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MitoPhen database: a human phenotype ontology-based approach to identify mitochondrial DNA diseases.
Ratnaike, Thiloka E; Greene, Daniel; Wei, Wei; Sanchis-Juan, Alba; Schon, Katherine R; van den Ameele, Jelle; Raymond, Lucy; Horvath, Rita; Turro, Ernest; Chinnery, Patrick F.
Afiliación
  • Ratnaike TE; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
  • Greene D; Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
  • Wei W; Department of Paediatrics, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
  • Sanchis-Juan A; Department of Haematology, University of Cambridge, NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK.
  • Schon KR; Medical Research Council Biostatistics Unit, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK.
  • van den Ameele J; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
  • Raymond L; Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
  • Horvath R; Department of Haematology, University of Cambridge, NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK.
  • Turro E; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
  • Chinnery PF; Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Nucleic Acids Res ; 49(17): 9686-9695, 2021 09 27.
Article en En | MEDLINE | ID: mdl-34428295
ABSTRACT
Diagnosing mitochondrial disorders remains challenging. This is partly because the clinical phenotypes of patients overlap with those of other sporadic and inherited disorders. Although the widespread availability of genetic testing has increased the rate of diagnosis, the combination of phenotypic and genetic heterogeneity still makes it difficult to reach a timely molecular diagnosis with confidence. An objective, systematic method for describing the phenotypic spectra for each variant provides a potential solution to this problem. We curated the clinical phenotypes of 6688 published individuals with 89 pathogenic mitochondrial DNA (mtDNA) mutations, collating 26 348 human phenotype ontology (HPO) terms to establish the MitoPhen database. This enabled a hypothesis-free definition of mtDNA clinical syndromes, an overview of heteroplasmy-phenotype relationships, the identification of under-recognized phenotypes, and provides a publicly available reference dataset for objective clinical comparison with new patients using the HPO. Studying 77 patients with independently confirmed positive mtDNA diagnoses and 1083 confirmed rare disease cases with a non-mitochondrial nuclear genetic diagnosis, we show that HPO-based phenotype similarity scores can distinguish these two classes of rare disease patients with a false discovery rate <10% at a sensitivity of 80%. Enriching the MitoPhen database with more patients will improve predictions for increasingly rare variants.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: ADN Mitocondrial / Bases de Datos Factuales / Enfermedades Mitocondriales Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2021 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: ADN Mitocondrial / Bases de Datos Factuales / Enfermedades Mitocondriales Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2021 Tipo del documento: Article País de afiliación: Reino Unido