Augmenting Diagnostic Yield From Genomic Testing in Neurological Diseases

Despite the high utility of clinical genome sequencing (GS) in diagnosing rare neurological disorders, a significant proportion of patients remain molecularly unsolved or receive results involving variants of uncertain significance (VUS). To bridge this diagnostic gap, neurologists should employ a multi-modal strategy incorporating targeted functional studies and systematic data reanalysis. When DNA sequencing identifies potentially spliceogenic variants, targeted RNA analysis using whole blood serves as an effective surrogate for inaccessible nervous tissue, enabling the reclassification of 79% of such variants and providing a molecular diagnosis for approximately 53% of these cases. Notably, transcriptomic analysis of blood is broadly applicable, as 77% of common neurodevelopmental genes exhibit sufficient expression levels in whole blood for targeted studies. For patients with initially nondiagnostic GS results, comprehensive reanalysis conducted every 12 to 24 months can achieve an additional diagnostic yield of 5.1% by applying advanced bioinformatics pipelines capable of detecting complex variants missed by standard clinical algorithms, such as short tandem repeat (STR) expansions, structural variants (SVs), and low-level mosaicism. This diagnostic process is further optimized through longitudinal phenotyping, where evolving clinical presentations are shared between the neurologist and the laboratory to inform new gene-disease associations or clarify the relevance of previously ignored variants. Implementing these integrated approaches significantly enhances clinical utility by facilitating access to precision therapies, clarifying prognosis, and providing accurate recurrence risk for families.