[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.
Disciplines :
Neurology
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
External co-authors :
yes
Language :
English
Title :
Leigh Map: A Novel Computational Diagnostic Resource for Mitochondrial Disease
Publication date :
2017
Journal title :
Annals of Neurology
ISSN :
1531-8249
Publisher :
John Wiley & Sons, Hoboken, United States - New York
