The Biobank Portal for Partners Personalized Medicine: A Query Tool for Working with Consented Biobank Samples, Genotypes, and Phenotypes Using i2b2

Vivian S Gainer, Andrew Cagan, Victor M Castro, Stacey Duey, Bhaswati Ghosh, Alyssa P Goodson, Sergey Goryachev, Reeta Metta, Taowei David Wang, Nich Wattanasin, Shawn N Murphy, Vivian S Gainer, Andrew Cagan, Victor M Castro, Stacey Duey, Bhaswati Ghosh, Alyssa P Goodson, Sergey Goryachev, Reeta Metta, Taowei David Wang, Nich Wattanasin, Shawn N Murphy

Abstract

We have designed a Biobank Portal that lets researchers request Biobank samples and genotypic data, query associated electronic health records, and design and download datasets containing de-identified attributes about consented Biobank subjects. This do-it-yourself functionality puts a wide variety and volume of data at the fingertips of investigators, allowing them to create custom datasets for their clinical and genomic research from complex phenotypic data and quickly obtain corresponding samples and genomic data. The Biobank Portal is built upon the i2b2 infrastructure [1] and uses an open-source web client that is available to faculty members and other investigators behind an institutional firewall. Built-in privacy measures [2] ensure that the data in the Portal are utilized only according to the processes to which the patients have given consent.

Keywords: Biobank IT; Biobank information technology; Biobank software; personalized medicine IT; phenotype; precision medicine IT.

Figures

Figure 1
Figure 1
The Biobank Portal.
Figure 2
Figure 2
Linking EHR and Biobank data for precision medicine research.
Figure 3
Figure 3
High-throughput phenotyping.
Figure 4
Figure 4
The Biobank Portal with expanded ontology folders.

References

    1. Murphy S.N., Weber G., Mendis M., Gainer V., Chueh H.C., Churchill S., Kohane I. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) J. Am. Med. Inform. Assoc. 2010;17:124–130. doi: 10.1136/jamia.2009.000893.
    1. Murphy S.N., Gainer V., Mendis M., Churchill S., Kohane I. Strategies for maintaining patient privacy in i2b2. J. Am. Med. Inform. Assoc. 2011;18(Suppl. S1):i103–i108. doi: 10.1136/amiajnl-2011-000316.
    1. Ness R.B. Influence of the HIPAA privacy rule on health research. JAMA. 2007;298:2164–2170. doi: 10.1001/jama.298.18.2164.
    1. Murphy S.N., Mendis M., Hackett K., Kuttan R., Pan W., Phillips L.C., Gainer V., Berkowicz D., Glaser J.P., Kohane I., et al. Architecture of the open-source clinical research chart from informatics for integrating biology and the bedside. AMIA Annu. Symp. Proc. 2007;2007:548–552.
    1. Kohane I.S., Churchill S.E., Murphy S.N. A translational engine at the national scale: Informatics for integrating biology and the bedside. J. Am. Med. Inform. Assoc. 2011;19:181–185. doi: 10.1136/amiajnl-2011-000492.
    1. Murphy S.N., Gainer V., Chueh H.C. A visual interface designed for novice users to find research patient cohorts in a large biomedical database. AMIA Annu. Symp. Proc. 2003;2003:489–493.
    1. Sinnott J.A., Dai W., Liao K.P., Shaw S.Y., Ananthakrishnan A.N., Gainer V.S., Karlson E.W., Churchill S., Szolovits P., Murphy S., et al. Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records. Hum. Genet. 2014;133:1369–1382. doi: 10.1007/s00439-014-1466-9.
    1. Goldstein L.B. Accuracy of ICD-9-CM coding for the identification of patients with acute ischemic stroke: Effect of modifier codes. Stroke. 1998;29:1602–1604. doi: 10.1161/01.STR.29.8.1602.
    1. Arts D.G., De Keizer N.F., Scheffer G.J. Defining and improving data quality in medical registries: A literature review, case study, and generic framework. J. Am. Med. Inform. Assoc. 2002;9:600–611. doi: 10.1197/jamia.M1087.
    1. Singh J.A., Holmgren A.R., Noorbaloochi S. Accuracy of veterans administration databases for a diagnosis of rheumatoid arthritis. Arthritis Rheum. 2004;51:952–957. doi: 10.1002/art.20827.
    1. Liao K.P., Cai T., Gainer V., Goryachev S., Zeng-treitler Q., Raychaudhuri S., Szolovits P., Churchill S., Murphy S., Kohane I., et al. Electronic medical records for discovery research in rheumatoid arthritis. Arthritis Care Res. 2010;62:1120–1127. doi: 10.1002/acr.20184.
    1. Liao K.P., Cai T., Savova G.K., Murphy S.N., Karlson E.W., Ananthakrishnan A.N., Gainer V.S., Shaw S.Y., Xia Z., Szolovits P., et al. Development of phenotype algorithms using electronic medical records and incorporating natural language processing. BMJ. 2015;350:h1885. doi: 10.1136/bmj.h1885.
    1. Zou H. The adaptive Lasso and its oracle properties. J. Am. Stat. Assoc. 2006;101:1418–1429. doi: 10.1198/016214506000000735.
    1. Newton K.M., Peissig P.L., Kho A.N., Bielinski S.J., Berg R.L., Choudhary V., Basford M., Chute C.G., Kullo I.J., Li R., et al. Validation of electronic medical record-basedpheontyping algorithms: results and lessons learned from the eMERGE network. J. Am. Med. Inform. Assoc. 2013;20:147–154. doi: 10.1136/amiajnl-2012-000896.
    1. Yu S., Liao K.P., Shaw S.Y., Gainer V.S., Churchill S.E., Szolovits P., Murphy S.N., Kohane I.S., Cai T. Toward high-throughput phenotyping: Unbiased automated feature extraction and selection from knowledge sources. J. Am. Med. Inform. Assoc. 2015;22:993–1000. doi: 10.1093/jamia/ocv034.
    1. Carroll R.J., Thompson W.K., Eyler A.E., Mandelin A.M., Cai T., Zink R.M., Pacheco J.A., Boomershine C.S., Lasko T.A., Xu H., et al. Portability of an algorithm to identify rheumatoid arthritis in electronic health records. J. Am. Med. Inform. Assoc. 2012;19:162–169. doi: 10.1136/amiajnl-2011-000583.
    1. Olson J.E., Ryu E., Johnson K.J., Koenig B.A., Maschke K.J., Morrisette J.A., Liebow M., Takahashi P.Y., Fredericksen Z.S., Sharma R.G., et al. The Mayo Clinic Biobank: A building block for individualized medicine. Mayo Clin. Proc. 2013;88:952–962. doi: 10.1016/j.mayocp.2013.06.006.
    1. Ollier W., Sprosen T., Peakman T. UK Biobank: from concept to reality. Pharmacogenomics. 2005;6:639–646. doi: 10.2217/14622416.6.6.639.
    1. Roden D.M., Pulley J.M., Basford M.A., Bernard G.R., Clayton E.W., Balser J.R., Masys D.R. Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clin. Pharmacol. Ther. 2008;3:362–369. doi: 10.1038/clpt.2008.89.
    1. Charlson M.E., Pompei P., Ales K., MacKenzie C.R. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J. Chronic Dis. 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8.
    1. Charlson M.E., Szatrowski T.P., Peterson J., Gold J. Validation of a combined comorbidity index. J. Clin. Epidemiol. 1994;47:1245–1251. doi: 10.1016/0895-4356(94)90129-5.
    1. Deyo R.A., Cherkin D.C., Ciol M.A. Adapting a clinical comorbidity index for use with ICD-9-CM administrative diseases. J. Clin. Epidemiol. 1992;45:613–619. doi: 10.1016/0895-4356(92)90133-8.

Source: PubMed

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