Biomedical Informatics Training Program, Stanford University, Stanford, California, USA.
Department of Bioengineering and Therapeutic Sciences, University of California at San Francisco, San Francisco, California, USA.
Clin Pharmacol Ther. 2021 Sep;110(3):637-648. doi: 10.1002/cpt.2349. Epub 2021 Jul 18.
The increasing availability of genotype data linked with information about drug-response phenotypes has enabled genomewide association studies (GWAS) that uncover genetic determinants of drug response. GWAS have discovered associations between genetic variants and both drug efficacy and adverse drug reactions. Despite these successes, the design of GWAS in pharmacogenomics (PGx) faces unique challenges. In this review, we analyze the last decade of GWAS in PGx. We review trends in publications over time, including the drugs and drug classes studied and the clinical phenotypes used. Several data sharing consortia have contributed substantially to the PGx GWAS literature. We anticipate increased focus on biobanks and highlight phenotypes that would best enable future PGx discoveries.
基因型数据与药物反应表型信息的结合，使得全基因组关联研究（GWAS）得以发现药物反应的遗传决定因素。GWAS 已经发现了遗传变异与药物疗效和药物不良反应之间的关联。尽管取得了这些成功，但药物基因组学（PGx）中的 GWAS 设计面临着独特的挑战。在这篇综述中，我们分析了过去十年中 PGx 的 GWAS。我们回顾了随时间推移的出版物趋势，包括研究的药物和药物类别以及使用的临床表型。几个数据共享联盟为 PGx GWAS 文献做出了重要贡献。我们预计将更加关注生物库，并强调最能促进未来 PGx 发现的表型。
