Zhang Peng, He Yulu, Zhen Qing, Zhang Yan
Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, the First Hospital of Jilin University, Changchun, China.
Brain Behav. 2025 Sep;15(9):e70857. doi: 10.1002/brb3.70857.
Ischemic stroke (IS) treatment remains a significant challenge. This study aimed to identify potential druggable genes for IS using a systematic druggable genome-wide Mendelian Randomization (MR) analysis.
Two-sample MR analysis was conducted to identify the causal association between potential druggable genes and IS. This involved integrating data from the druggable genome, expression quantitative trait loci (eQTL), protein quantitative trait loci (pQTL), and genome-wide association study summary data of IS. Sensitivity and Bayesian colocalization analyses were used to validate the causal relationships. In addition, phenome-wide MR analysis was used to evaluate the side effects or other indications of the identified druggable genes, and their functions were explored using the Metascape database.
Our MR analysis identified 16 potential druggable genes significantly associated with IS, three of which were significant in the two QTL datasets. Colocalization analysis revealed six druggable genes (two in the blood eQTL [CALCRL, KCNJ11], two in the brain eQTL [NEK3, THSD1], one in the blood pQTL [MMP12], and one in the brain pQTL [HSD17B12]) had a PP.H4 greater than 0.75. Phenome-wide MR analysis indicated that CALCRL is correlated with benign breast neoplasms, and HSD17B12 is associated with essential hypertension and hypertension.
This study identified six potential druggable genes (CALCRL, KCNJ11, NEK3, THSD1, MMP12, and HSD17B12) associated with IS risk. Further research is required to explore the specific roles of these druggable genes in the onset and progression of IS.
缺血性中风(IS)的治疗仍然是一项重大挑战。本研究旨在通过系统的全基因组可药物化孟德尔随机化(MR)分析,确定IS的潜在可药物化基因。
进行两样本MR分析,以确定潜在可药物化基因与IS之间的因果关系。这涉及整合来自可药物化基因组、表达数量性状位点(eQTL)、蛋白质数量性状位点(pQTL)以及IS的全基因组关联研究汇总数据。使用敏感性和贝叶斯共定位分析来验证因果关系。此外,使用全表型组MR分析来评估已鉴定的可药物化基因的副作用或其他指征,并使用Metascape数据库探索其功能。
我们的MR分析确定了16个与IS显著相关的潜在可药物化基因,其中3个在两个QTL数据集中具有显著性。共定位分析显示,6个可药物化基因(血液eQTL中的2个[CALCRL、KCNJ11],脑eQTL中的2个[NEK3、THSD1],血液pQTL中的1个[MMP12],以及脑pQTL中的1个[HSD17B12])的后验概率大于0.75。全表型组MR分析表明,CALCRL与良性乳腺肿瘤相关,而HSD17B12与原发性高血压和高血压相关。
本研究确定了6个与IS风险相关的潜在可药物化基因(CALCRL、KCNJ11、NEK3、THSD1、MMP12和HSD17B12)。需要进一步研究来探索这些可药物化基因在IS发病和进展中的具体作用。