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Molecular Diagnosis of Hereditary Neuropathies by Whole Exome Sequencing and Expanding the Phenotype Spectrum Publisher Pubmed



Taghizadeh S1, 2 ; Vazehan R3 ; Beheshtian M1, 3 ; Sadeghinia F1 ; Fattahi Z1, 3 ; Mohseni M1, 3 ; Arzhangi S1 ; Nafissi S4 ; Kariminejad A3 ; Najmabadi H1, 3 ; Kahrizi K1
Authors
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Authors Affiliations
  1. 1. Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
  2. 2. Student Research Committee, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
  3. 3. Kariminejad - Najmabadi Pathology and Genetics Center, Tehran, Iran
  4. 4. Department of Neurology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

Source: Archives of Iranian Medicine Published:2020


Abstract

Background: Inherited peripheral neuropathies (IPNs) are a group of neuropathies affecting peripheral motor and sensory neurons. Charcot-Marie-Tooth (CMT) disease is the most common disease in this group. With recent advances in next-generation sequencing (NGS) technologies, more than 100 genes have been implicated for different types of CMT and other clinically and genetically inherited neuropathies. There are also a number of genes where neuropathy is a major feature of the disease such as spinocerebellar ataxia (SCA) and hereditary spastic paraplegia (HSP). We aimed to determine the genetic causes underlying IPNs in Iranian families. Methods: We performed whole exome sequencing (WES) for 58 PMP22 deletion-/duplication-negative unrelated Iranian patients with a spectrum of phenotypes and with a preliminary diagnosis of hereditary neuropathies. Results: Twenty-seven (46.6%) of the cases were genetically diagnosed with pathogenic or likely pathogenic variants. In this study, we identified genetically strong variants within genes not previously linked to any established disease phenotype in five (8.6%) patients. Conclusion: Our results highlight the advantage of using WES for genetic diagnosis in highly heterogeneous diseases such as IPNs. Moreover, functional analysis is required for novel and uncertain variants. © 2020 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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