requests for further information should be made to corresponding author.

Acknowledgments

We sincerely thank all the participants for collaborating work. This study was supported by the Filière Nationale des Maladies Rares Neuromusculaires FILNEMUS. We thank Victor Morel for his help.

Conflicts of Interest

The authors declare that they have no conflict of interest.

Abbreviations

NGSNext Generation Sequencing
CMTCharcot–Marie–Tooth disease
HMSNHereditary Motor and Sensory Neuropathies
dHMNDistal Hereditary Motor Neuropathies
HSANHereditary Motor Neuropathies
DNADeoxyribonucleic Acid
FILNEMUSFilière Nationale des Maladies Rares Neuromusculaires
PMP22peripheral myelin protein 22
MPZMyelin Protein Zero
PNKPPolynucleotide Kinase Phosphatase
WESWhole Exome Sequencing
WGSWhole Genome Sequencing
MLPAMultiplex-ligation-dependent-probe-amplification
DYNC1H1Dynein Cytoplasmic 1 Heavy Chain 1
GARSGlycyl-TRNA Synthetase 1
HSPBHeat Shock Protein Family
IGHMBP2Immunoglobulin Mu DNA Binding Protein
MFN2Mitofusin 2
PLEKHG5Pleckstrin Homology And RhoGEF Domain Containing G5
SPG11Spastic Paraplegia 11
VUSVariant of Uncertain Significance

References

  1. Skre, H. Genetic and Clinical Aspects of Charcot–Marie–Tooth’s Disease. Clin. Genet. 1974, 6, 98–118. [Google Scholar] [CrossRef] [PubMed]
  2. Pisciotta, C.; Shy, M.E. Neuropathy. Handb. Clin. Neurol. 2018, 148, 653–665. [Google Scholar] [CrossRef] [PubMed]
  3. Bonne, G.; Rivier, F.; Hamroun, D. The 2019 Version of the Gene Table of Neuromuscular Disorders (Nuclear Genome). Neuromuscul. Disord. 2018, 28, 1031–1063. [Google Scholar] [CrossRef] [PubMed]
  4. Rossi, F.; Bruno, G.; Fratta, M.; Colavito, D.; Casertano, S.; Sampaolo, S.; Oliva, M.; Puoti, G. Expanding the Spectrum of SPTLC1-Related Disorders beyond Hereditary Sensory and Autonomic Neuropathies: A Novel Case of the Distinct “S331 Syndrome”. J. Peripher. Nerv. Syst. 2020, 25, 308–311. [Google Scholar] [CrossRef] [PubMed]
  5. Bacquet, J.; Stojkovic, T.; Boyer, A.; Martini, N.; Audic, F.; Chabrol, B.; Salort-Campana, E.; Delmont, E.; Desvignes, J.-P.; Verschueren, A.; et al. Molecular Diagnosis of Inherited Peripheral Neuropathies by Targeted Next-Generation Sequencing: Molecular Spectrum Delineation. BMJ Open 2018, 8, e021632. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Hartley, T.; Wagner, J.D.; Warman-Chardon, J.; Tétreault, M.; Brady, L.; Baker, S.; Tarnopolsky, M.; Bourque, P.R.; Parboosingh, J.S.; Smith, C.; et al. Whole-Exome Sequencing Is a Valuable Diagnostic Tool for Inherited Peripheral Neuropathies: Outcomes from a Cohort of 50 Families. Clin. Genet. 2018, 93, 301–309. [Google Scholar] [CrossRef] [PubMed]
  7. Gonzaga-Jauregui, C.; Harel, T.; Gambin, T.; Kousi, M.; Griffin, L.B.; Francescatto, L.; Ozes, B.; Karaca, E.; Jhangiani, S.N.; Bainbridge, M.N.; et al. Exome Sequence Analysis Suggests That Genetic Burden Contributes to Phenotypic Variability and Complex Neuropathy. Cell Rep. 2015, 12, 1169–1183. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Dohrn, M.F.; Glöckle, N.; Mulahasanovic, L.; Heller, C.; Mohr, J.; Bauer, C.; Riesch, E.; Becker, A.; Battke, F.; Hörtnagel, K.; et al. Frequent Genes in Rare Diseases: Panel-Based next Generation Sequencing to Disclose Causal Mutations in Hereditary Neuropathies. J. Neurochem. 2017, 143, 507–522. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Padilha, J.P.D.; Brasil, C.S.; Hoefel, A.M.L.; Winckler, P.B.; Donis, K.C.; Brusius-Facchin, A.C.; Saute, J.A.M. Diagnostic Yield of Targeted Sequential and Massive Panel Approaches for Inherited Neuropathies. Clin. Genet. 2020, 98, 185–190. [Google Scholar] [CrossRef] [PubMed]
  10. Taghizadeh, S.; Vazehan, R.; Beheshtian, M.; Sadeghinia, F.; Fattahi, Z.; Mohseni, M.; Arzhangi, S.; Nafissi, S.; Kariminejad, A.; Najmabadi, H.; et al. Molecular Diagnosis of Hereditary Neuropathies by Whole Exome Sequencing and Expanding the Phenotype Spectrum. Arch. Iran. Med. 2020, 23, 426–433. [Google Scholar] [CrossRef] [PubMed]
  11. Cortese, A.; Wilcox, J.E.; Polke, J.M.; Poh, R.; Skorupinska, M.; Rossor, A.M.; Laura, M.; Tomaselli, P.J.; Houlden, H.; Shy, M.E.; et al. Targeted Next-Generation Sequencing Panels in the Diagnosis of Charcot–Marie–Tooth Disease. Neurology 2020, 94, e51–e61. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Pipis, M.; Rossor, A.M.; Laura, M.; Reilly, M.M. Next-Generation Sequencing in Charcot–Marie–Tooth Disease: Opportunities and Challenges. Nat. Rev. Neurol. 2019, 15, 644–656. [Google Scholar] [CrossRef] [PubMed]
  13. Krahn, M.; Biancalana, V.; Cerino, M.; Perrin, A.; Michel-Calemard, L.; Nectoux, J.; Leturcq, F.; Bouchet-Séraphin, C.; Acquaviva-Bourdain, C.; Campana-Salort, E.; et al. A National French Consensus on Gene Lists for the Diagnosis of Myopathies Using Next-Generation Sequencing. Eur. J. Hum. Genet. 2019, 27, 349–352. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Benarroch, L.; Bonne, G.; Rivier, F.; Hamroun, D. The 2020 Version of the Gene Table of Neuromuscular Disorders (Nuclear Genome). Neuromuscul. Disord. 2019, 29, 980–1018. [Google Scholar] [CrossRef] [PubMed]
  15. Richards, S.; Aziz, N.; Bale, S.; Bick, D.; Das, S.; Gastier-Foster, J.; Grody, W.W.; Hegde, M.; Lyon, E.; Spector, E.; et al. Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 2015, 17, 405–424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Strande, N.T.; Riggs, E.R.; Buchanan, A.H.; Ceyhan-Birsoy, O.; DiStefano, M.; Dwight, S.S.; Goldstein, J.; Ghosh, R.; Seifert, B.A.; Sneddon, T.P.; et al. Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource. Am. J. Hum. Genet. 2017, 100, 895–906. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Rossor, A.M.; Carr, A.S.; Devine, H.; Chandrashekar, H.; Pelayo-Negro, A.L.; Pareyson, D.; Shy, M.E.; Scherer, S.S.; Reilly, M.M. Peripheral Neuropathy in Complex Inherited Diseases: An Approach to Diagnosis. J. Neurol. Neurosurg. Psychiatry 2017, 88, 846–863. [Google Scholar] [CrossRef] [PubMed]
Figure 1. National French consensus strategy for genetic diagnosis of NSIPN using NGS.
Figure 1. National French consensus strategy for genetic diagnosis of NSIPN using NGS.
Genes 13 00318 g001
Figure 2. Venn Diagram of CMT gene subgroups. Bold genes represent the “definitive” classified genes.
Figure 2. Venn Diagram of CMT gene subgroups. Bold genes represent the “definitive” classified genes.
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Table 1. Summary of National French consensual gene lists for the genetic diagnosis of NSIPN.
Table 1. Summary of National French consensual gene lists for the genetic diagnosis of NSIPN.
SubgroupDefinitive Genes
n (%)
Limited Genes
n (%)
Total Genes
n
CMT or HMSN55 (68%)26 (32%)81
dHMN21(81%)5(19%)26
HSAN17(85%)3(15%)20
NSIPN93 (73%)34 (27%)127
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MDPI and ACS Style

Benquey, T.; Pion, E.; Cossée, M.; Krahn, M.; Stojkovic, T.; Perrin, A.; Cerino, M.; Molon, A.; Lia, A.-S.; Magdelaine, C.; et al. A National French Consensus on Gene List for the Diagnosis of Charcot–Marie–Tooth Disease and Related Disorders Using Next-Generation Sequencing. Genes 2022, 13, 318. https://doi.org/10.3390/genes13020318

AMA Style

Benquey T, Pion E, Cossée M, Krahn M, Stojkovic T, Perrin A, Cerino M, Molon A, Lia A-S, Magdelaine C, et al. A National French Consensus on Gene List for the Diagnosis of Charcot–Marie–Tooth Disease and Related Disorders Using Next-Generation Sequencing. Genes. 2022; 13(2):318. https://doi.org/10.3390/genes13020318

Chicago/Turabian Style

Benquey, Thibaut, Emmanuelle Pion, Mireille Cossée, Martin Krahn, Tanya Stojkovic, Aurélien Perrin, Mathieu Cerino, Annamaria Molon, Anne-Sophie Lia, Corinne Magdelaine, and et al. 2022. "A National French Consensus on Gene List for the Diagnosis of Charcot–Marie–Tooth Disease and Related Disorders Using Next-Generation Sequencing" Genes 13, no. 2: 318. https://doi.org/10.3390/genes13020318

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