MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
MRL, Merck & Co., Inc., Kenilworth, NJ, USA.
Nature. 2018 Jun;558(7708):73-79. doi: 10.1038/s41586-018-0175-2. Epub 2018 Jun 6.
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.
虽然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点，但控制个体间血浆蛋白水平差异的遗传因素尚不清楚。在这里，我们描述了 INTERVAL 研究中健康献血者的人类血浆蛋白质组的遗传结构。我们确定了 1,478 种蛋白质与 1,927 种遗传关联，这是现有知识的四倍，包括 1,104 种蛋白质的跨关联。为了了解血浆蛋白水平干扰的后果，我们应用了一种综合方法，将遗传变异与生物途径、疾病和药物数据库联系起来。我们表明，蛋白质数量性状位点与基因表达数量性状位点以及与疾病相关的位点重叠，并且使用孟德尔随机化分析发现蛋白质生物标志物在疾病中具有因果作用的证据。通过将遗传因素与特定蛋白质相关的疾病联系起来，我们的分析突出了潜在的治疗靶点、将现有药物与新的疾病适应症相匹配的机会，以及开发中的药物的潜在安全问题。
