2017
An Empirical Study for Impacts of Measurement Errors on EHR based Association Studies.
Duan R, Cao M, Wu Y, Huang J, Denny J, Xu H, Chen Y. An Empirical Study for Impacts of Measurement Errors on EHR based Association Studies. AMIA Annual Symposium Proceedings 2017, 2016: 1764-1773. PMID: 28269935, PMCID: PMC5333313.Peer-Reviewed Original Research
2014
Genotype and risk of major bleeding during warfarin treatment
Kawai V, Cunningham A, Vear S, Van Driest S, Oginni A, Xu H, Jiang M, Li C, Denny J, Shaffer C, Bowton E, Gage B, Ray W, Roden D, Stein C. Genotype and risk of major bleeding during warfarin treatment. Pharmacogenomics 2014, 15: 1973-1983. PMID: 25521356, PMCID: PMC4304738, DOI: 10.2217/pgs.14.153.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedBiological Specimen BanksCytochrome P-450 CYP2C9Cytochrome P-450 Enzyme SystemCytochrome P450 Family 4Dose-Response Relationship, DrugEthnicityFemaleGene FrequencyGenetic Association StudiesGenetic VariationGenotypeHemorrhageHumansMaleMiddle AgedRisk FactorsVitamin K Epoxide ReductasesWarfarinPhenDisco: phenotype discovery system for the database of genotypes and phenotypes
Doan S, Lin K, Conway M, Ohno-Machado L, Hsieh A, Feupe S, Garland A, Ross M, Jiang X, Farzaneh S, Walker R, Alipanah N, Zhang J, Xu H, Kim H. PhenDisco: phenotype discovery system for the database of genotypes and phenotypes. Journal Of The American Medical Informatics Association 2014, 21: 31-36. PMID: 23989082, PMCID: PMC3912702, DOI: 10.1136/amiajnl-2013-001882.Peer-Reviewed Original ResearchConceptsNew information retrieval systemInformation retrieval systemsInformation retrieval toolsDatabase of GenotypesText processing toolsRetrieval systemSearch scenariosDiscovery systemRetrieval toolsAuthorized usersNon-standardized wayCross-study validationSearch comparisonProcessing toolsPromising performanceUsersPhenotype informationDatabaseInformationBiotechnology InformationQueriesMetadataEntrezResourcesSystem
2013
Characterization of Statin Dose Response in Electronic Medical Records
Wei W, Feng Q, Jiang L, Waitara M, Iwuchukwu O, Roden D, Jiang M, Xu H, Krauss R, Rotter J, Nickerson D, Davis R, Berg R, Peissig P, McCarty C, Wilke R, Denny J. Characterization of Statin Dose Response in Electronic Medical Records. Clinical Pharmacology & Therapeutics 2013, 95: 331-338. PMID: 24096969, PMCID: PMC3944214, DOI: 10.1038/clpt.2013.202.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAllelesAtorvastatinCholesterol, LDLCohort StudiesDatabases, FactualDose-Response Relationship, DrugElectronic Health RecordsGenotypeHeptanoic AcidsHumansHydroxymethylglutaryl-CoA Reductase InhibitorsHyperlipidemiasLipid MetabolismLipidsPhenotypePolymorphism, Single NucleotidePyrrolesRandomized Controlled Trials as TopicSimvastatin
2012
Optimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping
Schildcrout J, Denny J, Bowton E, Gregg W, Pulley J, Basford M, Cowan J, Xu H, Ramirez A, Crawford D, Ritchie M, Peterson J, Masys D, Wilke R, Roden D. Optimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping. Clinical Pharmacology & Therapeutics 2012, 92: 235-242. PMID: 22739144, PMCID: PMC3785311, DOI: 10.1038/clpt.2012.66.Peer-Reviewed Original ResearchConceptsVanderbilt University Medical CenterAdverse eventsPreemptive genotypingPotential adverse eventsUniversity Medical CenterHome patientsPharmacogenetic associationsMedical CenterVariant allelesMedicationsDrug outcomesPatient safetyDrug decision makingRelevant genetic variantsRoutine integrationTarget drugsGenetic variantsOutcomesFrequency of opportunitiesGenotypingSafetyPrescribingPatientsCohortPharmacogeneticsThe use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients
Birdwell K, Grady B, Choi L, Xu H, Bian A, Denny J, Jiang M, Vranic G, Basford M, Cowan J, Richardson D, Robinson M, Ikizler T, Ritchie M, Stein C, Haas D. The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients. Pharmacogenetics And Genomics 2012, 22: 32-42. PMID: 22108237, PMCID: PMC3237759, DOI: 10.1097/fpc.0b013e32834e1641.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1Body WeightCytochrome P-450 CYP3ADatabases, Nucleic AcidDose-Response Relationship, DrugDrug MonitoringElectronic Health RecordsFemaleGenetic Association StudiesGenotypeHemoglobinsHumansImmunosuppressive AgentsKidney TransplantationLinkage DisequilibriumMaleMiddle AgedPolymorphism, Single NucleotidePregnane X ReceptorReceptors, SteroidTacrolimusConceptsTacrolimus dose requirementsKidney transplant recipientsDose requirementsElectronic medical recordsBlood concentrationsTransplant recipientsMedical recordsCYP3A5 rs776746Electronic medical record dataInterindividual pharmacokinetic variabilityTacrolimus blood concentrationsNarrow therapeutic indexDNA biobanksMedical record dataTherapeutic drug monitoringDrug-metabolizing enzymesKidney transplantationClinical factorsPrimary outcomeImmunosuppressive drugsPharmacokinetic variabilityTacrolimus clearanceClinical covariatesPharmacogenomic predictorsTherapeutic index
2011
Predicting Clopidogrel Response Using DNA Samples Linked to an Electronic Health Record
Delaney J, Ramirez A, Bowton E, Pulley J, Basford M, Schildcrout J, Shi Y, Zink R, Oetjens M, Xu H, Cleator J, Jahangir E, Ritchie M, Masys D, Roden D, Crawford D, Denny J. Predicting Clopidogrel Response Using DNA Samples Linked to an Electronic Health Record. Clinical Pharmacology & Therapeutics 2011, 91: 257-263. PMID: 22190063, PMCID: PMC3621954, DOI: 10.1038/clpt.2011.221.Peer-Reviewed Original ResearchMeSH KeywordsAgedAryl Hydrocarbon HydroxylasesAryldialkylphosphataseATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1ClopidogrelCytochrome P-450 CYP2C19Databases, Nucleic AcidElectronic Health RecordsFemaleGenotypeHumansMaleMyocardial InfarctionPharmacogeneticsPlatelet Aggregation InhibitorsPolymorphism, GeneticStentsThrombosisTiclopidineTreatment OutcomeConceptsPercutaneous coronary interventionElectronic health recordsCardiac eventsMyocardial infarctionRecurrent cardiac eventsRecurrent cardiovascular eventsHealth recordsUse of EHRsClopidogrel therapyCardiovascular eventsClopidogrel treatmentClopidogrel resistanceClopidogrel responseCoronary interventionStent thrombosisReal-world settingCYP2C19ABCB1PON1Pharmacogenomic studiesRecurrent eventsTreatmentDNA repositoryDNA samplesInfarctionThe Emerging Role of Electronic Medical Records in Pharmacogenomics
Wilke R, Xu H, Denny J, Roden D, Krauss R, McCarty C, Davis R, Skaar T, Lamba J, Savova G. The Emerging Role of Electronic Medical Records in Pharmacogenomics. Clinical Pharmacology & Therapeutics 2011, 89: 379-386. PMID: 21248726, PMCID: PMC3204342, DOI: 10.1038/clpt.2010.260.Peer-Reviewed Original Research