Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record
- PMID: 20362271
- PMCID: PMC2850440
- DOI: 10.1016/j.ajhg.2010.03.003
Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record
Erratum in
- Am J Hum Genet. 2010 Aug 13;87(2):310
Abstract
Large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations. However, the extent to which such resources are capable of delivering on this promise is unknown. We studied whether an EMR-linked DNA biorepository can be used to detect known genotype-phenotype associations for five diseases. Twenty-one SNPs previously implicated as common variants predisposing to atrial fibrillation, Crohn disease, multiple sclerosis, rheumatoid arthritis, or type 2 diabetes were successfully genotyped in 9483 samples accrued over 4 mo into BioVU, the Vanderbilt University Medical Center DNA biobank. Previously reported odds ratios (OR(PR)) ranged from 1.14 to 2.36. For each phenotype, natural language processing techniques and billing-code queries were used to identify cases (n = 70-698) and controls (n = 808-3818) from deidentified health records. Each of the 21 tests of association yielded point estimates in the expected direction. Previous genotype-phenotype associations were replicated (p < 0.05) in 8/14 cases when the OR(PR) was > 1.25, and in 0/7 with lower OR(PR). Statistically significant associations were detected in all analyses that were adequately powered. In each of the five diseases studied, at least one previously reported association was replicated. These data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and they support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research cohorts and for discovery in genome science.
(c) 2010 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Figures


References
-
- Stead W.W. Rethinking electronic health records to better achieve quality and safety goals. Annu. Rev. Med. 2007;58:35–47. - PubMed
-
- Mahoney C.D., Berard-Collins C.M., Coleman R., Amaral J.F., Cotter C.M. Effects of an integrated clinical information system on medication safety in a multi-hospital setting. Am. J. Health Syst. Pharm. 2007;64:1969–1977. - PubMed
-
- Walsh K.E., Landrigan C.P., Adams W.G., Vinci R.J., Chessare J.B., Cooper M.R., Hebert P.M., Schainker E.G., McLaughlin T.J., Bauchner H. Effect of computer order entry on prevention of serious medication errors in hospitalized children. Pediatrics. 2008;121:e421–e427. - PubMed
-
- Galanter W.L., Hier D.B., Jao C., Sarne D. Computerized physician order entry of medications and clinical decision support can improve problem list documentation compliance. Int. J. Med. Inform. 2008 Published online July 1, 2008. - PubMed
-
- Kazley A.S., Ozcan Y.A. Do hospitals with electronic medical records (EMRs) provide higher quality care?: an examination of three clinical conditions. Med. Care Res. Rev. 2008;65:496–513. - PubMed
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Research Materials