Matchmaking disease

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GeneYenta: matchmaking for rare disease patients

This page was last edited on 8 January , at By using this site, you agree to the Terms of Use and Privacy Policy. The first iteration of the MME enables investigators with unsolved rare disease cases to submit their patient data and thereby find each other and undertake selective data sharing.


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This balances support for gene discovery with a researcher's desire to protect resource investment in identifying candidate genes. Alternative methods could be used for matchmaking within controlled access and open access environments, some of which would allow researchers to query databases even without patient data in hand or in situations where submission of patient data is not permitted. Many argue for a far more open environment for data sharing, which would drive scientific discovery in many more ways. For example, a researcher studying a biological pathway may hypothesize that genes in that pathway, when mutated, could cause disorders affecting a certain organ system and wish to validate that hypothesis in the absence of having access to real cases.

If that researcher could query MME services for cases with relevant phenotypes and deleterious variants in pathway genes, such a hypothesis could be more quickly validated and form the basis for future studies. Similarly, researchers may wish to perform meta-analyses of large datasets to arrive at generalized conclusions as well as have access to large datasets to train algorithms for pathogenicity detection. To enable these types of investigations, MME systems will need to designate datasets and provide services that allow searching without requiring data deposition of a patient case.

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Others services are committed to supporting such activities in the future. We hope that the MME will grow into a large and vibrant community of commercial, clinical, and academic users who are committed to a federated model of data sharing for the advancement of science and medicine.

In summary, this paper provides an overview of the Matchmaker Exchange, from its founding principles and goals to the steps required to launch it as a robust platform for rare disease discovery. The ensuing papers in this special issue of Human Mutation define many of the individual matchmaker services already connected Buske, et al. A few case examples of discoveries already made through use of matchmaking approaches are highlighted to add further support for this robust approach to rare disease gene discovery Au et al.

It is our hope that the success of the MME will serve as a model and foundation for innovative data sharing that leverages the increasing role of computational infrastructure to support the scaling of genomics as we collectively advance medicine and improve human health. Holm are supported in part by grant HG Holm is also supported by grant HG and grant HD Additional support for C.

Can you find patients online?

Department of Energy under [Contract No. Gibbs is supported in part by grant U54 HG The following authors have a commercial conflict of interest: Gibbs is the acting C. Philippakis is a Venture Partner at Google Ventures. National Center for Biotechnology Information , U. Author manuscript; available in PMC Oct 1.

Philippakis , 1, 2, 3 Danielle R. Azzariti , 4 Sergi Beltran , 5 Anthony J. Brookes , 6 Catherine A. Brownstein , 3, 18 Michael Brudno , 9, 10, 11 Han G. Brunner , 24, 25 Orion J. Dyke , 20 Johan T. Firth , 37 Richard A. Haendel , 16 Ada Hamosh , 8 Ingrid A.


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  • Opinion | Genetic matchmaking can improve medical outcomes.
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Holm , 3, 18 Lijia Huang , 23 Matthew E. Hurles , 27 Ben Hutton , 27 Joel B. Krier, 3 , 33 Andriy Misyura , 11 Christopher J. Sobreira , 8 Ganesh J. Swaminathan , 27 Peter E. Taschner , 16, 33 Sharon F. Terry , 13 Nicole L. Boycott , 36 and Heidi L. Rehm 1, 3, 4, 7. Cassie Doll 38 Google Inc. Find articles by Richard A. Find articles by Matthew E. Find articles by Ben Hutton. Find articles by Ganesh J. Author information Copyright and License information Disclaimer. The publisher's final edited version of this article is available at Hum Mutat.

Internet-driven patient-finding

See other articles in PMC that cite the published article. Introduction The content of genetic tests has gradually expanded over the years, with major leaps happening recently with the introduction of exome and genome sequencing. Open in a separate window. Building Blocks to Support the Matchmaker Exchange To promote responsible data sharing, the founding members of the MME have established a set of requirements for participating matchmaking services, a user agreement for those wishing to use the MME, and a steering committee SC to govern the program.

Require users to deposit case data to undertake a federated query across the MME service providers.

Contain content that is considered by the MME steering committee to be useful for matching, including the flagging of, or ability to prioritize, candidate genes. During user queries, enable dual notification of data requester i.

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For each database to which a MME service is connected by an API, the connected database's disclaimers should be posted on the MME service's website and displayed with query results. Disclaimers can be found on GitHub https: Store queries sent and received between MME sites only for the purpose of auditing, defining query statistics, and following up queries to understand rates of validated gene discovery. Advance the goals of the MME project through active participation in meetings and conference calls including defining a representative for the MME steering committee.

To make no attempt to identify individual patients in any MME database. To enable all cases submitted for querying to be stored in the query-initiating database for future matching. Due to a historically high reproductive rate among the relatively small number of individuals that comprise the community, rare mutations that might have been dormant in founder individuals begin to express themselves over time among their descendants, with dramatically increased frequency the longer the community remains endogamous.

Mutations, of themselves, are not uncommon in the general population. When an offspring inherits a copy of a recessive gene from only one parent, it could go through its entire life without displaying any symptoms of the disease. It is only when a child inherits a copy of the same mutation from both parents that the disease surfaces.

In communities with population bottlenecks, there is a significantly higher chance that both parents will carry the same recessive mutation. A number of inherited diseases have been identified to commonly exist in various Jewish communities such as the Ashkenazis. As abortion is generally unacceptable among orthodox Jews, prenatal screening is largely ineffective as a means to prevent affected foetuses from going to full term. Armed with information about their own genomic mutations, these schoolchildren were now equipped to determine, even before they started dating, whether the offspring they might have with the persons they intended to date are likely to be afflicted with one of these diseases.

As unromantic as this might sound, in communities with rigid religious and social norms, genetic matchmaking is perhaps the only way to avoid the proliferation of genetic diseases.

The Matchmaker Exchange: A Platform for Rare Disease Gene Discovery

India is home to more than 40, jatis as well as various other tribal groupings. Many of these groups follow, to this day, strict rules of endogamy that prevent them from, or at the least frown on, marrying anyone outside their group. We have only relatively recently begun to test these groups for genetic similarity.