The Matchmaker Exchange A Global Effort to Identify Novel Disease Genes. Ada Hamosh, MD, MPH Johns Hopkins University February 2017

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1 The Matchmaker Exchange A Global Effort to Identify Novel Disease Genes Ada Hamosh, MD, MPH Johns Hopkins University February 2017

2 Goal: To identify causal genes for rare disease by matching phenotypes and genotypes across a federated network of genomic databases. Patient #1 Clinical Geneticist #1 Patient #2 Clinical Geneticist #2 Notification of Match Phenotypic Data Feature 1 Feature 2 Feature 3 Feature 4 Feature 5 Genotypic Data Gene A Gene B Gene C Gene D Gene E Gene F Genomic Matchmaker Genotypic Data Gene D Gene G Gene H Phenotypic Data Feature 1 Feature 3 Feature 4 Feature 5 Feature 6 Courtesy of Joel Krier

3 Gene +/- Phenotype Diseases PEER Gene Matcher DECIPHER Gene and Phenotype (HPO) Disease and Variants Genome Connect LOVD Variants and VCFs Model Organisms Monarch Multiple disconnected Matchmaker Exchange solutions Variants and Phenotype Café Variome VCFs and Phenotype (HPO) RD Connect Gene Yenta Phenotype ASHG, Boston October 2013 Variant and Disease ClinGen Disease and VCFs GEM. app PhenomeCe ntral VCFs and Phenotype (HPO)

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5 API v1 Data Fields ID (Mandatory) - The internal identifier (obfuscated or not) that can be used by the originating system to reference the patient data. Label (Optional) - A name/identifier assigned by the user which can be used to reference the patient in a recognizable manner (in an for example); it should not contain any personally identifiable information. Query type (Optional) Accepted values: once or periodic Submitter (Mandatory) - Consists of contact information of the person that submitted the search Gender (Optional) Age of onset (Optional) Mode of inheritance (Optional) Disorders (Optional) - A list of OMIM (MIM:######) or OrphaNet (ORPHA#####) identifiers, can be empty Features It is mandatory to have at least clinical features or gene(s ); having both is preferred HPO terms for clinical features gene name(s)

6 February 2016 Connected MME Services

7 February 2017 Federated Network

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9 Instructions for individuals to use 1. Read and adhere to end users agreement 2. Determine if consent is needed 3. Pick the database that is appropriate for your data

10 MME End-Users Agreement

11 Consent Considerations Level 1: Gene Symbols / IDs, Disease Names, a few HPO IDs Level 2: DNA or protein sequence information, detailed phenotype Information

12 All matchmakers accept data from registered clinicians and researchers. GeneMatcher and MyGene2 accept submissions from patients for searching within their own databases, but do NOT yet exchange patient submitted data across the MME.

13 December 1, 2013 March 1, 2014 June 1, 2014 September 1, 2014 December 1, 2014 March 1, 2015 June 1, 2015 September 1, 2015 December 1, 2015 March 1, 2016 June 1, 2016 September 1, 2016 December 1, 2016 Number Gene Count Match Count Gene Match Count 0 GeneMatcher URL: Matches on Gene, condition OMIM number, Phenotypic features (HPO) 10,895 submissions from 2794 submitters in 63 countries 440 users have matches through MME 24 publications from within GeneMatcher: 2 from MME (PC) Growth 15,102 6,189 2,303

14 DECIPHER Over 22,600 cases 63,300 Phenotypic Annotations All data within the MME is consented for open searching Requests for collaboration go through curators Over 1000 publications on CNVs and SNVs from collaborators with DECIPHER

15 Partners: 3,040 patient records 893 users Growth 47,683 HPO annotations 695 exomes MME matches Service In Out Broad matchbox 6, DECIPHER GeneMatcher Monarch 0 61 MyGene MME API requests 28 match s received Recent publications TRIT1 (with GeneMatcher) submitted EXTL3 (with GeneMatcher) dx.doi.org/ / j.ajhg

16 MyGene2 URL: Designed for patients to share data, including VCF files Since patients upload, there is no IRB or consent required 1024 family profiles included Live since April 2016

17 matchbox Live since November 2016 >5000 cases (from the Broad SEQR database) 6 matches through MME, all being followed matchbox software is now open source and available for other databases to use

18 Australian Genomics Health Alliance MATCHMAKER EXCHANGE Platform developed by the Phenomics team at the Kinghorn Center of Clinical Genomics and managed out of the National Computational Infrastructure Launched mid-2016 and accessible to AGHA clinicians and researchers - 30 subscribers currently AGHA is recruiting patients with rare disease prospectively as they present to clinic and have genomic testing. As part of the research RD flagship, we expect to add ~500 patients per year which will increase as genomic testing becomes integrated into (and paid for) as part of clinical care All data will be accessible via the AGHA MME

19 The Monarch Initiative MME Monarch develops the Human Phenotype Ontology and algorithms to match against patients, known diseases, and model organisms to aid diagnosis

20 Matchmaker Exchange Connections

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22 Connecting a database to the MME Contact us: api@matchmakerexchange.org

23 Acknowledgements Harindra Arachchi Andrew Devereau Ekta Khurana Woong-Yan Park S Balasubramanian Johan den Dunnen Sebastian Kohler Justin Paschall Mike Bamshad Sergiu Dumitriu Joel Krier Anthony Philippakis Sergio Beltran Agullo Helen Firth Owen Lancaster Heidi Rehm Jonathan Berg Paul Flicek Melissa Landrum Peter Robinson Kym Boycott Jan Friedman Farrah Ladha Gary Saunders Anthony Brookes Richard Gibbs Paul Lasko Francois Schiettecatte Catherine Brownstein Marta Girdea Rick Lifton Rolf Sijmons Michael Brudno Robert Green Daniel MacArthur Nara Sobreira Han Brunner Tudor Groza Alex MacKenzie Jawahar Swaminathan Orion Buske Ada Hamosh Danielle Azzariti Morris Swertz Jessica X. Chong Melissa Haendel Aleksander Milosavljevic Peter Taschner Deanna Church Ingrid Holm Chris Mungall Sharon Terry Raymond Dalgliesh Matt Hurles Debbie Nickerson Rachel Thompson Victor de la Torre Ben Hutton Kathryn North Stephan Zuchner