June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
NEI eyeGENE® clinical research data accessibility through a Biomedical Research Informatics Computing System
Author Affiliations & Notes
  • Santa J Tumminia
    Office of the Director, National Eye Inst/NIH, Bethesda, Maryland, United States
  • Yvonne O Akporji
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Chelsea Bender
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Jemma Iano-Fletcher
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Andrew Hughes
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Matthew McAuliffe
    Dept. of Computational Biology, Center for Information Technology/NIH, Bethesda, Maryland, United States
  • Leonie Misquitta
    Dept. of Computational Biology, Center for Information Technology/NIH, Bethesda, Maryland, United States
  • Rebecca S Parrish
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Melissa J Reeves
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Kerry E Goetz
    Ophthalmic Genetics Visual Function Branch, National Eye Institute/NIH, Bethesda, Maryland, United States
  • Footnotes
    Commercial Relationships   Santa Tumminia, None; Yvonne Akporji, None; Chelsea Bender, None; Jemma Iano-Fletcher, None; Andrew Hughes, None; Matthew McAuliffe, None; Leonie Misquitta, None; Rebecca Parrish, None; Melissa Reeves, None; Kerry Goetz, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 585. doi:
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    • Get Citation

      Santa J Tumminia, Yvonne O Akporji, Chelsea Bender, Jemma Iano-Fletcher, Andrew Hughes, Matthew McAuliffe, Leonie Misquitta, Rebecca S Parrish, Melissa J Reeves, Kerry E Goetz; NEI eyeGENE® clinical research data accessibility through a Biomedical Research Informatics Computing System. Invest. Ophthalmol. Vis. Sci. 2017;58(8):585.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : As advances in data technology and data sharing requirements continue to feature in scientific efforts, the combined analysis of disparate data is a challenge to be addressed. eyeGENE®, a National Eye Institute(NEI) genomic research initiative created in response to growing therapeutic opportunities, has taken advantage of the Biomedical Research Informatics and Computing System (BRICS), a bioinformatics platform that allows users to store and query large amounts of data in a relational manner.

Methods : BRICS forms the foundation for a number of biomedical informatics platforms and data repositories within the NIH, extramural research communities, and the Department of Defense. It provides web-based functionality and downloadable tools to support data definition, data access and contribution for continuous research use. eyeGENE® developed forms for use in the system: Demographics, Genetics, Imaging, Legacy Clinical, and LOINC® Clinical. Data collected in the eyeGENE® legacy data capture system was exported into csv files corresponding to the appropriate form. Data was validated using the BRICS submission tool before being available for query.

Results : 475 Unique Data Elements were created to standardize eyeGENE® data collected from 2006-2015. The first data sets available were the demographics and genetics data containing 43,283 rows of data. Over 11,000 genes were tested in the program. Genetics data includes pathogenic mutations and variants of unknown significance. Imaging data, including 18,825 supplemental files, and clinical data will soon be available. The legacy data is also mapped to LOINC® standards to allow for cross-analysis. Research results are being collected in the BRICS Meta Study feature, which serves as a Data Commons.

Conclusions : Biomedical “Big Data” is diverse and complex, and drawing conclusions from large amounts of clinical research data relies heavily on being able to access, compare and query across these data sets. Using BRICS, we provide vision community access to data and tools for analysis of eyeGENE® clinical and genetic data. Summary level genetics results are also freely available to the public (https://eyegene.nih.gov/). LOINC® nomenclature (http://loinc.org) allows for data and information comparison across studies. Over time, it is expected that these efforts will maximize the value of the eyeGENE® data, leading to continued research discoveries.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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