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Challenges in modelling the Charcot-Marie-Tooth neuropathies for therapy development
  1. Manisha Juneja1,2,
  2. Joshua Burns3,
  3. Mario A Saporta4,
  4. Vincent Timmerman1,2
  1. 1 Peripheral Neuropathy Research Group, University of Antwerp, Antwerp, Belgium
  2. 2 Neurogenetics Labatory, Institute Born Bunge, Antwerp, Belgium
  3. 3 University of Sydney, Faculty of Health Sciences & Sydney Children’s Hospitals Network, Sydney, New South Wales, Australia
  4. 4 Department of Neurology, Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, USA
  1. Correspondence to Dr Vincent Timmerman, Peripheral Neuropathy Research Group, University of Antwerp, Antwerp 2610, Belgium; vincent.timmerman{at}


Much has been achieved in terms of understanding the complex clinical and genetic heterogeneity of Charcot-Marie-Tooth neuropathy (CMT). Since the identification of mutations in the first CMT associated gene, PMP22, the technological advancement in molecular genetics and gene technology has allowed scientists to generate diverse animal models expressing monogenetic mutations that closely resemble the CMT phenotype. Additionally, one can now culture patient-derived neurons in a dish using cellular reprogramming and differentiation techniques. Nevertheless, despite the fact that finding a disease-causing mutation offers a precise diagnosis, there is no cure for CMT at present. This review will shed light on the exciting advancement in CMT disease modelling, the breakthroughs, pitfalls, current challenges for scientists and key considerations to move the field forward towards successful therapies.

  • neuropathy

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  • Contributors MJ, JB, MAS and VT contributed to the writing of this review.

  • Funding The research by MJ and VT are supported in part by the Fund for Scientific Research (FWO-Flanders), the ‘Association Belge contre les Maladies Neuromusculaires’ (ABMM), the Medical Foundation Queen Elisabeth (GSKE), the Association Française contre les Myopathies (AFM), the Muscular Dystrophy Association (MDA) and the Solve-RD project from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257.

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement No additional data are available.

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