Reference : Leigh Map: A Novel Computational Diagnostic Resource for Mitochondrial Disease
Scientific journals : Article
Human health sciences : Neurology
Systems Biomedicine
http://hdl.handle.net/10993/29127
Leigh Map: A Novel Computational Diagnostic Resource for Mitochondrial Disease
English
Rhaman, Joyeeta mailto [UCL Great Ormond Street Institute of Child Health > Mitochondrial Research Group, Genetics and Genomic Medicine Programme]
Noronha, Alberto mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Thiele, Ines mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Rahman, Shamima mailto [UCL Great Ormond Street Institute of Child Health, London, UK > Mitochondrial Research Group, Genetics and Genomic Medicine Programme > > ; Great Ormond Street Hospital NHS Foundation Trust, London, UK > Metabolic Department]
2017
Annals of Neurology
Yes (verified by ORBilu)
International
1531-8249
[en] Leigh syndrome ; mitochondrial disease ; gene-phenotype interaction ; computational network ; bioinformatics
[en] Mitochondrial disorders are amongst the most severe metabolic disorders and are beset by genetic, biochemical, and clinical heterogeneity. Variation between individuals and poor understanding of disease pathophysiology pose significant diagnostic challenges. We present a novel interactive computational network, the Leigh Map, cataloguing >1700 gene-to-phenotype interactions in Leigh syndrome, the most common and genetically heterogeneous mitochondrial disorder. Blinded validation of the Leigh Map yielded an 80% success rate in correct identification of causative genes. We conclude that the Leigh Map is an efficacious resource that, in combination with whole-exome sequencing, can be utilized as a novel diagnostic resource for mitochondrial disease.
http://hdl.handle.net/10993/29127
10.1002/ana.24835

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