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遗传关联与蛋白质水平之间的比值检测新的 pQTL 并揭示蛋白质-蛋白质相互作用。

Genetic associations with ratios between protein levels detect new pQTLs and reveal protein-protein interactions.

机构信息

Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha 24144, Qatar; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA.

出版信息

Cell Genom. 2024 Mar 13;4(3):100506. doi: 10.1016/j.xgen.2024.100506. Epub 2024 Feb 26.

Abstract

Protein quantitative trait loci (pQTLs) are an invaluable source of information for drug target development because they provide genetic evidence to support protein function, suggest relationships between cis- and trans-associated proteins, and link proteins to disease endpoints. Using Olink proteomics data for 1,463 proteins measured in over 54,000 samples of the UK Biobank, we identified 4,248 associations with 2,821 ratios between protein levels (rQTLs). rQTLs were 7.6-fold enriched in known protein-protein interactions, suggesting that their ratios reflect biological links between the implicated proteins. Conducting a GWAS on ratios increased the number of discovered genetic signals by 24.7%. The approach can identify novel loci of clinical relevance, support causal gene identification, and reveal complex networks of interacting proteins. Taken together, our study adds significant value to the genetic insights that can be derived from the UKB proteomics data and motivates the wider use of ratios in large-scale GWAS.

摘要

蛋白质数量性状基因座(pQTLs)是药物靶点开发的宝贵信息来源,因为它们提供了支持蛋白质功能的遗传证据,暗示了顺式和反式相关蛋白之间的关系,并将蛋白质与疾病终点联系起来。利用 UK Biobank 中超过 54000 个样本中测量的 1463 种蛋白质的 Olink 蛋白质组学数据,我们确定了 4248 个与 2821 个蛋白质水平比率(rQTLs)之间的关联。rQTLs 在已知的蛋白质-蛋白质相互作用中富集了 7.6 倍,这表明它们的比率反映了所涉及蛋白质之间的生物学联系。对比率进行 GWAS 增加了发现遗传信号的数量24.7%。该方法可以识别具有临床相关性的新基因座,支持因果基因鉴定,并揭示相互作用蛋白质的复杂网络。总之,我们的研究为从 UKB 蛋白质组学数据中得出的遗传见解增添了重要价值,并促使在大规模 GWAS 中更广泛地使用比率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/328b/10943581/770a76726a83/fx1.jpg

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