Citation
Pendergrass, Sarah A.; Brown-Gentry, Kristin; Dudek, Scott M.; Torstenson, Eric S.; Ambite, Jose Luis; Avery, Christy L.; Buyske, Steven G.; Cai, Congxing; Fesinmeyer, Megan D.; & Haiman, Christopher A., et al. (2011). The Use of Phenome-Wide Association Studies (PheWAS) for Exploration of Novel Genotype-Phenotype Relationships and Pleiotropy Discovery. Genetic Epidemiology, 35(5), 410-422. PMCID: PMC3116446Abstract
The field of phenomics has been investigating network structure among large arrays of phenotypes, and genome-wide association studies (GWAS) have been used to investigate the relationship between genetic variation and single diseases/outcomes. A novel approach has emerged combining both the exploration of phenotypic structure and genotypic variation, known as the phenome-wide association study (PheWAS). The Population Architecture using Genomics and Epidemiology (PAGE) network is a National Human Genome Research Institute (NHGRI)-supported collaboration of four groups accessing eight extensively characterized epidemiologic studies. The primary focus of PAGE is deep characterization of well-replicated GWAS variants and their relationships to various phenotypes and traits in diverse epidemiologic studies that include European Americans, African Americans, Mexican Americans/Hispanics, Asians/Pacific Islanders, and Native Americans. The rich phenotypic resources of PAGE studies provide a unique opportunity for PheWAS as each genotyped variant can be tested for an association with the wide array of phenotypic measurements available within the studies of PAGE, including prevalent and incident status for multiple common clinical conditions and risk factors, as well as clinical parameters and intermediate biomarkers. The results of PheWAS can be used to discover novel relationships between SNPs, phenotypes, and networks of interrelated phenotypes; identify pleiotropy; provide novel mechanistic insights; and foster hypothesis generation. The PAGE network has developed infrastructure to support and perform PheWAS in a high-throughput manner. As implementing the PheWAS approach has presented several challenges, the infrastructure and methodology, as well as insights gained in this project, are presented herein to benefit the larger scientific community.URL
http://dx.doi.org/10.1002/gepi.20589Reference Type
Journal ArticleYear Published
2011Journal Title
Genetic EpidemiologyAuthor(s)
Pendergrass, Sarah A.Brown-Gentry, Kristin
Dudek, Scott M.
Torstenson, Eric S.
Ambite, Jose Luis
Avery, Christy L.
Buyske, Steven G.
Cai, Congxing
Fesinmeyer, Megan D.
Haiman, Christopher A.
Heiss, Gerardo M.
Hindorff, Lucia A.
Hsu, Chu-Nan
Jackson, Rebecca D.
Kooperberg, Charles L.
Le Marchand, Loic
Lin, Yi
Matise, Tara C.
Moreland, Larry
Monroe, Kristine R.
Reiner, Alexander P.
Wallace, Robert
Wilkens, Lynne R.
Crawford, Dana C.
Ritchie, Marylyn D.