Plain-language medical vocabulary for precision diagnosis. - Vasilevsky, Nicole A; Foster, Erin D; Engelstad, Mark E; Carmody, Leigh; Might, Matt; Chambers, Chip; Dawkins, Hugh J S; Lewis, Janine; Della Rocca, Maria G; Snyder, Michelle; Boerkoel, Cornelius F; Rath, Ana; et al. (Nat Genet, 2018)

Matchmaker Exchange. - Sobreira, Nara L M; Arachchi, Harindra; Buske, Orion J; Chong, Jessica X; Hutton, Ben; Foreman, Julia; Schiettecatte, François; Groza, Tudor; Jacobsen, Julius O B; Haendel, Melissa A; Boycott, Kym M; Hamosh, Ada; et al. (Curr Protoc Hum Genet, 2017)
In well over half of the individuals with rare disease who undergo clinical or research next-generation sequencing, the responsible gene cannot be determined. Some reasons for this relatively low yield include unappreciated phenotypic heterogeneity; locus heterogeneity; somatic and germline mosaicism; variants of uncertain functional significance; technically inaccessible areas of the genome; incorrect mode of inheritance investigated; and inadequate communication between clinicians and basic scientists with knowledge of particular genes, proteins, or biological systems. To facilitate such communication and improve the search for patients or model organisms with similar phenotypes and variants in specific candidate genes, we have developed the Matchmaker Exchange (MME). MME was created to establish a federated network connecting databases of genomic and phenotypic data using a common application programming interface (API). To date, seven databases can exchange data using the API (GeneMatcher, PhenomeCentral, DECIPHER, MyGene2, matchbox, Australian Genomics Health Alliance Patient Archive, and Monarch Initiative; the latter included for model organism matching). This article guides usage of the MME for rare disease gene discovery. © 2017 by John Wiley & Sons, Inc.
Keywords: Animals; Computational Biology; Databases, Genetic; Genetic Association Studies; Genetic Predisposition to Disease; Genomics; Humans; Rare Diseases; Software; Web Browser

The Matchmaker Exchange: a platform for rare disease gene discovery. - Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; et al. (Hum Mutat, 2015)
There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.
Keywords: Database Management Systems; Databases, Genetic; Genetic Association Studies; Genetic Predisposition to Disease; Humans; Information Dissemination; Rare Diseases; Software