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通过遗传学和疾病关联进行大规模血浆蛋白质组学比较。

Large-scale plasma proteomics comparisons through genetics and disease associations.

机构信息

deCODE Genetics/Amgen, Reykjavik, Iceland.

School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland.

出版信息

Nature. 2023 Oct;622(7982):348-358. doi: 10.1038/s41586-023-06563-x. Epub 2023 Oct 4.

Abstract

High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.

摘要

高通量蛋白质组学平台可测量血浆中的数千种蛋白质,结合基因组和表型信息,具有弥合基因组与疾病之间差距的潜力。在这里,我们对英国生物库制药蛋白质组学项目生成的 Olink Explore 3072 数据进行了关联研究,该研究基于英国生物库的 50,000 多名参与者的血浆样本,这些样本具有表型和基因型数据,并按英国或爱尔兰、非洲和南亚血统进行分层。我们将结果与来自 36,000 名冰岛人的 SomaScan v4 研究进行了比较,其中有 1,514 人也有 Olink 数据。我们发现两个平台之间存在适度的相关性。尽管在两个平台上检测到类似数量的顺式蛋白质数量性状基因座(Olink 上有 2,101 个,SomaScan 上有 2,120 个),但支持这种证据的检测性能的检测比例在 Olink 平台上更高(72%对 43%)。相当数量的蛋白质具有平台之间存在差异的基因组关联。我们提供了一些例子,说明平台之间的差异可能会影响从蛋白质水平与疾病研究整合中得出的结论。我们展示了如何利用英国生物库参与者的不同血统来帮助检测新的关联并细化基因组位置。我们的结果表明了两个最常用的高通量蛋白质组学平台提供的信息的价值,并展示了它们之间的差异,这些差异有时提供了有用的互补性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/10567571/5c8b2134d37c/41586_2023_6563_Fig1_HTML.jpg

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