| Literature DB >> 24270849 |
Joshua C Denny, Lisa Bastarache, Marylyn D Ritchie, Robert J Carroll, Raquel Zink, Jonathan D Mosley, Julie R Field, Jill M Pulley, Andrea H Ramirez, Erica Bowton, Melissa A Basford, David S Carrell, Peggy L Peissig, Abel N Kho, Jennifer A Pacheco, Luke V Rasmussen, David R Crosslin, Paul K Crane, Jyotishman Pathak, Suzette J Bielinski, Sarah A Pendergrass, Hua Xu, Lucia A Hindorff, Rongling Li, Teri A Manolio, Christopher G Chute, Rex L Chisholm, Eric B Larson, Gail P Jarvik, Murray H Brilliant, Catherine A McCarty, Iftikhar J Kullo, Jonathan L Haines, Dana C Crawford, Daniel R Masys, Dan M Roden.
Abstract
Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10⁻⁶ (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort (n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.Entities:
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Year: 2013 PMID： 24270849 PMCID： PMC3969265 DOI： 10.1038/nbt.2749
Source DB: PubMed Journal: Nat Biotechnol ISSN： 1087-0156 Impact factor: 54.908