Whole Genome Sequencing for Variant Detection in Charcot-Marie-Tooth Disease: A Cross-sectional Diagnostic Study.

ABSTRACT

Introduction: Charcot-Marie-Tooth disease (CMT) is one of the most common inherited Neuromuscular Disorders (NMDs), classified under peripheral neuropathies and characterised by progressive motor and sensory dysfunction. Although Wholeexome Sequencing (WES), gene panels, and conventional methods have improved detection rates, they often miss deep intronic, regulatory, and Structural Variants (SVs). Wholegenome Sequencing (WGS), with its comprehensive coverage of coding and non coding regions, enables the identification of variants that are often overlooked by other approaches. Aim: To assess the diagnostic utility of WGS in CMT cases that remain unresolved by WES, analysing both coding and non coding variants. Materials and Methods: The present cross-sectional diagnostic study was conducted between July 2023 and January 2025 at the Neuberg Center for Genomic Medicine (NCGM), Ahmedabad, Gujarat, India. WGS was performed on 31 clinically suspected CMT patients, including two who had previously tested negative by WES. Both coding and non coding variants including missense, nonsense, frameshift, in-frame, intronic, and 5’ Untranslated Region (UTR) mutations were analysed. Variants were classified according to American College of Medical Genetics and Genomics (ACMG) guidelines, incorporating Combined Annotation Dependent Depletion (CADD) scores and Minor Allele Frequency (MAF) thresholds. They were interpreted based on pathogenicity, inheritance patterns, and genotypephenotype correlations. Selected non coding variants in the Gap Junction Beta-1 (GJB1; c.-16-511G>C) and Lamin A/C (LMNA; c.-142C>A) genes were validated by Sanger sequencing. Results: Sequencing data from 31 participants were processed using a standardised bioinformatics pipeline. Variants were classified according to ACMG guidelines, and their frequencies were calculated. WES and WGS results were compared to determine the additional diagnostic yield. WGS identified clinically significant non coding variants in GJB1 (intronic) and LMNA (5’ UTR) in two cases, yielding a 6.5% increase over WES. Overall, 31 variants were detected: 11 (35.5%) classified as pathogenic, 2 (6.5%) as likely pathogenic, and 18 (58.0%) as Variants of Uncertain Significance (VUS), reflecting the genetic heterogeneity of CMT. Conclusion: The WGS enhances diagnostic accuracy in CMT by detecting clinically relevant non coding variants often missed by WES. This is the first report from India confirming a GJB1 intronic variant and a Lamin A/C (LMNA) 5´ UTR variant using WGS in CMT patients. These findings support the integration of WGS into routine diagnostic workflows and highlight the value of comprehensive variant analysis for early and precise genetic diagnosis.