2.5 years’ experience of GeneMatcher data-sharing: a powerful tool for identifying new genes responsible for rare diseases.
Authors of this article are:
Bruel AL, Vitobello A, Mau-Them FT, Nambot S, Duffourd Y, Quéré V, Kuentz P, Garret P, Thevenon J, Moutton S, Lehalle D, Jean-Marçais N,; Orphanomix Physicians’ Group, Garde A, Delanne J, Lefebvre M, Lecoquierre F, Trost D, Cho M, Begtrup A, Telegrafi A, Vabres P, Mosca-Boidron AL, Callier P, Philippe C, Faivre L, Thauvin-Robinet C,.
A summary of the article is shown below:
PURPOSE: Exome 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.METHODS: We used GeneMatcher over 2.5 years to share 71 novel candidate genes identified by ES.RESULTS: Matches 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.CONCLUSION: The 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.
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