Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data

被引：672

作者：

Denny, Joshua C. ^{[1
,2
]}

Bastarache, Lisa ^{[2
]}

Ritchie, Marylyn D. ^{[3
]}

Carroll, Robert J. ^{[2
]}

Zink, Raquel ^{[2
]}

Mosley, Jonathan D. ^{[1
]}

Field, Julie R. ^{[4
]}

Pulley, Jill M. ^{[4
,5
]}

Ramirez, Andrea H. ^{[1
]}

Bowton, Erica ^{[4
]}

Basford, Melissa A. ^{[4
]}

Carrell, David S. ^{[6
]}

Peissig, Peggy L. ^{[7
]}

Kho, Abel N. ^{[8
]}

Pacheco, Jennifer A. ^{[9
]}

Rasmussen, Luke V. ^{[10
]}

Crosslin, David R. ^{[11
]}

Crane, Paul K. ^{[12
]}

Pathak, Jyotishman ^{[13
,14
]}

Bielinski, Suzette J. ^{[15
]}

Pendergrass, Sarah A. ^{[3
]}

Xu, Hua ^{[16
]}

Hindorff, Lucia A.

Li, Rongling ^{[17
]}

Manolio, Teri A. ^{[17
]}

Chute, Christopher G. ^{[13
]}

Chisholm, Rex L. ^{[18
]}

Larson, Eric B. ^{[6
]}

Jarvik, Gail P. ^{[11
,12
,14
]}

Brilliant, Murray H. ^{[19
]}

McCarty, Catherine A. ^{[20
]}

Kullo, Iftikhar J. ^{[21
]}

Haines, Jonathan L. ^{[22
]}

Crawford, Dana C. ^{[22
]}

Masys, Daniel R. ^{[23
]}

Roden, Dan M. ^{[1
,24
]}

机构：

[1] Vanderbilt Univ, Sch Med, Dept Med, Nashville, TN 37212 USA

[2] Vanderbilt Univ, Sch Med, Dept Biomed Informat, Nashville, TN 37212 USA

[3] Penn State Univ, Dept Biochem & Mol Biol, Ctr Syst Genom, University Pk, PA 16802 USA

[4] Vanderbilt Univ, Sch Med, Res Off, Nashville, TN 37212 USA

[5] Vanderbilt Univ, Sch Med, Dept Med Adm, Nashville, TN 37212 USA

[6] Grp Hlth Res Inst, Seattle, WA USA

[7] Marshfield Clin Res Fdn, Biomed Informat Res Ctr, Marshfield, WI USA

[8] Northwestern Univ, Dept Med, Feinberg Sch Med, Chicago, IL 60611 USA

[9] Northwestern Univ, Ctr Genet Med, Feinberg Sch Med, Chicago, IL 60611 USA

[10] Northwestern Univ, Dept Preventat Med, Feinberg Sch Med, Chicago, IL 60611 USA

[11] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA

[12] Univ Washington, Dept Med, Seattle, WA USA

[13] Mayo Clin, Div Biomed Informat, Rochester, MN USA

[14] Mayo Clin, Div Stat, Rochester, MN USA

[15] Mayo Clin, Div Epidemiol, Rochester, MN USA

[16] Univ Texas Hlth Sci Ctr Houston, Sch Biomed Informat, Houston, TX 77030 USA

[17] NHGRI, Div Genom Med, Bethesda, MD 20892 USA

[18] Northwestern Univ, Dept Cell & Mol Biol, Feinberg Sch Med, Chicago, IL 60611 USA

[19] Marshfield Clin Res Fdn, Ctr Human Genet, Marshfield, WI USA

[20] Essentia Inst Rural Hlth, Duluth, MN USA

[21] Mayo Clin, Div Cardiovasc Dis, Rochester, MN USA

[22] Vanderbilt Univ, Sch Med, Dept Mol Physiol & Biophys, Ctr Human Genet Res, Nashville, TN 37212 USA

[23] Univ Washington, Dept Biomed Informat & Med Educ, Seattle, WA 98195 USA

[24] Vanderbilt Univ, Sch Med, Dept Pharmacol, Nashville, TN 37212 USA

来源：

NATURE BIOTECHNOLOGY | 2013年 / 31卷 / 12期

关键词：

RISK; VARIANTS; DISEASES; BIOBANK; TRAITS; TOOL; METAANALYSIS; PHENOTYPES; MELANOMA;

D O I：

10.1038/nbt.2749

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for a human disease; many of these associations require further study to replicate the results. Here we report the first c large-scale application of the phenome-wide association "study (PheWAS) paradigm within electronic medical records E (EMRs), an unbiased approach to replication and discovery. v that interrogates relationships between targeted genotypes 1s and multiple phenotypes. We scanned for associations z between 3,144 single-nucleotide polymorphisms (previously N 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 x 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.

引用

页码：1102 / +

页数：12

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