医学
生命银行
孟德尔随机化
前瞻性队列研究
队列
危险系数
优势比
内科学
队列研究
外显子组
生物信息学
肿瘤科
遗传学
置信区间
外显子组测序
遗传变异
突变
生物
基因
基因型
作者
Xiaodong Peng,Yukun Li,Nian Liu,Shijun Xia,Wei Wang,Yiwei Lai,Liu He,Caihua Sang,Jianzeng Dong,Changsheng Ma
出处
期刊:Circulation-arrhythmia and Electrophysiology
[Ovid Technologies (Wolters Kluwer)]
日期:2024-10-02
标识
DOI:10.1161/circep.124.013037
摘要
BACKGROUND: 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. METHODS: 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 International Classification of Diseases, Tenth Revision 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 cis -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. RESULTS: Data from 53 032 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 P values below 0.05. CONCLUSIONS: 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.
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