The Matchmaker Exchange: a platform for rare disease gene discovery.

Abstract

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.

• Authors: Anthony A Philippakis, Danielle R Azzariti, Sergi Beltran, Anthony J Brookes, Catherine A Brownstein, Michael Brudno, Han G Brunner, Orion J Buske, Knox Carey, Cassie Doll, Sergiu Dumitriu, Stephanie O M Dyke, Johan T den Dunnen, Helen V Firth, Richard A Gibbs, Marta Girdea, Michael Gonzalez, Melissa A Haendel, Ada Hamosh, Ingrid A Holm, Lijia Huang, Matthew E Hurles, Ben Hutton, Joel B Krier, Andriy Misyura, Christopher J Mungall, Justin Paschall, Benedict Paten, Peter N Robinson, François Schiettecatte, Nara L Sobreira, Ganesh J Swaminathan, Peter E Taschner, Sharon F Terry, Nicole L Washington, Stephan Züchner, Kym M Boycott, Heidi L Rehm
• Journal: Human mutation (Hum Mutat) Vol. 36 Issue 10 Pg. 915-21 (Oct 2015) ISSN: 1098-1004 [Electronic] United States
• PMID: 26295439 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
• Copyright: © 2015 WILEY PERIODICALS, INC.

Topics

• Database Management Systems
• Databases, Genetic
• Genetic Association Studies
• Genetic Predisposition to Disease (genetics)
• Humans
• Information Dissemination (methods)
• Rare Diseases (genetics)
• Software