与蛋白质水平之间比率的遗传关联可发现新的 pQTLs 并揭示蛋白质与蛋白质之间的相互作用。

IF 11.1 Q1 CELL BIOLOGY
Cell genomics Pub Date : 2024-03-13 Epub Date: 2024-02-26 DOI:10.1016/j.xgen.2024.100506
Karsten Suhre
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引用次数: 0

摘要

蛋白质数量性状位点(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,提示了顺式和反式相关蛋白质之间的关系,并将蛋白质与疾病终点联系起来。利用英国生物库 54,000 多份样本中测出的 1,463 种蛋白质的 Olink 蛋白质组学数据,我们发现了 4,248 种与 2,821 种蛋白质水平比率(rQTLs)相关的关联。对比率进行 GWAS 分析,发现的遗传信号数量增加了 24.7%。这种方法可以发现与临床相关的新基因位点,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,我们的研究为从英国广播公司(UKB)蛋白质组学数据中获得遗传学见解增添了重要价值,并推动了在大规模基因组学分析中更广泛地使用比率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic associations with ratios between protein levels detect new pQTLs and reveal protein-protein interactions.

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.

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