The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Development of a Large-Scale De-Identified DNA Biobank to Enable Personalized Medicine
Open accessAbstract
Our objective was to develop a DNA biobank linked to phenotypic data derived from an electronic medical record (EMR) system. An "opt-out" model was implemented after significant review and revision. The plan included (i) development and maintenance of a de-identified mirror image of the EMR, namely, the "synthetic derivative" (SD) and (ii) DNA extracted from discarded blood samples and linked to the SD. Surveys of patients indicated general acceptance of the concept, with only a minority ( approximately 5%) opposing it. As a result, mechanisms to facilitate opt-out included publicity and revision of a standard "consent to treatment" form. Algorithms for sample handling and procedures for de-identification were developed and validated in order to ensure acceptable error rates (<0.3 and <0.1%, respectively). The rate of sample accrual is 700-900 samples/week. The advantages of this approach are the rate of sample acquisition and the diversity of phenotypes based on EMRs.
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Cites
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
A genome-wide association study identifies novel risk loci for type 2 diabetes
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Complement factor H variant increases the risk of age-related macular degeneration
Haines, J. L., Hauser, M. A., Schmidt, S., Scott, W. K., Olson, L. M., Gallins, P., Spencer, K. L., Kwan, S. Y., Noureddine, M., Gilbert, J. R., et al. (2005) · Science · doi:10.1126/science.1110359 · Cited by 2,424
Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes
Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., et al. (2007) · Science · doi:10.1126/science.1142364 · Cited by 2,194
A Common Allele on Chromosome 9 Associated with Coronary Heart Disease
McPherson, R., Pertsemlidis, A., Kavaslar, N., Stewart, A., Roberts, R., Cox, D. R., Hinds, D. A., Pennacchio, L. A., Tybjaerg-Hansen, A., Folsom, A. R., et al. (2007) · Science · doi:10.1126/science.1142447 · Cited by 1,587
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UK Biobank: From Concept to Reality
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Cited by
Mining electronic health records: towards better research applications and clinical care
Jensen, P. B., Jensen, L. J., & Brunak, S. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3208 · Cited by 1,680
PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations
Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., Wang, D., Masys, D. R., Roden, D. M., & Crawford, D. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq126 · Cited by 1,219
Self-citationOverview of the BioBank Japan Project: Study design and profile
Nagai, A., Hirata, M., Kamatani, Y., Muto, K., Matsuda, K., Kiyohara, Y., Ninomiya, T., Tamakoshi, A., Yamagata, Z., Mushiroda, T., et al. (2017) · Journal of Epidemiology · doi:10.1016/j.je.2016.12.005 · Cited by 739
the eMERGE Team, McCarty, C. A., Chisholm, R. L., Chute, C. G., Kullo, I. J., Jarvik, G. P., Larson, E. B., Li, R., Masys, D. R., Ritchie, M. D., et al. (2011) · BMC Medical Genomics · doi:10.1186/1755-8794-4-13 · Cited by 699
Self-citationChen, M.-H., Raffield, L. M., Mousas, A., Sakaue, S., Huffman, J. E., Moscati, A., Trivedi, B., Jiang, T., Akbari, P., Vuckovic, D., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.045 · Cited by 661
Metadata
- Authors
- Roden, D., Pulley, J., Basford, M., Bernard, G., Clayton, E., Balser, Jr., & Masys, D.
- Venue
- Clinical Pharmacology & Therapeutics
- Publisher
- Wiley
- Published
- 2008-05-21
- Volume
- 84
- Issue
- 3
- Pages
- 362-369
- ISSN
- 0009-9236 (ISSN-L)
- 1532-6535
- OpenAlex
- W2006776184
- Cited by
- 983
- References
- 8
- FWCI
- 26.97
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Development of a Large-Scale De-Identified DNA Biobank to Enable Personalized Medicine. https://app.cochat.ai/papers/10.1038/clpt.2008.89
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- Roden, D., Pulley, J., Basford, M., Bernard, G., Clayton, E., Balser, Jr., & Masys, D. (2008). Development of a Large-Scale De-Identified DNA Biobank to Enable Personalized Medicine. Clinical Pharmacology & Therapeutics. https://doi.org/10.1038/clpt.2008.89
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
