Literature DB >> 27147087

Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.

Joshua C Denny1,2, Lisa Bastarache1, Dan M Roden1,2,3.   

Abstract

Beginning in the early 2000s, the accumulation of biospecimens linked to electronic health records (EHRs) made possible genome-phenome studies (i.e., comparative analyses of genetic variants and phenotypes) using only data collected as a by-product of typical health care. In addition to disease and trait genetics, EHRs proved a valuable resource for analyzing pharmacogenetic traits and developing reverse genetics approaches such as phenome-wide association studies (PheWASs). PheWASs are designed to survey which of many phenotypes may be associated with a given genetic variant. PheWAS methods have been validated through replication of hundreds of known genotype-phenotype associations, and their use has differentiated between true pleiotropy and clinical comorbidity, added context to genetic discoveries, and helped define disease subtypes, and may also help repurpose medications. PheWAS methods have also proven to be useful with research-collected data. Future efforts that integrate broad, robust collection of phenotype data (e.g., EHR data) with purpose-collected research data in combination with a greater understanding of EHR data will create a rich resource for increasingly more efficient and detailed genome-phenome analysis to usher in new discoveries in precision medicine.

Entities:  

Keywords:  electronic health record; genome-wide association study; phenome-wide association study; phenotyping

Mesh:

Year:  2016        PMID: 27147087      PMCID: PMC5480096          DOI: 10.1146/annurev-genom-090314-024956

Source DB:  PubMed          Journal:  Annu Rev Genomics Hum Genet        ISSN: 1527-8204            Impact factor:   8.929


  82 in total

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Authors:  Joshua C Denny; Marylyn D Ritchie; Melissa A Basford; Jill M Pulley; Lisa Bastarache; Kristin Brown-Gentry; Deede Wang; Dan R Masys; Dan M Roden; Dana C Crawford
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Journal:  PLoS Genet       Date:  2014-12-04       Impact factor: 5.917

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Review 5.  Interdisciplinary Models for Research and Clinical Endeavors in Genomic Medicine: A Scientific Statement From the American Heart Association.

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