The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery. Pendergrass, S. A., Brown-Gentry, K., Dudek, S. M., Torstenson, E. S., Ambite, J. L., Avery, C. L., Buyske, S., Cai, C., Fesinmeyer, M. D., Haiman, C., Heiss, G., Hindorff, L. A., Hsu, C., Jackson, R. D., Kooperberg, C., Le Marchand, L., Lin, Y., Matise, T. C., Moreland, L., Monroe, K., Reiner, A. P., Wallace, R., Wilkens, L. R., Crawford, D. C., & Ritchie, M. D. Genetic epidemiology, 35:410–422, July, 2011.
The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery. [link]Paper  doi  abstract   bibtex   
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.
@article{PendergrassBrownGentryDudekEtAl2011,
	abstract = {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.},
	author = {Pendergrass, S. A. and Brown-Gentry, K. and Dudek, S. M. and Torstenson, E. S. and Ambite, J. L. and Avery, C. L. and Buyske, S. and Cai, C. and Fesinmeyer, M. D. and Haiman, C. and Heiss, G. and Hindorff, L. A. and Hsu, C.-N. and Jackson, R. D. and Kooperberg, C. and Le Marchand, L. and Lin, Y. and Matise, T. C. and Moreland, L. and Monroe, K. and Reiner, A. P. and Wallace, R. and Wilkens, L. R. and Crawford, D. C. and Ritchie, M. D.},
	citation-subset = {IM},
	completed = {2011-09-29},
	country = {United States},
	doi = {10.1002/gepi.20589},
	issn = {1098-2272},
	issn-linking = {0741-0395},
	issue = {5},
	journal = {Genetic epidemiology},
	keywords = {Continental Population Groups, genetics; Databases, Genetic; Ethnic Groups, genetics; Genetic Association Studies, statistics & numerical data; Genetic Variation; Genome-Wide Association Study, statistics & numerical data; Humans; Models, Genetic; Models, Statistical; Phenotype; Polymorphism, Single Nucleotide},
	mid = {NIHMS293168},
	month = jul,
	nlm-id = {8411723},
	owner = {NLM},
	pages = {410--422},
	pmc = {PMC3116446},
	pmid = {21594894},
	url = {https://pubmed.ncbi.nlm.nih.gov/21594894/},

	pubmodel = {Print-Electronic},
	pubstate = {ppublish},
	revised = {2019-01-08},
	title = {The use of phenome-wide association studies ({PheWAS}) for exploration of novel genotype-phenotype relationships and pleiotropy discovery.},
	volume = {35},
	year = {2011},
	bdsk-url-1 = {https://pubmed.ncbi.nlm.nih.gov/21594894/},
	bdsk-url-2 = {https://doi.org/10.1002/gepi.20589}}
Downloads: 0
About
Documentation
Keywords
Search
Users
Terms and Conditions of Use
Privacy Policy
Sitemap
© BibBase.org 2021