Multiomics tools for the diagnosis and treatment of rare neurological disease

Abstract

Conventional workup of rare neurological disease is frequently hampered by diagnostic delay or lack of diagnosis. While biomarkers have been established for many neurometabolic disorders, improved methods are required for diagnosis of previously unidentified or underreported causes of rare neurological disease. This would result in a higher diagnostic yield and increased patient numbers required for interventional studies. Recent studies using next-generation sequencing and metabolomics have led to identification of novel disease-causing genes and biomarkers. This combined approach can assist in overcoming challenges associated with analyzing and interpreting the large amount of data obtained from each technique. In particular, metabolomics can support the pathogenicity of sequence variants in genes encoding enzymes or transporters involved in metabolic pathways. Moreover, metabolomics can show the broader perturbation caused by inborn errors of metabolism and identify a metabolic fingerprint of metabolic disorders. As such, using "omics" has great potential to meet the current needs for improved diagnosis and elucidation of rare neurological disease.