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.
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.
Authors: Elizabeth Wohler; Renan Martin; Sean Griffith; Eliete da S Rodrigues; Corina Antonescu; Jennifer E Posey; Zeynep Coban-Akdemir; Shalini N Jhangiani; Kimberly F Doheny; James R Lupski; David Valle; Ada Hamosh; Nara Sobreira Journal: Orphanet J Rare Dis Date: 2021-08-18 Impact factor: 4.123
Authors: Fuad Chowdhury; Lei Wang; Mohammed Al-Raqad; David J Amor; Alice Baxová; Šárka Bendová; Elisa Biamino; Alfredo Brusco; Oana Caluseriu; Nancy J Cox; Tawfiq Froukh; Meral Gunay-Aygun; Miroslava Hančárová; Devon Haynes; Solveig Heide; George Hoganson; Tadashi Kaname; Boris Keren; Kenjiro Kosaki; Kazuo Kubota; Jennifer M Lemons; Maria A Magriña; Paul R Mark; Marie T McDonald; Sarah Montgomery; Gina M Morley; Hidenori Ohnishi; Nobuhiko Okamoto; David Rodriguez-Buritica; Patrick Rump; Zdeněk Sedláček; Krista Schatz; Haley Streff; Tomoko Uehara; Jagdeep S Walia; Patricia G Wheeler; Antje Wiesener; Christiane Zweier; Koichi Kawakami; Ingrid M Wentzensen; Seema R Lalani; Victoria M Siu; Weimin Bi; Tugce B Balci Journal: Genet Med Date: 2021-04-06 Impact factor: 8.822