通过脑和血浆蛋白与溃疡性结肠炎全基因组关联研究的整合蛋白质全基因组关联研究来鉴定新型药物靶点。

Identification of novel drug targets through integrative PWAS of brain and plasma proteins with Ulcerative Colitis GWAS.

作者信息

Liu Ningning, Hou Yi, Yu Miao, Liu Gaihong, Xu Yingxue, Jiang Qiang, Wang Dongli, Wang Lianzhu, Zhao Yujie

机构信息

Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.

Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.

出版信息

PLoS One. 2025 May 30;20(5):e0324035. doi: 10.1371/journal.pone.0324035. eCollection 2025.

Abstract

Previous genome-wide association studies (GWAS) have identified various risk variants for ulcerative colitis (UC), but there is a lack of evidence showing how these variants contribute to the development of UC. We employed an integrated pipeline to effectively translate genetic associations in order to identify pathogenic genes for UC.By combining GWAS data for UC with proteomic data from the human brain and plasma, we conducted a protein-wide association study (PWAS) and utilized protein-protein interaction (PPI) network analysis to screen for potential key proteins. Subsequently, causal analysis was performed to assess the potential causal relationships between these proteins and the risk of developing UC.Multiple genes associated with UC were identified in the human brain and plasma proteomes, including known genes such as TYK2 and STAT3, as well as newly discovered genes such as NARS2. PPI networks revealed strong interactions among proteins, including TYK2, STAT3, and IL23R. Causal analysis indicated that 11 risk genes, including FCGR2A, showed significant causal associations with UC, and were linked to key processes related to immune regulation and inflammatory responses, suggesting their potential roles in the pathogenesis of UC.This study integrated GWAS and PWAS data to identify risk genes associated with UC, providing new insights into the disease's pathogenesis and potential therapeutic targets.

摘要

以往的全基因组关联研究(GWAS)已经确定了溃疡性结肠炎(UC)的各种风险变异,但缺乏证据表明这些变异如何导致UC的发生。我们采用了一种综合流程来有效转化基因关联,以确定UC的致病基因。通过将UC的GWAS数据与来自人脑和血浆的蛋白质组数据相结合,我们进行了全蛋白质组关联研究(PWAS),并利用蛋白质-蛋白质相互作用(PPI)网络分析来筛选潜在的关键蛋白质。随后,进行因果分析以评估这些蛋白质与发生UC风险之间的潜在因果关系。在人脑和血浆蛋白质组中鉴定出多个与UC相关的基因,包括TYK2和STAT3等已知基因,以及NARS2等新发现的基因。PPI网络揭示了蛋白质之间的强相互作用,包括TYK2、STAT3和IL23R。因果分析表明,包括FCGR2A在内的11个风险基因与UC存在显著的因果关联,并与免疫调节和炎症反应相关的关键过程有关,表明它们在UC发病机制中的潜在作用。本研究整合了GWAS和PWAS数据以识别与UC相关的风险基因,为该疾病的发病机制和潜在治疗靶点提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fde/12124744/f1b55add2188/pone.0324035.g001.jpg

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