The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
The Geisinger MyCode community health initiative: an electronic health record–linked biobank for precision medicine research
Open accessAbstract
PURPOSE: Geisinger Health System (GHS) provides an ideal platform for Precision Medicine. Key elements are the integrated health system, stable patient population, and electronic health record (EHR) infrastructure. In 2007, Geisinger launched MyCode, a system-wide biobanking program to link samples and EHR data for broad research use. METHODS: Patient-centered input into MyCode was obtained using participant focus groups. Participation in MyCode is based on opt-in informed consent and allows recontact, which facilitates collection of data not in the EHR and, since 2013, the return of clinically actionable results to participants. MyCode leverages Geisinger's technology and clinical infrastructure for participant tracking and sample collection. RESULTS: MyCode has a consent rate of >85%, with more than 90,000 participants currently and with ongoing enrollment of ~4,000 per month. MyCode samples have been used to generate molecular data, including high-density genotype and exome sequence data. Genotype and EHR-derived phenotype data replicate previously reported genetic associations. CONCLUSION: The MyCode project has created resources that enable a new model for translational research that is faster, more flexible, and more cost-effective than traditional clinical research approaches. The new model is scalable and will increase in value as these resources grow and are adopted across multiple research platforms.Genet Med 18 9, 906-913.
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Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728
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
Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities
Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,601
Lippa, N. C., & Sanderson, S. C. (2013) · Human Heredity · doi:10.1159/000353712 · Cited by 6,078
A New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202
Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., Perry, J. R. B., Elliott, K. S., Lango, H., Rayner, N. W., et al. (2007) · Science · doi:10.1126/science.1141634 · Cited by 4,531
Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes
Grant, S. F. A., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Manolescu, A., Sainz, J., Helgason, A., Stefansson, H., Emilsson, V., Helgadottir, A., et al. (2006) · Nature Genetics · doi:10.1038/ng1732 · Cited by 2,287
Genomewide Association Analysis of Coronary Artery Disease
Samani, N. J., Erdmann, J., Hall, A. S., Hengstenberg, C., Mangino, M., Mayer, B., Dixon, R. J., Meitinger, T., Braund, P., Wichmann, H.-E., et al. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa072366 · Cited by 2,044
A Common Variant on Chromosome 9p21 Affects the Risk of Myocardial Infarction
Helgadottir, A., Thorleifsson, G., Manolescu, A., Gretarsdottir, S., Blondal, T., Jonasdottir, A., Jonasdottir, A., Sigurdsson, A., Baker, A., Palsson, A., et al. (2007) · Science · doi:10.1126/science.1142842 · Cited by 1,594
Common variants near MC4R are associated with fat mass, weight and risk of obesity
The Prostate, L., Loos, R. J. F., KORA, Study, N. H., Initiative, D. G., Study, T. S., The Wellcome Trust Case Control Consortium, FUSION, Lindgren, C. M., Li, S., et al. (2008) · Nature Genetics · doi:10.1038/ng.140 · Cited by 1,325
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Self-citation
Metadata
- Authors
- Carey, D. J., Fetterolf, S. N., Davis, F. D., Faucett, W. A., Kirchner, H. L., Mirshahi, U., Murray, M. F., Smelser, D. T., Gerhard, G. S., & Ledbetter, D. H.
- Venue
- Genetics in Medicine
- Publisher
- Elsevier BV
- Published
- 2016-09
- Volume
- 18
- Issue
- 9
- Pages
- 906-913
- ISSN
- 1098-3600 (ISSN-L)
- OpenAlex
- W2443172870
- Cited by
- 462
- References
- 30
- FWCI
- 35.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
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