Leigh map: A novel computational diagnostic resource for mitochondrial disease

Mitochondrial disorders are among the most severe metabolic disorders wherein patients suffer from multisystemic phenotypes, often resulting in early death. Clinical, biochemical, and genetic heterogeneity among individuals, together with poor understanding of gene-tophenotype relationships, pose significant diagnostic and therapeutic challenges for clinicians. In light of recent advances in next generation sequencing technologies, whole exome sequencing (WES) is emerging as the new global standard for the diagnosis of monogenic disorders, including mitochondrial diseases. However, owing to genetic heterogeneity of mitochondrial disorders and ongoing discovery of novel disease genes, WES data may not provide clinicians with enough certainty for a definitive diagnosis. With these challenges in mind, we present the Leigh Map, a novel computational gene-to-phenotype network to be used as a diagnostic resource for mitochondrial disease, using Leigh syndrome (Mendelian Inheritance in Man 256000), the most genetically heterogeneous and most frequent phenotype of pediatric mitochondrial disease, as a prototype. Leigh syndrome is a progressive neurodegenerative disorder defined neuropathologically by spongiform basal ganglia and brainstem lesions. Clinical manifestations include psychomotor retardation, with regression, and progressive neurological abnormalities related to basal ganglia and/or brainstem dysfunction, often resulting in death within 2 years of initial presentation. However, many patients may also present with multisystemic (eg, cardiac, hepatic, renal, or hematological) phenotypes. To date, there are 89 genes known to cause Leigh syndrome, the majority of which are difficult to definitively differentiate from each other, either biochemically or clinically. We hypothesized that these multisystemic features may help to distinguish different genetic subtypes of Leigh syndrome. The Leigh Map (freely available at vmh.uni.lu/ #leighmap), was built on the Molecular Interaction NEtwoRks VisuAlization (MINERVA) platform previously used to construct networks of Parkinson disease and human metabolism. The network comprises 89 genes and 236 phenotypes, expressed in Human Phenotypic Ontology (HPO) terms, providing sufficient phenotypic and genetic variation to test the network’s diagnostic capability. The Leigh Map aims to enhance the interpretation of WES data to aid clinicians in providing faster and more accurate diagnoses for patients so that appropriate measures can be taken for optimal management. The phenotypic components of the Leigh Map can be queried to generate a list of candidate genes. In addition, the genetic components of the Leigh Map may also be queried to browse a list of all reported phenotypes associated with a particular gene defect. We propose that this functionality can be used to enhance clinical surveillance of patients with an established genetic diagnosis. Blinded validation of test cases containing