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Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

ABSTRACT: Genetic variation can affect drug response in multiple ways, although 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 ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation-Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

SUBMITTER: Bush WS

PROVIDER: S-EPMC5010878 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

Bush W S WS Crosslin D R DR Owusu-Obeng A A Wallace J J Almoguera B B Basford M A MA Bielinski S J SJ Carrell D S DS Connolly J J JJ Crawford D D Doheny K F KF Gallego C J CJ Gordon A S AS Keating B B Kirby J J Kitchner T T Manzi S S Mejia A R AR Pan V V Perry C L CL Peterson J F JF Prows C A CA Ralston J J Scott S A SA Scrol A A Smith M M Stallings S C SC Veldhuizen T T Wolf W W Volpi S S Wiley K K Li R R Manolio T T Bottinger E E Brilliant M H MH Carey D D Chisholm R L RL Chute C G CG Haines J L JL Hakonarson H H Harley J B JB Holm I A IA Kullo I J IJ Jarvik G P GP Larson E B EB McCarty C A CA Williams M S MS Denny J C JC Rasmussen-Torvik L J LJ Roden D M DM Ritchie M D MD

Clinical pharmacology and therapeutics 20160601 2

Genetic variation can affect drug response in multiple ways, although 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 ∼5,000 clinical su ...[more]

PMID: 26857349

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Project description:BackgroundSystematic study of clinical phenotypes is important for a better understanding of the genetic basis of human diseases and more effective gene-based disease management. A key aspect in facilitating such studies requires standardized representation of the phenotype data using common data elements (CDEs) and controlled biomedical vocabularies. In this study, the authors analyzed how a limited subset of phenotypic data is amenable to common definition and standardized collection, as well as how their adoption in large-scale epidemiological and genome-wide studies can significantly facilitate cross-study analysis.MethodsThe authors mapped phenotype data dictionaries from five different eMERGE (Electronic Medical Records and Genomics) Network sites studying multiple diseases such as peripheral arterial disease and type 2 diabetes. For mapping, standardized terminological and metadata repository resources, such as the caDSR (Cancer Data Standards Registry and Repository) and SNOMED CT (Systematized Nomenclature of Medicine), were used. The mapping process comprised both lexical (via searching for relevant pre-coordinated concepts and data elements) and semantic (via post-coordination) techniques. Where feasible, new data elements were curated to enhance the coverage during mapping. A web-based application was also developed to uniformly represent and query the mapped data elements from different eMERGE studies.ResultsApproximately 60% of the target data elements (95 out of 157) could be mapped using simple lexical analysis techniques on pre-coordinated terms and concepts before any additional curation of terminology and metadata resources was initiated by eMERGE investigators. After curation of 54 new caDSR CDEs and nine new NCI thesaurus concepts and using post-coordination, the authors were able to map the remaining 40% of data elements to caDSR and SNOMED CT. A web-based tool was also implemented to assist in semi-automatic mapping of data elements.ConclusionThis study emphasizes the requirement for standardized representation of clinical research data using existing metadata and terminology resources and provides simple techniques and software for data element mapping using experiences from the eMERGE Network.

Dataset Information

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

Publications

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

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