The utility of phenomics in diagnosis of inherited metabolic disorders

Abstract

Inherited metabolic disorders (IMDs) are debilitating inherited diseases, with phenotypic, biochemical and genetic heterogeneity, frequently leading to prolonged diagnostic Odysseys. Mitochondrial disorders represent one of the most severe classes of IMDs, wherein defects in >350 genes lead to multisystem disease. Diagnostic rates have improved considerably following the adoption of next-generation sequencing (NGS) technologies, but are still far from perfect. Phenomic annotation is an emerging concept which is being utilised to enhance interpretation of NGS results. To test whether phenomic correlations have utility in mitochondrial disease and IMDs, we created a gene-to-phenotype interaction network with searchable elements, for Leigh syndrome, a frequently observed paediatric mitochondrial disorder. The Leigh Map comprises data on 92 genes and 275 phenotypes standardised in human phenotype ontology terms, with 80% predictive accuracy. This commentary highlights the usefulness of the Leigh Map and similar resources and the challenges associated with integrating phenomic technologies into clinical practice.