Phenome-wide association studies across large population cohorts support drug target validation.
Phenome-wide association studies across large population cohorts support drug target validation.
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DOI：
10.1038/s41467-018-06540-3
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发表时间：
2018-10-16
影响因子：
16.6
通讯作者：
Runz H
中科院分区：
文献类型：
--
作者：
Diogo D;Tian C;Franklin CS;Alanne-Kinnunen M;March M;Spencer CCA;Vangjeli C;Weale ME;Mattsson H;Kilpeläinen E;Sleiman PMA;Reilly DF;McElwee J;Maranville JC;Chatterjee AK;Bhandari A;Nguyen KH;Estrada K;Reeve MP;Hutz J;Bing N;John S;MacArthur DG;Salomaa V;Ripatti S;Hakonarson H;Daly MJ;Palotie A;Hinds DA;Donnelly P;Fox CS;Day-Williams AG;Plenge RM;Runz H
全表型关联研究（PheWAS）已被提议作为药物开发的可能辅助手段，通过阐明作用机制，确定替代适应症或预测药物不良事件（ADE）。在这里，我们选择了25个单核苷酸多态性（SNP），通过全基因组关联研究（GWAS）与19个常见疾病适应症的候选药物靶点相关联。我们在四个具有广泛健康信息的大型队列（23andMe，UK Biobank，FINRISK，CHOP）中通过PheWAS询问这些SNP与多达697，815个个体的1683个二元终点的关联，并对145个映射的疾病终点进行荟萃分析。我们的分析重复了75%的已知GWAS关联（P < 0.05），并确定了9个研究范围内显著的新关联（71个FDR < 0.1）。我们描述了可以预测ADE的关联，例如，PNPLA 3中rs738409（p.I148M）的痤疮、高胆固醇、痛风和胆结石，IFIH 1中rs 1990760（p.T946A）的哮喘。我们的研究结果表明，PheWAS是药物发现工具包的一个强大补充。测试遗传变异和一系列表型之间的关联可以帮助药物开发。在一项多达697，815人的全表型关联研究中，Diogo等人确定了预测疗效、替代适应症或药物不良反应的基因型-表型关联。
Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P < 0.05) and identify nine study-wide significant novel associations (of 71 with FDR < 0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery. Testing the association between genetic variants and a range of phenotypes can assist drug development. Here, in a phenome-wide association study in up to 697,815 individuals, Diogo et al. identify genotype–phenotype associations predicting efficacy, alternative indications or adverse drug effects.
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影响因子：
120.1
作者：
Cook, David;Brown, Dearg;Pangalos, Menelas N.
通讯作者：
Pangalos, Menelas N.
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
46.9
作者：
通讯作者：
--
DOI：
10.1056/nejmoa1405760
发表时间：
2015-01-15
期刊：
The New England journal of medicine
影响因子：
--
作者：
Büller HR;Bethune C;Bhanot S;Gailani D;Monia BP;Raskob GE;Segers A;Verhamme P;Weitz JI;FXI-ASO TKA Investigators
通讯作者：
FXI-ASO TKA Investigators
影响因子：
3.9
作者：
Ehrenstein V;Nielsen H;Pedersen AB;Johnsen SP;Pedersen L
通讯作者：
Pedersen L