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Outcome of over 1500 matches through the Matchmaker Exchange for rare disease gene discovery: The 2-year experience of Care4Rare Canada

Matthew Osmond, Taila Hartley, David A. Dyment, Kristin D. Kernohan, Michael Brudno, Orion J. Buske, A. Micheil Innes, Kym M. Boycott, Kym M. Boycott, Michael Brudno, François P. Bernier, Clara van Karnebeek, David A. Dyment, Kristin D. Kernohan, Micheil Innes, Ryan E. Lamont, Jillian S. Parboosingh, Deborah A. Marshall, Christian R. Marshall, Roberto Mendoza‐Londono, James J. Dowling, Robin Z. Hayeems, Bartha Maria Knoppers, Anna Lehman, Sara Mostafavi

2021Genetics in Medicine26 citationsDOIOpen Access PDF

Abstract

PURPOSE: Matchmaking has emerged as a useful strategy for building evidence toward causality of novel disease genes in patients with undiagnosed rare diseases. The Matchmaker Exchange (MME) is a collaborative initiative that facilitates international data sharing for matchmaking purposes; however, data on user experience is limited. METHODS: Patients enrolled as part of the Finding of Rare Disease Genes in Canada (FORGE) and Care4Rare Canada research programs had their exome sequencing data reanalyzed by a multidisciplinary research team over a 2-year period. Compelling variants in genes not previously associated with a human phenotype were submitted through the MME node PhenomeCentral, and outcomes were collected. RESULTS: In this study, 194 novel candidate genes were submitted to the MME, resulting in 1514 matches, and 15% of the genes submitted resulted in collaborations. Most submissions resulted in at least 1 match, and most matches were with GeneMatcher (82%), where additional email exchange was required to evaluate the match because of the lack of phenotypic or inheritance information. CONCLUSION: Matchmaking through the MME is an effective way to investigate novel candidate genes; however, it is a labor-intensive process. Engagement from the community to contribute phenotypic, genotypic, and inheritance data will ensure that matchmaking continues to be a useful approach in the future.

Topics & Concepts

Multidisciplinary approachInheritance (genetic algorithm)GeneDiseasePhenotypeExome sequencingExomeCandidate geneCausality (physics)Computational biologyGeneticsMedicineBiologyPolitical scienceInternal medicinePhysicsQuantum mechanicsLawGenomics and Rare DiseasesGenetic Associations and EpidemiologyGenetic Syndromes and Imprinting
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