Reducing the Diagnostic Odyssey for Patients with Neuromuscular Disorders (NMDs)

Fast and accurate diagnosis of neuromuscular disorders (NMDs) remains challenging for clinicians. Consequently, patients with NMDs typically face a diagnostic odyssey. Recently, Next-Generation Sequencing (NGS) has become a promising technology to shorten the average diagnostic odyssey. However, the lack of a standardised diagnosticworkflowfor end-userswithout extensive bioinformatics background impedes its usage. Therefore, our project aims to design a simplified yet comprehensive pipeline to accurately identify disease-causing variants in NMD patients more quickly. The pipeline comprises filters for quality control score, population frequency and disease-phenotype associations. By filtering Whole-Exome Sequencing (WES) data through our customised pipeline, a total of 630,297 variants were prioritised for disease-causing variants in 3 unrelated, undiagnosed NMD patients. Variant curation was then conducted based on the American College of Medical Genetics and Genomics (ACMG) guidelines. In Case 1, a missensemutation in Fused in Sarcoma (FUS) gene was found as a strong candidate variant most likely associated with Amyotrophic Lateral Sclerosis 6. For Case 2, a missense variant in Kinesin Family Member 1B (KIF1B) gene was the highest-ranking causative variant most likely associated with Charcot-Marie-Tooth disease. However, no high-ranking causative variants were found in Case 3. Thus, although the proposed pipeline did not yield conclusive pathogenic genes, this WES-based pipeline narrowed down causative candidates for the cases and can reduce efforts in clinical validation by providing clinicians with a more refined dataset for a more accurate diagnosis of NMD patients. It can be successfully adapted to a clinical setting for the diagnosis of other rare NMDs, thereby shortening the diagnostic odyssey of many patients.