A genome-wide association study identifies protein quantitative trait loci (pQTLs).
A genome-wide association study identifies protein quantitative trait loci (pQTLs).
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DOI：
10.1371/journal.pgen.1000072
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发表时间：
2008-05-09
期刊：
影响因子：
4.5
通讯作者：
Ferrucci L
中科院分区：
文献类型：
--
作者：
Melzer D;Perry JR;Hernandez D;Corsi AM;Stevens K;Rafferty I;Lauretani F;Murray A;Gibbs JR;Paolisso G;Rafiq S;Simon-Sanchez J;Lango H;Scholz S;Weedon MN;Arepalli S;Rice N;Washecka N;Hurst A;Britton A;Henley W;van de Leemput J;Li R;Newman AB;Tranah G;Harris T;Panicker V;Dayan C;Bennett A;McCarthy MI;Ruokonen A;Jarvelin MR;Guralnik J;Bandinelli S;Frayling TM;Singleton A;Ferrucci L
有大量证据表明人类遗传变异影响基因表达。全基因组研究表明，mRNA 水平与编码这些 mRNA 转录本的基因中或附近的遗传变异（顺式效应）和基因组其他地方的遗传变异（反式效应）相关。遗传变异在确定蛋白质水平中的作用尚未得到系统评估。使用全基因组关联方法，我们表明常见的遗传变异会影响人血清和血浆中临床相关蛋白质的水平。我们评估了基于人群的 InCHIANTI 研究中 496,032 个多态性对 1200 名禁食个体测量的 42 种蛋白质水平的作用。蛋白质包括胰岛素、多种白细胞介素、脂肪因子、趋化因子和肝功能标记物，这些蛋白质与许多常见疾病（包括代谢、炎症和感染性疾病）有关。我们确定了八种顺式效应，包括IL6R (p = 1.8×10−57)、CCL4L1 (p = 3.9×10−21)、IL18 (p = 6.8×10−13)、LPA (p = 4.4×10−10)、GGT1 中或附近的变异体(p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) 和 IL1RN (p = 7.3×10−6) 基因，均与其各自的蛋白质产物相关，每个等位基因的效应大小范围为 0.19 至 0.69 标准差。所涉及的机制包括与未结合的可溶性受体 (IL6R) 结合的裂解速率的改变、不同大小蛋白质 (LPA) 的分泌速率的改变、基因拷贝数的变化 (CCL4L1) 和转录的改变 (GGT1)。我们发现了一种新的反式效应，它是 ABO 血型与肿瘤坏死因子 α (TNF-α) 水平之间的关联 (p = 6.8×10−40)，但当使用不同的测定方法或在第二项研究中测量 TNF-α 时，这一发现并不存在，表明存在测定特异性关联。我们的结果表明蛋白质水平具有基因表达遗传学的一些特征。其中包括顺式位置存在强烈的遗传效应。蛋白质数量性状基因座（pQTL）的鉴定可能是增进我们对疾病途径的理解的有力补充方法。分子遗传学的中心法则之一是DNA转录为RNA，RNA再翻译为蛋白质，而蛋白质的改变可以影响人类疾病。全基因组关联研究最近揭示了许多影响人类疾病的新 DNA 变异。为了补充这些努力，一些全基因组研究已经确定 DNA 变异会影响 mRNA 表达水平。影响 mRNA 水平的基因座被称为“eQTL”。在这项研究中，我们对这个拼图中的第三部分进行了首次全基因组关联研究——DNA 变异与蛋白质水平或“pQTL”相关的作用。我们分析了 InCHIANTI 研究中血液成分中测量的 42 种蛋白质。我们确定了八种顺式效应，包括 IL6R、CCL4、IL18、LPA、GGT1、SHBG、CRP 和 IL1RN 基因中或附近的常见变异，所有这些都与各自蛋白质产物的血液水平相关。涉及的机制包括转录改变（GGT1），以及与未结合的可溶性受体（IL6R）结合的裂解速率、不同大小蛋白质（LPA）分泌速率的改变以及基因拷贝数（CCL4）的变化。许多这些蛋白质的血液水平与人类疾病相关，“pQTL”的识别反过来可能有助于我们对疾病的理解。
There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts – cis effects, and elsewhere in the genome – trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10−57), CCL4L1 (p = 3.9×10−21), IL18 (p = 6.8×10−13), LPA (p = 4.4×10−10), GGT1 (p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) and IL1RN (p = 7.3×10−6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10−40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. One of the central dogmas of molecular genetics is that DNA is transcribed to RNA which is translated to protein and alterations to proteins can influence human diseases. Genome-wide association studies have recently revealed many new DNA variants that influence human diseases. To complement these efforts, several genome-wide studies have established that DNA variation influences mRNA expression levels. Loci influencing mRNA levels have been termed “eQTLs”. In this study we have performed the first genome-wide association study of the third piece in this jigsaw – the role of DNA variation in relation to protein levels, or “pQTLs”. We analysed 42 proteins measured in blood fractions from the InCHIANTI study. We identified eight cis effects including common variants in or near the IL6R, CCL4, IL18, LPA, GGT1, SHBG, CRP and IL1RN genes, all associated with blood levels of their respective protein products. Mechanisms implicated included altered transcription (GGT1) but also rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA) and variation in gene copy number (CCL4). Blood levels of many of these proteins are correlated with human diseases and the identification of “pQTLs” may in turn help our understanding of disease.
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影响因子：
15.9
作者：
BOERWINKLE, E;LEFFERT, CC;HOBBS, HH
通讯作者：
HOBBS, HH
DOI：
10.1111/j.1532-5415.2000.tb03873.x
发表时间：
2000-12-01
影响因子：
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作者：
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通讯作者：
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作者：
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56.9
作者：
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通讯作者：
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影响因子：
56.9
作者：
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通讯作者：
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