【摘要】 目的 本研究采用全面的孟德尔随机化（MR）方法，以揭示心律失常的潜在蛋白质标志物和治疗靶点。方法 本研究采用孟德尔随机化方法，分析了来自FinnGen联盟R9发布数据（67 035例病例和220 224例对照）的汇总统计数据。我们进行了逆方差加权MR分析，重点关注与deCODE研究中2 845种血液蛋白质相关的顺式作用变异（n=35 559）。为了确定候选蛋白质的因果关系，我们使用共定位和基于汇总数据的孟德尔随机化分析进行了相关实验。通过评估蛋白质相互作用和药物可及性，确定了潜在的治疗靶点。结果 分析确定了11种蛋白质的遗传预测水平与心律失常风险增加有关，特别是PCSK9。值得注意的是，SERPINC1、MBTPS1、PROS1、ANGPTL3和PCSK9之间的相互作用表明存在一个影响心律失常风险的网络。此前被认为与预防血栓形成和脂质代谢有关的PCSK9、ANGPTL3、SERPINC1和PROS1，如今已被证实是心律失常的潜在治疗靶点。结论 本研究确定了一系列与心律失常风险相关的蛋白质生物标志物，为该疾病的病因学提供了新的见解。这些发现为开发和筛选心律失常治疗的生物标志物和治疗剂提供了有前景的途径。更多还原

【Abstract】 Objective This study adopted a comprehensive Mendelian randomization(MR) approach to unveil potential protein biomarkers and therapeutic targets for arrhythmias. Methods In this study, the Mendelian randomization method was utilized to analyze the summary statistics derived from the data released by the FinnGen Consortium R9(67,035 cases and 220,224 controls). An inverse variance weighted MR analysis was conducted, with a particular focus on cis-acting variants(n=35,559) associated with 2 845 blood proteins in the deCODE study. To establish the causal relationships of candidate proteins, relevant experiments were carried out using colocalization and Mendelian randomization analysis based on summary data. Potential therapeutic targets were determined by evaluating protein-protein interactions and drug accessibility. Results Through Mendelian randomization analysis, this study identified significant causal associations between the genetically predicted levels of 11 proteins and an increased risk of arrhythmia. Among them, the association of PCSK9 was particularly prominent. Protein-protein interaction analysis indicated that there were interaction relationships between SERPINC1, MBTPS1, PROS1, ANGPTL3 and PCSK9. Conclusions This study has identified a series of protein biomarkers associated with the risk of arrhythmia. The analysis shows that there is an interaction network among these proteins, suggesting that they could serve as potential biomarkers and therapeutic targets for arrhythmia.更多还原