Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease. The New England journal of medicine. 2016 Mar 24;374(374). 1134-44. PMID: 26934567 [PubMed]
Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC).
Hoffman JM, Dunnenberger HM, Kevin Hicks J, Caudle KE, Whirl Carrillo M, Freimuth RR, Williams MS, Klein TE, Peterson JF. Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Journal of the American Medical Informatics Association : JAMIA. 2016 Mar 28. PMID: 27026620 [PubMed]
Bush WS, Crosslin DR, Obeng AO, Wallace J, Almoguera B, Basford MA, Bielinski SJ, Carrell DS, Connolly JJ, Crawford D, Doheny KF, Gallego CJ, Gordon AS, Keating B, Kirby J, Kitchner T, Manzi S, Mejia AR, Pan V, Perry CL, Peterson JF, Prows CA, Ralston J, Scott SA, Scrol A, Smith M, Stallings SC, Veldhuizen T, Wolf W, Volpi S, Wiley K, Li R, Manolio T, Bottinger E, Brilliant MH, Carey D, Chisholm RL, Chute CG, Haines JL, Hakonarson H, Harley JB, Holm IA, Kullo IJ, Jarvik GP, Larson EB, McCarty CA, Williams MS, Denny JC, Rasmussen-Torvik LJ, Roden DM, Ritchie MD. Genetic Variation among 82 Pharmacogenes: the PGRN-Seq data from the eMERGE Network. Clinical pharmacology and therapeutics. 2016 Feb 9. PMID: 26857349 [PubMed]
Genetic variation can affect drug response in multiple ways, though it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE-PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of "precision medicine." The February 2015 eMERGE-PGx data release includes sequence-derived data from ∼5000 clinical subjects.
Feng Q, Wei WQ, Chung CP, Levinson RT, Bastarache L, Denny JC, Stein CM. The effect of genetic variation in PCSK9 on the LDL-cholesterol response to statin therapy. The pharmacogenomics journal. 2016 Feb 23. PMID: 26902539 [PubMed]
Statins (HMG-CoA reductase inhibitors) lower low-density lipoprotein cholesterol (LDL-C) and prevent cardiovascular disease. However, there is wide individual variation in LDL-C response. Drugs targeting proprotein convertase subtilin/kexin type 9 (PCSK9) lower LDL-C and will be used with statins. PCSK9 mediates the degradation of LDL receptors (LDLRs). Therefore, a greater LDL-C response to statins would be expected in individuals with PCSK9 loss-of-function (LOF) variants because LDLR degradation is reduced.
A prognostic model based on readily available clinical data enriched a preemptive pharmacogenetic testing program.
Schildcrout JS, Shi Y, Danciu I, Bowton E, Field JR, Pulley JM, Basford M, Gregg W, Cowan J, Harrell FE, Roden DM, Peterson JF, Denny JC. A prognostic model based on readily available clinical data enriched a preemptive pharmacogenetic testing program. Journal of clinical epidemiology. 2015 Nov 25. PMID: 26628336 [PubMed]
Roden DM, Denny JC. Integrating electronic health record genotype and phenotype datasets to transform patient care. Clinical pharmacology and therapeutics. 2015 Dec 14. PMID: 26667791 [PubMed]
The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 mandates the development and implementation of electronic health record (EHR) systems across the country.
Wilke RA, Xu H, Denny JC, Roden DM, Krauss RM, McCarty CA, Davis RL, Skaar T, Lamba J, Savova G. The emerging role of electronic medical records in pharmacogenomics. Clinical pharmacology and therapeutics. 2011 Mar;89(89). 379-86. PMID: 21248726 [PubMed] PMCID: PMC3204342 NIHMSID: NIHMS327277.
Health-care information technology and genotyping technology are both advancing rapidly, creating new opportunities for medical and scientific discovery. The convergence of these two technologies is now facilitating genetic association studies of unprecedented size within the context of routine clinical care. As a result, the medical community will soon be presented with a number of novel opportunities to bring functional genomics to the bedside in the area of pharmacotherapy.
Facilitating pharmacogenetic studies using electronic health records and natural-language processing: a case study of warfarin.
Xu H, Jiang M, Oetjens M, Bowton EA, Ramirez AH, Jeff JM, Basford MA, Pulley JM, Cowan JD, Wang X, Ritchie MD, Masys DR, Roden DM, Crawford DC, Denny JC. Facilitating pharmacogenetic studies using electronic health records and natural-language processing: a case study of warfarin. Journal of the American Medical Informatics Association : JAMIA. 18(18). 387-91. PMID: 21672908 [PubMed] PMCID: PMC3128409
DNA biobanks linked to comprehensive electronic health records systems are potentially powerful resources for pharmacogenetic studies. This study sought to develop natural-language-processing algorithms to extract drug-dose information from clinical text, and to assess the capabilities of such tools to automate the data-extraction process for pharmacogenetic studies.
Delaney JT, Ramirez AH, Bowton E, Pulley JM, Basford MA, Schildcrout JS, Shi Y, Zink R, Oetjens M, Xu H, Cleator JH, Jahangir E, Ritchie MD, Masys DR, Roden DM, Crawford DC, Denny JC. Predicting clopidogrel response using DNA samples linked to an electronic health record. Clinical pharmacology and therapeutics. 2012 Feb;91(91). 257-63. PMID: 22190063 [PubMed] PMCID: PMC3621954 NIHMSID: NIHMS346495.
Variants in ABCB1 and CYP2C19 have been identified as predictors of cardiac events during clopidogrel therapy initiated after myocardial infarction (MI) or percutaneous coronary intervention (PCI). In addition, PON1 has recently been associated with stent thrombosis. The reported effects of these variants have not yet been replicated in a real-world setting.
Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record.
Ramirez AH, Shi Y, Schildcrout JS, Delaney JT, Xu H, Oetjens MT, Zuvich RL, Basford MA, Bowton E, Jiang M, Speltz P, Zink R, Cowan J, Pulley JM, Ritchie MD, Masys DR, Roden DM, Crawford DC, Denny JC. Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record. Pharmacogenomics. 2012 Mar;13(13). 407-18. PMID: 22329724 [PubMed] PMCID: PMC3361510 NIHMSID: NIHMS364371.
Warfarin pharmacogenomic algorithms reduce dosing error, but perform poorly in non-European-Americans. Electronic health record (EHR) systems linked to biobanks may allow for pharmacogenomic analysis, but they have not yet been used for this purpose.