Clinical utility of multigene analysis in over 25, 000 patients with neuromuscular disorders. (April 2020)

• Record Type: Journal Article
• Authors: Winder, Thomas L.; Tan, Christopher A.; Klemm, Sarah; White, Hannah; Westbrook, Jody M.; Wang, James Z.; Entezam, Ali; Truty, Rebecca; Nussbaum, Robert L.; McNally, Elizabeth M.; Aradhya, Swaroop
• Is Part Of: Neurology. Volume 6:Number 2(2020)
• Publication Date: 2020-04
• Subjects: Neurogenetics -- Periodicals; 616.80442
• DOI: 10.1212/NXG.0000000000000412
• Languages: English
• ISSNs: 2376-7839

Abstract

Abstract : Objective: Molecular genetic testing for hereditary neuromuscular disorders is increasingly used to identify disease subtypes, determine prevalence, and inform management and prognosis, and although many small disease-specific studies have demonstrated the utility of genetic testing, comprehensive data sets are better positioned to assess the complexity of genetic analysis. Methods: Using high depth-of-coverage next-generation sequencing (NGS) with simultaneous detection of sequence variants and copy number variants (CNVs), we tested 25, 356 unrelated individuals for subsets of 266 genes. Results: A definitive molecular diagnosis was obtained in 20% of this cohort, with yields ranging from 4% among individuals with congenital myasthenic syndrome to 33% among those with a muscular dystrophy. CNVs accounted for as much as 39% of all clinically significant variants, with 10% of them occurring as rare, private pathogenic variants. Multigene testing successfully addressed differential diagnoses in at least 6% of individuals with positive results. Even for classic disorders like Duchenne muscular dystrophy, at least 49% of clinically significant results were identified through gene panels intended for differential diagnoses rather than through single-gene analysis. Variants of uncertain significance (VUS) were observed in 53% of individuals. Only 0.7% of these variants were later reclassified as clinically significant, most commonly in RYR1, GDAP1, SPAST, and MFN2, providing insight into the types of evidence that support VUS resolution and informing expectations of reclassification rates. Conclusions: These data provide guidance for clinicians using genetic testing to diagnose neuromuscular disorders and represent one of the largest studies demonstrating the utility of NGS-based testing for these disorders.