The convergence of two rapidly developing technologies - high-throughput genotyping and electronic health records (EHRs) - gives scientists an unprecedented opportunity to utilize routine healthcare data to accelerate genomic discovery. Institutions and healthcare systems have been building EHR-linked DNA biobanks to enable such a vision. However, the precise extraction of detailed disease and drug-response phenotype information hidden in EHRs is not an easy task. EHR-based studies have successfully replicated known associations, made new discoveries for diseases and drug response traits, rapidly contributed cases and controls to large meta-analyses, and demonstrated the potential of EHRs for broad-based phenome-wide association studies. In this review, we summarize the advantages and challenges of repurposing EHR data for genetic research. We also highlight recent notable studies and novel approaches to provide an overview of advanced EHR-based phenotyping.
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The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients
Impact of data fragmentation across healthcare centers on the accuracy of a high-throughput clinical phenotyping algorithm for specifying subjects with type 2 diabetes mellitus
Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record
Operational implementation of prospective genotyping for personalized medicine: the design of the Vanderbilt PREDICT project
The absence of longitudinal data limits the accuracy of high-throughput clinical phenotyping for identifying type 2 diabetes mellitus subjects
A clinician-driven automated system for integration of pharmacogenetic interpretations into an electronic medical record
Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network
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Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network
A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry
Caveats for the use of operational electronic health record data in comparative effectiveness research
Identification of acute myocardial infarction from electronic healthcare records using different disease coding systems: a validation study in three European countries
A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources
A collaborative approach to developing an electronic health record phenotyping algorithm for drug-induced liver injury
A genome- and phenome-wide association study to identify genetic variants influencing platelet count and volume and their pleiotropic effects
Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data
Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface
Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems
Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index
Evaluation of matched control algorithms in EHR-based phenotyping studies: a case study of inflammatory bowel disease comorbidities
Assessing the role of a medication-indication resource in the treatment relation extraction from clinical text
Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins
Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis
A genome-wide association study of heparin-induced thrombocytopenia using an electronic medical record
Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance
Text mining for precision medicine: automating disease-mutation relationship extraction from biomedical literature
Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals
Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record
Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach
Genome-wide and Phenome-wide Approaches to Understand Variable Drug Actions in Electronic Health Records
Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution
Association Between Low-Density Lipoprotein Cholesterol Levels and Risk for Sepsis Among Patients Admitted to the Hospital With Infection
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Comparative Study of Percutaneous Sacroiliac Screw with or without TiRobot Assistance for Treating Pelvic Posterior Ring Fractures
Phenome-wide association study of TTR and RBP4 genes in 361,194 individuals reveals novel insights in the genetics of hereditary and wildtype transthyretin amyloidoses
Combining clinical and candidate gene data into a risk score for azathioprine-associated leukopenia in routine clinical practice
GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network
Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction
TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records
A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments
Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation
Heterogeneity introduced by EHR system implementation in a de-identified data resource from 100 non-affiliated organizations
Optimizing Antihypertensive Medication Classification in Electronic Health Record-Based Data: Classification System Development and Methodological Comparison
Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care
PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records
Optimizing identification of resistant hypertension: Computable phenotype development and validation
Development of an Algorithm to Identify Cases of Nonalcoholic Steatohepatitis Cirrhosis in the Electronic Health Record
LabWAS: Novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks
Making work visible for electronic phenotype implementation: Lessons learned from the eMERGE network
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