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2.5 years’ experience of GeneMatcher data-sharing: a powerful tool for identifying new genes responsible for rare diseases

2018; Elsevier BV; Volume: 21; Issue: 7 Linguagem: Inglês

10.1038/s41436-018-0383-z

1530-0366

Ange‐Line Bruel, Antonio Vitobello, Frédéric Tran Mau‐Them, Sophie Nambot, Yannis Duffourd, Virginie Quéré, Paul Kuentz, Philippine Garret, Julien Thévenon, Sébastien Moutton, Daphné Lehalle, Nolwenn Jean‐Marçais, Aurore Garde, Julian Delanne, Mathilde Lefebvre, François Lecoquierre, Detlef Trost, Megan Cho, Amber Begtrup, Aida Telegrafi, P. Vabres, Anne‐Laure Mosca‐Boidron, Patrick Callier, Christophe Philippe, Laurence Faivre, Christel Thauvin-Robinet,

Genetics and Neurodevelopmental Disorders

PurposeExome sequencing (ES) powerfully identifies the molecular bases of heterogeneous conditions such as intellectual disability and/or multiple congenital anomalies (ID/MCA). Current ES analysis, combining diagnosis analysis restricted to disease-causing genes reported in OMIM database and subsequent research investigation extended to other genes, indicated causal and candidate genes around 40% and 10%. Nonconclusive results are frequent in such ultrarare conditions that recurrence and genotype-phenotype correlations are limited. International data-sharing permits the gathering of additional patients carrying variants in the same gene to draw definitive conclusions on their implication as disease causing. Several web-based tools have been developed and grouped in Matchmaker Exchange. In this study, we report our current experience as a regional center that has implemented ES as a first-line diagnostic test since 2013, working with a research laboratory devoted to disease gene identification.MethodsWe used GeneMatcher over 2.5 years to share 71 novel candidate genes identified by ES.ResultsMatches occurred in 60/71 candidate genes allowing to confirm the implication of 39% of matched genes as causal and to rule out 6% of them.ConclusionThe introduction of user-friendly gene-matching tools, such as GeneMatcher, appeared to be an essential step for the rapid identification of novel disease genes responsible for ID/MCA.