Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Office of Beijing Cardiovascular Diseases Prevention, Beijing, China.
Circ Arrhythm Electrophysiol. 2024 Oct;17(10):e013037. doi: 10.1161/CIRCEP.124.013037. Epub 2024 Oct 2.
Currently, there are no reliable methods for predicting and preventing atrial fibrillation (AF) in its early stages. This study aimed to identify plasma proteins associated with AF to discover biomarkers and potential drug targets.
The UK Biobank Pharma Proteomics Project examined 2923 circulating proteins using the Olink platform, forming the basis of this prospective cohort study. The UK Biobank Pharma Proteomics Project included a randomly selected discovery cohort and the consortium-selected replication cohort. The study's end point was incident AF, identified using codes. The association between plasma proteins and incident AF was evaluated using Cox proportional hazard models in both cohorts. Proteins present in both cohorts underwent Mendelian randomization analysis to delineate causal connections, utilizing -protein quantitative trait loci as genetic tools. The predictive efficacy of the identified proteins for AF was assessed using the area under the receiver operating characteristic curve, and their druggability was explored.
Data from 38 784 participants were included in this study. Incident AF cases were identified in the discovery cohort (1894; 5.5%) within a median follow-up of 14.5 years and in the replication cohort (451; 10.6%) within a median follow-up of 14.4 years. Twenty-one proteins linked to AF were identified in both cohorts. Specifically, COL4A1 (collagen IV α-1; odds ratio, 1.11 [95% CI, 1.04-1.19]; false discovery rate, 0.016) and RET (proto-oncogene tyrosine-protein kinase receptor Ret; odds ratio, 0.96 [95% CI, 0.94-0.98]; false discovery rate, 0.013) demonstrated a causal link with AF, and RET is druggable. COL4A1 improved the short- and long-term predictive performance of established AF models, as evidenced by significant enhancements in the area under the receiver operating characteristic, integrated discrimination improvement, and net reclassification index, all with values below 0.05.
COL4A1 and RET are associated with the development of AF. RET is identified as a potential drug target for AF prevention, while COL4A1 serves as a biomarker for AF prediction. Future studies are needed to evaluate the effectiveness of targeting these proteins to reduce AF risk.
目前，尚无可靠方法可用于预测和预防早期心房颤动（AF）。本研究旨在确定与 AF 相关的血浆蛋白，以发现生物标志物和潜在的药物靶点。
英国生物库制药蛋白质组学项目使用 Olink 平台检查了 2923 种循环蛋白，这构成了这项前瞻性队列研究的基础。英国生物库制药蛋白质组学项目包括一个随机选择的发现队列和联盟选择的复制队列。该研究的终点是通过代码确定的事件性 AF。使用 Cox 比例风险模型在两个队列中评估血浆蛋白与事件性 AF 之间的关联。在两个队列中都存在的蛋白质进行孟德尔随机化分析，利用 -蛋白数量性状基因座作为遗传工具来描绘因果关系。使用接收器操作特征曲线下的面积评估所确定的蛋白质对 AF 的预测效力，并探索其成药性。
这项研究纳入了 38784 名参与者的数据。在中位随访 14.5 年期间，在发现队列（1894 例；5.5%）中确定了事件性 AF 病例，在中位随访 14.4 年期间，在复制队列（451 例；10.6%）中确定了事件性 AF 病例。在两个队列中均发现了 21 种与 AF 相关的蛋白质。具体而言，COL4A1（胶原 IV α-1；优势比，1.11[95%置信区间，1.04-1.19]；假发现率，0.016）和 RET（原癌基因酪氨酸蛋白激酶受体 Ret；优势比，0.96[95%置信区间，0.94-0.98]；假发现率，0.013）与 AF 具有因果关系，并且 RET 可成药。COL4A1 改善了既定 AF 模型的短期和长期预测性能，这表现为接收器操作特征曲线下面积、综合判别改善和净重新分类指数的显著提高，所有这些都具有低于 0.05 的 值。
COL4A1 和 RET 与 AF 的发生有关。RET 被确定为预防 AF 的潜在药物靶点，而 COL4A1 则作为 AF 预测的生物标志物。需要进一步研究来评估针对这些蛋白以降低 AF 风险的有效性。
