CC-CHOC Rare Disease Workgroup Goals

1. Childhood Rare Diseases and the Use of InformaticsCase study: Distributed Biobanks for Rare Diseases (DBRD)Jennifer Puck, MDUniversity of California San FranciscoCC-CHOC Meeting, Apr. 30, 2010

2. CC-CHOC Rare Disease Workgroup Goals • Originally child health oriented, now all ages. • Increase translational research in rare diseases at our home CTSA sites. • Build partnerships across CTSA sites because no single site has enough cases to make rapid progress alone. • Bring new investigators into rare disease research. • Develop new infrastructure to facilitate multi-site projects.

3. CC-CHOC Rare Disease Work Group • Rare diseases have been a CC-CHOC priority since the first meeting • outline pressing rare disease research issues • Identify opportunities • overcome hurdles using expertise and resources from across the CTSA Consortium as well as from federal and other entities. • Collaborative partners • NCRR, CTSA supplements • NIH Office of Rare Diseases • NIH Rare Disease Clinical Research Networks • FDA Office of Orphan Products Development • NHGRI, NBSTRN/ACMG • NORD, independent advocacy groups

4. Rare Disease Workgroup Action Plan • Challenges/Issues • Inadequate patient numbers at individual sites • Incompatible mechanisms for data collection, encoding, storage, access/sharing • Little coordinated information about rare disease specimen collections • Volunteers solicited to bring their own projects to address the issues • Severe combined immunodeficiency (SCID) • Down syndrome • Distributed Biobanks for Rare Diseases (DBRD)

5. Premise of Distributed Biobanks for Rare Diseases (DBRD) Rare diseases provide an ideal substrate for working out CTSA collaborative technology. Rare diseases can’t be studied effectively without collaborations between multiple institutions. [Pediatric researchers already have a culture of sharing] Rare disease researchers are motivated to develop CTSA infrastructure for collaborative research. Rare disease Use Cases can test CTSA technology for sharing samples and data on a small scale. Functionality required for rare disease research mirrors on a small scale what will be required for large cohort studies.

6. DBRD Activities Assemble Rare Disease Use Cases Severe combined immunodeficiency (SCID): how is genotype (disease gene and specific mutation type) related to outcome following bone marrow transplant? Jennifer Puck, UCSF Luigi Notarangelo, Harvard Mort Cowan, Primary Immune Deficiency Treatment Consortium (Rare Disease Consortium Research Network) Kate Sullivan, CHOP, US Immunodeficiency Network (Immune Deficiency Foundation, NIAID) Down syndrome: what genetic factors influence severity of cognitive impairment? Priya Kishnani, Duke Stephanie Sherman, Emory Cheryl Maslen, OHSU Scientific questions determine what data and samples are collected

7. DBRD Activities, continued Governance Biobank best practices, SOPs for sample handling and tracking. Prohibitive cost of central sample collection dictated local (or regionalized) storage. Samples from patients with rare diseases are irreplaceable, need to be salvaged even if not collected by ideal guidelines Prospective standardization essential Legal, ownership issues Physician investigators have a large investment in their sample and data collections and insist on some control over their use Human subjects issues (archived and prospective collections) Keeping samples at their original site could be an acceptable way to make them available on a collaborative basis.

8. DBRD Activities, continued Informatics (R. Wynden et al., The integrated data repository: ontology mapping and data discovery for the translational investigator. J Biol Informatics 2010) Extract sample tracking data and sample associated clinical data from local databases. Transform data into standard formats in a secure database that substitutes codes for subject identifiers. Extract a de-identified data summary for each available sample to constitute a sample index at each site. Make the sample index available to be queried by pre-qualified viewers over a secure informatics grid. Implement a 2-step process for rare disease researchers Initial de-identified query to find potential appropriate samples Collaboration established between sample holders and investigators

9. Stored Specimen Data Clinical Data lexEVS caDSR ctsDSR HL7 OID Registry i2b2 ISO 111-79 View Ontology Mapper Mapping Workbench Ontology Mapper Cell i2b2 based queries with SHRINE Instance Map Folder UCSF SHRINE, CaGrid Network bewteen CTSAs Additional Sites: DMCC, USIDNET, CIBMTR Harvard Childrens Boston Cincinnati Children’s U. Penn CHOP DBRD Informatics, SCID Project

10. Remaining Challenges Ethics and research regulation policies vary between institutions. Two IRBs came to different conclusions about the need to re-consent subjects with Down syndrome in order to have their samples used in multisite studies. HIPAA and institutional protections require security for inter-site electronic grid queries, but mechanisms to review and monitor access are not yet established at CTSA sites. Scaling up to accommodate users at many CTSA sites will require a generalized protocol.

11. Governance IRB: Lainie Friedman Ross, U Chicago; Jeff Botkin, U Utah Ownership, Trust Fabric: Ellen Wright Clayton, Vanderbilt Repository best practices, SOPs: Elisa Eiseman, Rand Corporation Investigator perspectives: Nancy Green, Columbia; Bonnie Ramsey, U Washington Use Cases SCID: Jennifer Puck & Mort Cowan, UCSF; Luigi Notarangelo, Harvard; Kathleen Sullivan, CHOP; Lisa Filipovich, Cincinnati; USIDNET, CIBMTR, PIDTC networks Down syndrome: Stephanie Sherman, Emory; Priya Kishnani, Duke; Cheryl Maslen, OHSU Informatics Rob Wynden, UCSF; others at each of the participating CTSA sites Thanks to Collaborators