Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.
Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.
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DOI：
10.1146/annurev-genom-090314-024956
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发表时间：
2016-08-31
影响因子：
8.7
通讯作者：
Roden DM
中科院分区：
文献类型：
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作者：
Denny JC;Bastarache L;Roden DM
从21世纪初开始，与电子健康记录（EHR）相关的生物标本的积累使得基因组-表型组研究成为可能（即，遗传变异和表型的比较分析）仅使用作为典型医疗保健副产品收集的数据。除了疾病和性状遗传学，EHR被证明是分析药物遗传学性状和开发反向遗传学方法（如全表型关联研究（PheWAS））的宝贵资源。PheWAS旨在调查许多表型中的哪些可能与给定的遗传变异相关。PheWAS方法已通过复制数百种已知的基因型-表型关联得到验证，它们的使用区分了真正的多效性和临床合并症，为遗传发现增加了背景，并有助于定义疾病亚型，还可能有助于重新使用药物。PheWAS方法也被证明对研究收集的数据有用。未来的努力，整合广泛，强大的收集表型数据（例如，EHR数据）与目的收集的研究数据相结合，再加上对EHR数据的更深入了解，将为越来越高效和详细的基因组-表型组分析创造丰富的资源，以迎来精准医学的新发现。
Beginning in the early 2000s, the accumulation of biospecimens linked to electronic health records (EHRs) made possible genome-phenome studies (i.e., comparative analyses of genetic variants and phenotypes) using only data collected as a by-product of typical health care. In addition to disease and trait genetics, EHRs proved a valuable resource for analyzing pharmacogenetic traits and developing reverse genetics approaches such as phenome-wide association studies (PheWASs). PheWASs are designed to survey which of many phenotypes may be associated with a given genetic variant. PheWAS methods have been validated through replication of hundreds of known genotype-phenotype associations, and their use has differentiated between true pleiotropy and clinical comorbidity, added context to genetic discoveries, and helped define disease subtypes, and may also help repurpose medications. PheWAS methods have also proven to be useful with research-collected data. Future efforts that integrate broad, robust collection of phenotype data (e.g., EHR data) with purpose-collected research data in combination with a greater understanding of EHR data will create a rich resource for increasingly more efficient and detailed genome-phenome analysis to usher in new discoveries in precision medicine.