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利用表型全基因组关联研究(PheWAS)探索新的基因型-表型关系和多效性发现。

The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery.

机构信息

Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232-0700, USA.

出版信息

Genet Epidemiol. 2011 Jul;35(5):410-22. doi: 10.1002/gepi.20589. Epub 2011 May 18.

DOI:10.1002/gepi.20589
PMID:21594894
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3116446/
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.

摘要

表型组学领域一直在研究大量表型之间的网络结构,全基因组关联研究(GWAS)已被用于研究遗传变异与单一疾病/结果之间的关系。一种新的方法已经出现,它结合了表型结构和基因型变异的探索,称为表型全基因组关联研究(PheWAS)。利用基因组学和流行病学构建人群结构(PAGE)网络是一个由四个小组组成的美国国立人类基因组研究所(NHGRI)支持的合作组织,该网络访问了八个广泛特征化的流行病学研究。PAGE 的主要重点是深入研究经过充分复制的 GWAS 变体及其与不同流行病学研究中各种表型和特征的关系,这些研究包括欧洲裔美国人、非裔美国人、墨西哥裔美国人/西班牙裔、亚洲/太平洋岛民和美洲原住民。PAGE 研究丰富的表型资源为 PheWAS 提供了独特的机会,因为每个基因分型的变体都可以与 PAGE 研究中可用的广泛表型测量值进行关联测试,包括多种常见临床病症和危险因素的流行和发病情况,以及临床参数和中间生物标志物。PheWAS 的结果可用于发现 SNP、表型和相互关联的表型网络之间的新关系;识别多效性;提供新的机制见解;并促进假设的产生。PAGE 网络已经开发了基础设施,以支持和以高通量方式执行 PheWAS。由于实施 PheWAS 方法提出了一些挑战,因此本文介绍了该基础设施和方法,以及在此项目中获得的见解,以造福更广泛的科学界。

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