Verma Anurag, Ritchie Marylyn D
Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA.
The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA.
Curr Epidemiol Rep. 2017 Dec;4(4):321-329. doi: 10.1007/s40471-017-0127-7. Epub 2017 Nov 2.
Over many decades, researchers have been designing studies to investigate the relationship between genotypes and phenotypes to gain an understanding about the effect of genetics on disease. Recently, a high-throughput approach called phenome-wide associations studies (PheWAS) have been extensively used to identify associations between genetic variants and many diseases and traits simultaneously. In this review, we describe the value of PheWAS along with methodological issues and challenges in interpretation for current applications of PheWAS.
PheWAS have uncovered a paradigm to identify new associations for genetic loci across many diseases. The application of PheWAS have been effective with phenotype data from electronic health records, epidemiological studies, and clinical trials data.
The key strength of a PheWAS is to identify the association of one or more genetic variants with multiple phenotypes, which can showcase interconnections among the phenotypes due to shared genetic associations. While the PheWAS approach appears promising, there are a number of challenges that need to be addressed to provide additional robustness to PheWAS findings.
几十年来，研究人员一直在设计研究以调查基因型与表型之间的关系，从而了解遗传学对疾病的影响。最近，一种名为全表型组关联研究（PheWAS）的高通量方法已被广泛用于同时识别遗传变异与多种疾病和性状之间的关联。在本综述中，我们描述了PheWAS的价值以及当前PheWAS应用在方法学问题和解释方面的挑战。
PheWAS揭示了一种为多种疾病的基因座识别新关联的范例。PheWAS在电子健康记录、流行病学研究和临床试验数据的表型数据应用中很有效。
PheWAS的关键优势在于识别一个或多个遗传变异与多种表型之间的关联，这可以展示由于共享遗传关联而在表型之间的相互联系。虽然PheWAS方法看起来很有前景，但仍有许多挑战需要解决，以使PheWAS的发现更具稳健性。
