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Tissue-specific genetic features inform prediction of drug side effects in clinical trials.
Science Advances ( IF 13.6 ) Pub Date : 2020-09-10 , DOI: 10.1126/sciadv.abb6242
Áine Duffy 1, 2 , Marie Verbanck 1, 2, 3 , Amanda Dobbyn 1, 2, 4 , Hong-Hee Won 5 , Joshua L Rein 6 , Iain S Forrest 1, 2 , Girish Nadkarni 2, 6 , Ghislain Rocheleau 1, 2 , Ron Do 1, 2
Affiliation  

Adverse side effects often account for the failure of drug clinical trials. We evaluated whether a phenome-wide association study (PheWAS) of 1167 phenotypes in >360,000 U.K. Biobank individuals, in combination with gene expression and expression quantitative trait loci (eQTL) in 48 tissues, can inform prediction of drug side effects in clinical trials. We determined that drug target genes with five genetic features—tissue specificity of gene expression, Mendelian associations, phenotype- and tissue-level effects of genome-wide association (GWA) loci driven by eQTL, and genetic constraint—confer a 2.6-fold greater risk of side effects, compared to genes without such features. The presence of eQTL in multiple tissues resulted in more unique phenotypes driven by GWA loci, suggesting that drugs delivered to multiple tissues can induce several side effects. We demonstrate the utility of PheWAS and eQTL data from multiple tissues for informing drug side effect prediction and highlight the need for tissue-specific drug delivery.



中文翻译:

组织特异性遗传特征有助于预测临床试验中的药物副作用。

不良副作用通常是药物临床试验失败的原因。我们评估了超过 360,000 名英国生物银行个体中 1167 种表型的全表型关联研究 (PheWAS),结合 48 种组织中的基因表达和表达数量性状基因座 (eQTL),是否可以为临床试验中的药物副作用预测提供信息。我们确定具有五个遗传特征的药物靶基因——基因表达的组织特异性、孟德尔关联、由 eQTL 驱动的全基因组关联 (GWA) 基因座的表型和组织水平效应以及遗传约束——赋予了 2.6 倍更大与没有这些特征的基因相比,有副作用的风险。eQTL 在多个组织中的存在导致了由 GWA 基因座驱动的更独特的表型,表明递送到多个组织的药物会引起几种副作用。我们展示了来自多个组织的 PheWAS 和 eQTL 数据用于为药物副作用预测提供信息的效用,并强调了对组织特异性药物递送的需求。

更新日期:2020-09-11
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