血浆蛋白质组与遗传学和疾病的大规模整合。
Large-scale integration of the plasma proteome with genetics and disease.
作者信息
Ferkingstad Egil, Sulem Patrick, Atlason Bjarni A, Sveinbjornsson Gardar, Magnusson Magnus I, Styrmisdottir Edda L, Gunnarsdottir Kristbjorg, Helgason Agnar, Oddsson Asmundur, Halldorsson Bjarni V, Jensson Brynjar O, Zink Florian, Halldorsson Gisli H, Masson Gisli, Arnadottir Gudny A, Katrinardottir Hildigunnur, Juliusson Kristinn, Magnusson Magnus K, Magnusson Olafur Th, Fridriksdottir Run, Saevarsdottir Saedis, Gudjonsson Sigurjon A, Stacey Simon N, Rognvaldsson Solvi, Eiriksdottir Thjodbjorg, Olafsdottir Thorunn A, Steinthorsdottir Valgerdur, Tragante Vinicius, Ulfarsson Magnus O, Stefansson Hreinn, Jonsdottir Ingileif, Holm Hilma, Rafnar Thorunn, Melsted Pall, Saemundsdottir Jona, Norddahl Gudmundur L, Lund Sigrun H, Gudbjartsson Daniel F, Thorsteinsdottir Unnur, Stefansson Kari
机构信息
deCODE genetics/Amgen, Inc., Reykjavik, Iceland.
Department of Anthropology, University of Iceland, Reykjavik, Iceland.
出版信息
Nat Genet. 2021 Dec;53(12):1712-1721. doi: 10.1038/s41588-021-00978-w. Epub 2021 Dec 2.
The plasma proteome can help bridge the gap between the genome and diseases. Here we describe genome-wide association studies (GWASs) of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders. We found 18,084 associations between sequence variants and levels of proteins in plasma (protein quantitative trait loci; pQTL), of which 19% were with rare variants (minor allele frequency (MAF) < 1%). We tested plasma protein levels for association with 373 diseases and other traits and identified 257,490 associations. We integrated pQTL and genetic associations with diseases and other traits and found that 12% of 45,334 lead associations in the GWAS Catalog are with variants in high linkage disequilibrium with pQTL. We identified 938 genes encoding potential drug targets with variants that influence levels of possible biomarkers. Combining proteomics, genomics and transcriptomics, we provide a valuable resource that can be used to improve understanding of disease pathogenesis and to assist with drug discovery and development.
血浆蛋白质组有助于弥合基因组与疾病之间的差距。在此，我们描述了对35559名冰岛人使用4907种适体测量血浆蛋白水平的全基因组关联研究（GWAS）。我们发现序列变异与血浆中蛋白质水平（蛋白质定量性状位点；pQTL）之间存在18084种关联，其中19%与罕见变异（次要等位基因频率（MAF）<1%）相关。我们测试了血浆蛋白水平与373种疾病及其他性状的关联，共鉴定出257490种关联。我们将pQTL与疾病及其他性状的遗传关联进行整合，发现GWAS目录中45334个主要关联中有12%与与pQTL处于高连锁不平衡状态的变异相关。我们鉴定出938个编码潜在药物靶点的基因，其变异会影响可能的生物标志物水平。结合蛋白质组学、基因组学和转录组学，我们提供了一种有价值的资源，可用于增进对疾病发病机制的理解，并协助药物发现和开发。
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