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Genomic atlas of the human plasma proteome
Nature ( IF 50.5 ) Pub Date : 2018-06-01 , DOI: 10.1038/s41586-018-0175-2
Benjamin B Sun 1 , Joseph C Maranville 2, 3 , James E Peters 1, 4 , David Stacey 1 , James R Staley 1 , James Blackshaw 1 , Stephen Burgess 1, 5 , Tao Jiang 1 , Ellie Paige 1, 6 , Praveen Surendran 1 , Clare Oliver-Williams 1, 7 , Mihir A Kamat 1 , Bram P Prins 1 , Sheri K Wilcox 8 , Erik S Zimmerman 8 , An Chi 2 , Narinder Bansal 1, 9 , Sarah L Spain 10 , Angela M Wood 1 , Nicholas W Morrell 4, 11 , John R Bradley 12 , Nebojsa Janjic 8 , David J Roberts 13, 14 , Willem H Ouwehand 4, 15, 16, 17, 18 , John A Todd 19 , Nicole Soranzo 4, 15, 17, 18 , Karsten Suhre 20 , Dirk S Paul 1 , Caroline S Fox 2 , Robert M Plenge 2, 3 , John Danesh 1, 4, 17, 18 , Heiko Runz 2, 21 , Adam S Butterworth 1, 18
Affiliation  

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.A genetic atlas of the human plasma proteome, comprising 1,927 genetic associations with 1,478 proteins, identifies causes of disease and potential drug targets.

中文翻译:


人类血浆蛋白质组基因组图谱



尽管血浆蛋白在生物过程中具有重要作用并且是许多药物的直接靶标,但控制血浆蛋白水平个体间差异的遗传因素尚不清楚。在这里,我们通过 INTERVAL 研究描述了健康献血者血浆蛋白质组的遗传结构。我们确定了 1,927 个与 1,478 种蛋白质的遗传关联,比现有知识增加了四倍,其中包括 1,104 种蛋白质的反式关联。为了了解血浆蛋白水平扰动的后果,我们应用了一种将遗传变异与生物途径、疾病和药物数据库联系起来的综合方法。我们证明蛋白质数量性状基因座与基因表达数量性状基因座以及疾病相关基因座重叠,并使用孟德尔随机化分析找到蛋白质生物标志物在疾病中具有因果作用的证据。通过通过特定蛋白质将遗传因素与疾病联系起来,我们的分析突出了潜在的治疗靶点、将现有药物与新疾病适应症相匹配的机会以及正在开发的药物的潜在安全性问题。人类血浆蛋白质组的遗传图谱,包含 1,927 个与1,478 种蛋白质,可识别疾病原因和潜在药物靶点。
更新日期:2018-06-01
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