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, 22 (2), 371-380

The Genomics Research and Innovation Network: Creating an Interoperable, Federated, Genomics Learning System

Collaborators, Affiliations

The Genomics Research and Innovation Network: Creating an Interoperable, Federated, Genomics Learning System

Kenneth D Mandl et al. Genet Med.

Erratum in

  • Correction: The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system.
    Mandl KD, Glauser T, Krantz ID, Avillach P, Bartels A, Beggs AH, Biswas S, Bourgeois FT, Corsmo J, Dauber A, Devkota B, Fleisher GR, Heath AP, Helbig I, Hirschhorn JN, Kilbourn J, Kong SW, Kornetsky S, Majzoub JA, Marsolo K, Martin LJ, Nix J, Schwarzhoff A, Stedman J, Strauss A, Sund KL, Taylor DM, White PS, Marsh E, Grimberg A, Hawkes C; Genomics Research and Innovation Network. Mandl KD, et al. Genet Med. 2020 Feb;22(2):449. doi: 10.1038/s41436-019-0711-y. Genet Med. 2020. PMID: 31772351 Free PMC article.


Purpose: Clinicians and researchers must contextualize a patient's genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care.

Methods: Three of the nation's leading children's hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model.

Results: Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype-phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications.

Conclusions: The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.

Keywords: biobanking; electronic health records; federated networks; genomic medicine; information technology.


Fig. 1
Fig. 1
Collaboration structure for the Genomics Research and Innovation Network.
Fig. 2
Fig. 2
The PIC-SURE application programming interface (API) is used to access genotype and phenotype data from databases at each site of care. Currently the databases are i2b2/TranSMART instances, but the API is agnostic. Authorized investigators from the three institutions can log in with their standard hospital credentials at the Genomics Research and Innovation Network (GRIN) Central Access Portal. Investigators can interrogate data all three hospitals using the discover portal, which returns aggregate counts by institution. With proper institutional review board (IRB) authorization, they can access line-level de-identified data for exploratory analyses using i2b2/TranSMART, or export line-level data to the analysis portal, an Amazon Web Services (AWS)–hosted environment shared across the three institutions.
Fig. 3
Fig. 3
The discovery user interface (UI) finding patients across the hospital with a diagnosis of epilepsy and recurrent seizures. The figure illustrates not only the power of distributed query, but also the nature of a modular, scalable federated network, in that the three hospitals are at different stages of data contribution. The Cincinnati Children’s Hospital Medical Center has made its full corpus of electronic health record (EHR) data available for query. The Children’s Hospital of Philadelphia and Boston Children’s Hospital have only made data available for consented biobank cohorts. Note—both of the latter hospitals are committed to making the full EHR cohort available during 2019.
Fig. 4
Fig. 4
The discovery user interface (UI) finding three patients with a specific variant at one of the hospitals. With proper approvals, samples, sequence, electronic health record data, or recontact can be requested by any investigator at the hospitals.

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