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This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward., (Published 2015. This article is a U.S. Government work and is in the public domain in the USA.)

We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1- to 3-year time frame across several clinical sites; (ii) to integrate well-established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to managing incidental findings, and patient and clinician education methods.

Efforts to define the genetic architecture underlying variable statin response have met with limited success, possibly because previous studies were limited to effect based on a single dose. We leveraged electronic medical records (EMRs) to extract potency (ED50) and efficacy (Emax) of statin dose-response curves and tested them for association with 144 preselected variants. Two large biobanks were used to construct dose-response curves for 2,026 and 2,252 subjects on simvastatin and atorvastatin, respectively. Atorvastatin was more efficacious, was more potent, and demonstrated less interindividual variability than simvastatin. A pharmacodynamic variant emerging from randomized trials (PRDM16) was associated with Emax for both. For atorvastatin, Emax was 51.7 mg/dl in subjects homozygous for the minor allele vs. 75.0 mg/dl for those homozygous for the major allele. We also identified several loci associated with ED50. The extraction of rigorously defined traits from EMRs for pharmacogenetic studies represents a promising approach to further understand the genetic factors contributing to drug response.