A Phenotype-Driven Approach To Mitochondrial Dna Disease Identification Using Mitophen

Objectives Mitochondrial diseases are difficult to diagnose owing to phenotypic and genetic heterogeneity. Next generation sequencing (NGS) methods may improve diagnostic rates. We aimed to use a manually curated mitochondrial DNA (mtDNA) disease database- MitoPhen (1)- to investigate the phenotype similarities between patients with rare disease recruited to Solve-RD (2).

Methods MitoPhen was created through the manual reclassification of mtDNA variants, and review of all associated published patients with phenotype data entered as Human Phenotype Ontology (HPO) terms (1). Phenotype similarity scores were performed between probands in MitoPhen, and patients enrolled in Solve-RD.

Results MitoPhen is populated with 676 publications detailing 6688 individuals with one of the 89 pathogenic mtDNA variants. There are 3696 (55%) individuals recorded as clinically affected and 1349 (20%) have Paediatric-onset disease (1). The Solve-RD dataset consisted of 53 mtDNA disease patients, 170 patients with a ‘nuclear-mitochondrial’ disease, and 653 patients with a ‘nuclear-other’ genetic disease. Phenotype similarity scores were calculated through MitoPhen (1) and showed a statistically significant difference between the mtDNA and other genetic groups.

Conclusions This work highlights the utility of MitoPhen- a manually curated mtDNA disease database- in the phenotype-driven approach to identifying patients with mtDNA diseases.

References 1) Ratnaike TE, Greene D, et al. MitoPhen database: a human phenotype ontology-based approach to identify mitochondrial DNA diseases. Nucleic Acids Res. 2021. doi: 10.1093/nar/gkab726. 2) Zurek, B., Ellwanger, K., Vissers, L.E.L.M. et al. Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases. Eur J Hum Genet 2021. https://doi.org/10.1038/s41431-021-00859-0