A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers.

Defining the full spectrum of human disease associated with a biomarker is necessary to advance the biomarker into clinical practice. We hypothesize that associating biomarker measurements with electronic health record (EHR) populations based on shared genetic architectures would establish the clinical epidemiology of the biomarker. We use Bayesian sparse linear mixed modeling to calculate SNP weightings for 53 biomarkers from the Atherosclerosis Risk in Communities study. We use the SNP weightings to computed predicted biomarker values in an EHR population and test associations with 1139 diagnoses. Here we report 116 associations meeting a Bonferroni level of significance. A false discovery rate (FDR)-based significance threshold reveals more known and undescribed associations across a broad range of biomarkers, including biometric measures, plasma proteins and metabolites, functional assays, and behaviors. We confirm an inverse association between LDL-cholesterol level and septicemia risk in an independent epidemiological cohort. This approach efficiently discovers biomarker-disease associations.

Multidisciplinary model to implement pharmacogenomics at the point of care.

PURPOSE: Despite potential clinical benefits, implementation of pharmacogenomics (PGx) faces many technical and clinical challenges. These challenges can be overcome with a comprehensive and systematic implementation model. METHODS: The development and implementation of PGx were organized into eight interdependent components addressing resources, governance, clinical practice, education, testing, knowledge translation, clinical decision support (CDS), and maintenance. Several aspects of implementation were assessed, including adherence to the model, production of PGx-CDS interventions, and access to educational resources. RESULTS: Between August 2012 and June 2015, 21 specific drug-gene interactions were reviewed and 18 of them were implemented in the electronic medical record as PGx-CDS interventions. There was complete adherence to the model with variable production time (98-392 days) and delay time (0-148 days). The implementation impacted approximately 1,247 unique providers and 3,788 unique patients. A total of 11 educational resources complementary to the drug-gene interactions and 5 modules specific for pharmacists were developed and implemented. CONCLUSION: A comprehensive operational model can support PGx implementation in routine prescribing. Institutions can use this model as a roadmap to support similar efforts. However, we also identified challenges that will require major multidisciplinary and multi-institutional efforts to make PGx a universal reality.Genet Med 19 4, 421-429.