Reference : Leigh Map: A Novel Computational Diagnostic Resource for Mitochondrial Disease

	Document type :	Scientific journals : Article
	Discipline(s) :	Human health sciences : Neurology
	Focus Areas :	Systems Biomedicine
	To cite this reference:	http://hdl.handle.net/10993/29127

Title :	Leigh Map: A Novel Computational Diagnostic Resource for Mitochondrial Disease
Language :	English
Author, co-author :	Rhaman, Joyeeta [UCL Great Ormond Street Institute of Child Health > Mitochondrial Research Group, Genetics and Genomic Medicine Programme]
	Noronha, Alberto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Thiele, Ines [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Rahman, Shamima [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]
Publication date :	2017
Journal title :	Annals of Neurology
Peer reviewed :	Yes (verified by ORBilu)
Audience :	International
e-ISSN :	1531-8249
Keywords :	[en] Leigh syndrome ; mitochondrial disease ; gene-phenotype interaction ; computational network ; bioinformatics
Abstract :	[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.
Permalink :	http://hdl.handle.net/10993/29127
DOI :	10.1002/ana.24835

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