Experts in CMT
CMT Gene Browser

Experts in CMT built the CMT Gene Browser as a searchable, gene-centered reference for Charcot-Marie-Tooth disease (CMT) genetics. It brings together the genes known or suspected to cause CMT, the subtypes associated with each gene, inheritance patterns, genomic locations, gene and protein identifiers, evidence classifications, and the sentinel publications.

Why is the CMT Gene Browser Needed?

CMT genetic information is spread across many resources. HGNC, Ensembl, UniProt, OMIM, gnomAD, ClinVar, ClinGen, GeneReviews, MANE Select, the scientific literature, and other databases. Each provides important information, but none offers a complete, CMT-specific view.

That fragmentation makes even straightforward questions surprisingly difficult to answer. Which CMT subtypes are associated with a particular gene? What evidence supports the gene-disease relationship? Where’s the authoritative publication? What are the identifiers for cross-platform referencing? The CMT Gene Browser brings these pieces together into a unified research surface.

Each gene has a single record that connects its CMT associations with standardized identifiers, external resources, evidence classifications, and publications supporting the genotype-phenotype relationship. Rather than reconstructing the information across multiple databases and papers, you can begin here with a CMT-specific relationship already mapped and follow the underlying sources directly.

How to Use the CMT Gene Browser

You can search by gene symbol, gene name, genomic locus, HGNC identifier, or other indexed information. Results can be filtered by CMT classification, inheritance pattern, chromosome, mitochondrial involvement, and candidate-gene status, enabling examination of either an individual gene or a defined group of CMT genes.

Expanding a gene record reveals its associated CMT subtype(s), inheritance pattern(s), the year each association was first described, and the supporting publication. The record also connects directly to available HGNC, Ensembl, UniProt, OMIM, gnomAD, ClinVar, ClinGen, GeneReviews, MANE Select, and other records, allowing you to move from the CMT-specific view into the underlying genomic, variant, protein, clinical, or evidence data without needing to conduct a separate search at each platform.

Together, these search, filter, and cross-reference capabilities allow you to interrogate CMT genetics from multiple directions: “Which CMT subtypes are associated with this gene?” “Which autosomal recessive genes are associated with CMT2?” “What evidence and publications established this genotype-phenotype relationship?” And all from a single UI.

The CMT Gene Browser does not replace the databases it references. It instead connects them around the question they were not built to answer: What does this gene mean in CMT?

Genes, Chromosomes, and Unmapped CMT Subtypes

CMT disease genes are found on chromosomes 1 through 22, the X chromosome, and mitochondrial DNA (MT). No CMT gene has been mapped to the Y chromosome.

Five clinically described CMT subtypes have been mapped to a locus but do not have an identified disease gene: CMTX2, HMSN-5, HSAN-1B, HSN-1B, and dHMN-1. These subtypes remain part of the Experts in CMT dataset but are not surfaced here in the CMT Gene Browser because there is no gene record through which to connect them.

A Note About CMTX3

CMTX3 is the one record in the CMT Gene Browser that does not follow the gene-centered model. Its cause is not a coding gene but a structural rearrangement, an interchromosomal insertion at Xq27.1, represented in the International System for Human Cytogenomic Nomenclature (ISCN) notation as ins(X;8)(q27.1;q24.3) rather than by a gene symbol.

Although CMTX3 technically does not have a specific gene for the purpose of counting CMT genes, Experts in CMT counts its interchromosomal insertion as a gene in its datasets and includes it in the platform’s CMT gene count. Because HGNC does not provide an identifier for the rearrangement, the browser uses ISCN notation.

Candidate CMT Genes

Experts in CMT tracks candidate gene associations reported in the scientific literature, clinical or diagnostic contexts, or academic settings, but that do not currently meet the evidence criteria for inclusion as established CMT gene-disease associations.

Unlike the CMT Subtype Browser, where candidate genes are maintained separately from the primary results and excluded from CMT gene counts, the CMT Gene Browser surfaces candidate genes directly within the dataset. Each is clearly identified as a candidate, and researchers can use the Candidate Gene filter to isolate these records.

Experts in CMT does not attempt to resolve, validate, or adjudicate candidate gene associations. Their inclusion in the CMT Gene Browser provides researchers with visibility into reported CMT associations that remain preliminary, require further validation, or may warrant consideration as additional genetic and clinical evidence becomes available.

What the CMT Gene Browser Does Not Do

This page is intended as an educational and reference resource only. It does not provide medical advice, variant interpretation, diagnostic guidance, or disease management recommendations. Genetic testingdiagnosis, and healthcare decisions should always be made in consultation with a qualified healthcare professional.

Download the Dataset

Download the dataset

Version 1.0.3 · August 17, 2026 · ZIP 152.7 KB · JSON, CSV, README, license · CC BY 4.0

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How to Cite

Experts in CMT. (2026). Experts in CMT: CMT Gene Browser (Version 1.0.3) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21970234


CMT Gene Browser

Every gene known to cause CMT. Each is cross-referenced to HGNC, Ensembl, UniProt, OMIM, MANE Select, gnomAD, ClinVar, and ClinGen, and lists every subtype it causes with its defining publication.

140+ CMT disease genes cataloged
170+ classified subtypes
GeneFull nameLocusInh.SubtypesSubtype ClassificationDetails

Sources

Records referenced in the CMT Gene Browser are drawn from HGNC (gene nomenclature), MANE (reference transcripts), UniProt (protein annotations), ClinVar (variant classifications), ClinGen (gene-disease validity and dosage sensitivity classifications), gnomAD (population frequency and constraint), OMIM (record identifiers only), Genomics England PanelApp (panel and entity identifiers only), and the Genesis Project Foundation (discovery attributions). Source data for this release was obtained on August 2, 2026.

The GENESIS discovery flag carried by certain gene records indicates that the gene-disease association was identified through work conducted on the GENESIS platform, as published by the Genesis Project Foundation. No GENESIS platform data is included in the CMT Gene Browser.

ClinGen

Curated content was obtained from the Clinical Genome Resource: Gene-Disease Validity classifications and Gene Dosage Sensitivity classifications, accessed August 2, 2026. ClinGen itself recommends citation of its marker paper and, for work focused on its curation activities, the later ClinGen Consortium paper.

  1. Rehm HL, Berg JS, Brooks LD, Bustamante CD, Evans JP, Landrum MJ, Ledbetter DH, Maglott DR, Martin CL, Nussbaum RL, Plon SE, Ramos EM, Sherry ST, Watson MS. ClinGen: the Clinical Genome Resource. New England Journal of Medicine. 2015;372(23):2235-2242. doi: 10.1056/NEJMsr1406261
  2. ClinGen Consortium. The Clinical Genome Resource (ClinGen): advancing genomic knowledge through global curation. Genetics in Medicine. 2025;27(1):101228. doi: 10.1016/j.gim.2024.101228

ClinVar

  1. Landrum MJ, Lee JM, Benson M, Brown GR, Chao C, Chitipiralla S, Gu B, Hart J, Hoffman D, Jang W, Karapetyan K, Katz K, Liu C, Maddipatla Z, Malheiro A, McDaniel K, Ovetsky M, Riley G, Zhou G, Holmes JB, Kattman BL, Maglott DR. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Research. 2018;46(D1):D1062-D1067. doi: 10.1093/nar/gkx1153

Ensembl

  1. Dyer SC, Austine-Orimoloye O, Azov AG, Barba M, Barnes I, Barrera-Enriquez VP, Becker A, Bennett R, Beracochea M, Berry A, et al. Ensembl 2025. Nucleic Acids Research. 2025;53(D1):D948-D957. doi: 10.1093/nar/gkae1071

Genesis Project Foundation

  1. Genesis Project Foundation. Discoveries. https://tgp-foundation.org/d-i-s-c-o-v-e-r-i-e-s
  2. Gonzalez M, Falk MJ, Gai X, Postrel R, Schüle R, Züchner S. Innovative Genomic Collaboration Using the GENESIS (GEM.app) Platform. Human Mutation. 2015;36(10):950-956. doi: 10.1002/humu.22836

gnomAD

  1. Chen S, Francioli LC, Goodrich JK, et al.; Genome Aggregation Database Consortium. A genomic mutational constraint map using variation in 76,156 human genomes. Nature. 2024;625(7993):92-100. doi: 10.1038/s41586-023-06045-0
  2. Karczewski KJ, Francioli LC, Tiao G, et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020;581(7809):434-443. doi: 10.1038/s41586-020-2308-7

HGNC

  1. Seal RL, Braschi B, Gray K, McClay J, Tweedie S, Bruford EA. Genenames.org: the HGNC and PGNC resources in 2026. Nucleic Acids Research. 2026;54(D1):D1098-D1107. doi: 10.1093/nar/gkaf1229
  2. HGNC Database, HUGO Gene Nomenclature Committee (HGNC), Department of Haematology, University of Cambridge, School of Clinical Medicine, Cambridge CB2 0PT, United Kingdom. Data retrieved August 2026.

MANE

  1. Morales J, Pujar S, Loveland JE, et al. A joint NCBI and EMBL-EBI transcript set for clinical genomics and research. Nature. 2022;604(7905):310-315. doi: 10.1038/s41586-022-04558-8

MONDO

  1. Vasilevsky NA, Matentzoglu NA, Toro S, Flack JE, Hegde H, Unni DR, Alyea GF, Amberger JS, Babb L, Balhoff JP, et al. Mondo: Unifying diseases for the world, by the world. medRxiv. 2022. doi:10.1101/2022.04.13.22273750

OMIM

  1. Amberger JS, Bocchini CA, Schiettecatte F, Scott AF, Hamosh A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Research. 2015;43(D1):D789-D798. doi: 10.1093/nar/gku1205

PanelApp

  1. Martin AR, Williams E, Foulger RE, Leigh S, Daugherty LC, Niblock O, Leong IUS, Smith KR, Gerasimenko O, Haraldsdottir E, Thomas E, Scott RH, Baple E, Tucci A, Brittain H, de Burca A, Ibañez K, Kasperaviciute D, Smedley D, Caulfield M, Rendon A, McDonagh EM. PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Nature Genetics. 2019;51(11):1560-1565. doi: 10.1038/s41588-019-0528-2

UniProt

  1. The UniProt Consortium. UniProt: the Universal Protein Knowledgebase in 2025. Nucleic Acids Research. 2025;53(D1):D609-D617. doi: 10.1093/nar/gkae1010

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