Neuromuscular Disorders in Children through the Lens of Next Generation Sequencing: A Study of Diagnostic Yield
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background: Pediatric-onset neuromuscular diseases (NMDs) represent a clinically and genetically heterogeneous group of rare disorders, often posing significant diagnostic challenges due to overlapping phenotypes. Next-generation sequencing (NGS), particularly whole-exome sequencing (WES), has transformed the diagnostic landscape; however, its clinical utility varies across phenotypic subgroups. Methods: We conducted a combined retrospective–prospective cohort study including 100 pediatric patients with suspected neuromuscular disorders evaluated at a tertiary referral center between 2015 and 2025. Patients were stratified into seven clinically defined diagnostic categories prior to genetic testing. NGS-based diagnostics (primarily WES) were performed following initial clinical and targeted evaluations. Diagnostic yield and predictors of a positive genetic result were analyzed using univariate and multivariable statistical approaches. Results: A molecular diagnosis was established in 71% of patients, including 64% with pathogenic/likely pathogenic variants and 7% with clinically consistent variants of uncertain significance. Diagnostic yield varied significantly across disease categories (p < 0.001), reaching near-complete rates in well-defined phenotypes such as congenital myasthenic syndromes, neuropathies, and metabolic myopathies, while markedly lower yield was observed in unclassified cases (38.2%). Multivariable logistic regression identified disease group as the only independent predictor of diagnostic success (B = −0.436, p = 0.001). Frequently implicated genes included DMD, RYR1, and LAMA2, reflecting a predominance of structural and excitation–contraction coupling defects. Conclusions: NGS demonstrates high diagnostic utility in pediatric neuromuscular disorders, particularly when applied in a phenotype-driven framework. Diagnostic performance is strongly influenced by the degree of clinical definition prior to testing, highlighting the continued importance of expert phenotyping in the genomic era.