From Negative to Positive Diagnosis: Structural Variation Could Be the Second Mutation You Are Looking for in a Recessive Autosomal Gene

Next-generation sequencing (NGS) allows the detection of plentiful mutations increasing the rate of patients getting a positive diagnosis. However, while single-nucleotide variants (SNVs) or small indels can be easily detected, structural variations (SVs) such as copy number variants (CNVs) are often not researched. In Charcot-Marie-Tooth disease (CMT), the most common hereditary peripheral neuropathy, the PMP22-duplication was the first variation detected. Since then, more than 90 other genes have been associated with CMT, with point mutations or small indels mostly described. Herein, we present a personalized approach we performed to obtain a positive diagnosis of a patient suffering from demyelinating CMT. His NGS data were aligned to the human reference sequence but also studied using the CovCopCan software, designed to detect large CNVs. This approach allowed the detection of only one mutation in SH3TC2, the frequent p.Arg954*, while SH3TC2 is known to be responsible for autosomal recessive demyelinating CMT forms. Interestingly, by modifying the standard CovCopCan use, we detected the second mutation of this patient corresponding to a 922 bp deletion in SH3TC2 (Chr5:148,390,609-Chr5:148,389,687), including only one exon (exon 14). This highlights that SVs, different from PMP22 duplication, can be responsible for peripheral neuropathy and should be searched systematically. This approach could also be employed to improve the diagnosis of all inherited diseases.

Automated summary

Next-generation sequencing (NGS) has increased the ability to diagnose patients through the detection of numerous mutations, however, structural variations (SVs) such as copy number variants (CNVs) are often overlooked. This study presents a personalized approach for the positive diagnosis of a patient with demyelinating Charcot-Marie-Tooth disease (CMT) using NGS data and specialized software to detect CNVs. This approach revealed the presence of a previously undetected mutation in SH3TC2, highlighting the importance of systematically searching for SVs in peripheral neuropathy diagnoses.