High-throughput framework for genetic analyses of adverse drug reactions using electronic health records.
High-throughput framework for genetic analyses of adverse drug reactions using electronic health records.
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DOI：
10.1371/journal.pgen.1009593
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发表时间：
2021-06
期刊：
影响因子：
4.5
通讯作者：
Wei WQ
中科院分区：
文献类型：
--
作者：
Zheng NS;Stone CA;Jiang L;Shaffer CM;Kerchberger VE;Chung CP;Feng Q;Cox NJ;Stein CM;Roden DM;Denny JC;Phillips EJ;Wei WQ
了解遗传变异对药物反应的贡献可以改善精准医疗的交付。然而，药物反应的全基因组关联研究（GWAS）并不常见，并且经常受到小样本量的阻碍。我们提出了一个高通量的框架，以有效地识别合格的患者的药物不良反应（ADR）的遗传研究使用“药物过敏”标签从电子健康记录（EHR）。作为概念验证，我们对来自范德比尔特大学医学中心BioVU DNA生物库的14种常见药物/药物组的81，739名个体进行了ADR的GWAS。我们在P < 5 × 10−8时确定了7个与ADR相关的遗传位点，包括已知的遗传相关性，如CYP 2D 6和OPRM 1与CYP 2D 6代谢的阿片类ADR相关。额外的表达数量性状基因座和全表型关联分析增加了所观察到的关联的证据。我们的高通量框架具有可扩展性和便携性，能够进行有影响力的药物基因组学研究，以改善精准医学。药物不良反应是医疗保健系统的一个相当大的负担。遗传学研究可以提高我们对药物不良反应的病理生理机制的理解，但由于样本量小而受到阻碍。药物反应比生理特征和常见疾病更少被记录。在这里，我们提出了一个高通量的框架，以有效地识别合格的患者的遗传研究的药物不良反应的电子健康记录。我们通过对来自范德比尔特大学医学中心BioVU DNA生物库的81，739名个体进行14种常见药物/药物组的不良反应的全基因组关联研究来验证我们的方法，确定了与药物不良反应相关的7个遗传位点。我们的高通量框架可以实现有影响力的药物基因组学研究，以帮助制定将正确的药物输送给正确的人的临床指南。
Understanding the contribution of genetic variation to drug response can improve the delivery of precision medicine. However, genome-wide association studies (GWAS) for drug response are uncommon and are often hindered by small sample sizes. We present a high-throughput framework to efficiently identify eligible patients for genetic studies of adverse drug reactions (ADRs) using “drug allergy” labels from electronic health records (EHRs). As a proof-of-concept, we conducted GWAS for ADRs to 14 common drug/drug groups with 81,739 individuals from Vanderbilt University Medical Center’s BioVU DNA Biobank. We identified 7 genetic loci associated with ADRs at P < 5 × 10−8, including known genetic associations such as CYP2D6 and OPRM1 for CYP2D6-metabolized opioid ADR. Additional expression quantitative trait loci and phenome-wide association analyses added evidence to the observed associations. Our high-throughput framework is both scalable and portable, enabling impactful pharmacogenomic research to improve precision medicine. Adverse drug reactions are a considerable burden on the healthcare system. Genetic studies can improve our understanding of the pathophysiological mechanisms of adverse drug reactions but have been hindered by small sample sizes. Drug responses are less often recorded than physiological traits and common diseases. Here, we present a high-throughput framework to efficiently identify eligible patients for genetic studies of adverse drug reactions from electronic health records. We validated our approach by conducting genome-wide association studies for adverse reactions to 14 common drug/drug groups with 81,739 individuals from Vanderbilt University Medical Centre’s BioVU DNA Biobank, identifying 7 genetic loci associated with adverse drug reactions. Our high-throughput framework can enable impactful pharmacogenomic research to help develop clinical guidelines for the delivery of the right drug to the right person.
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DOI：
10.1038/nrd.2016.234
发表时间：
2017-01
期刊：
Nature reviews. Drug discovery
影响因子：
--
作者：
Giacomini KM;Yee SW;Mushiroda T;Weinshilboum RM;Ratain MJ;Kubo M
通讯作者：
Kubo M
影响因子：
2.8
作者：
Kirchheiner, J.;Schmidt, H.;Brockmoeller, J.
通讯作者：
Brockmoeller, J.
影响因子：
30.8
作者：
Das, Sayantan;Forer, Lukas;Schoenherr, Sebastian;Sidore, Carlo;Locke, Adam E.;Kwong, Alan;Vrieze, Scott I.;Chew, Emily Y.;Levy, Shawn;McGue, Matt;Schlessinger, David;Stambolian, Dwight;Loh, Po-Ru;Iacono, William G.;Swaroop, Anand;Scott, Laura J.;Cucca, Francesco;Kronenberg, Florian;Boehnke, Michael;Abecasis, Goncalo R.;Fuchsberger, Christian
通讯作者：
Fuchsberger, Christian
影响因子：
46.9
作者：
通讯作者：
--
影响因子：
64.8
作者：
Relling MV;Evans WE
通讯作者：
Evans WE