肥厚性心肌病
医学
心房颤动
内科学
接收机工作特性
置信区间
心脏病学
蛋白质组学
心肌病
心力衰竭
基因
生物化学
化学
作者
H. Hartman,Nina Harano,Lusha W. Liang,Kohei Hasegawa,Mathew S. Maurer,Albree Tower‐Rader,Michael A. Fifer,Muredach P. Reilly,Yuichi J. Shimada
出处
期刊:Europace
[Oxford University Press]
日期:2024-10-23
标识
DOI:10.1093/europace/euae267
摘要
Abstract Background and Aims Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), increasing symptom burden and stroke risk. We aimed to construct a plasma proteomics-based model to predict new-onset AF in patients with HCM and determine dysregulated signaling pathways. Methods In this prospective, multi-center cohort study, we conducted plasma proteomics profiling of 4,986 proteins at enrollment. We developed a proteomics-based machine learning (ML) model to predict new-onset AF using samples from one institution (training set) and tested its predictive ability using independent samples from another institution (test set). We performed a survival analysis to compare the risk of new-onset AF among high- and low-risk groups in the test set. We performed pathway analysis of proteins significantly (univariable p<0.05) associated with new-onset AF using a false discovery rate (FDR) threshold of 0.001. Results The study included 284 patients with HCM (training set: 193, test set: 91). Thirty-seven (13%) patients developed AF during median follow-up of 3.2 years [25–75 percentile: 1.8-5.2]. Using the proteomics-based prediction model developed in the training set, the area under the receiver-operating-characteristic curve (AUC) was 0.89 (95% confidence interval 0.78-0.99) in the test set. In the test set, patients categorized as high-risk had a higher rate of developing new-onset AF (log-rank p=0.002). The Ras-MAPK pathway was dysregulated in patients who developed incident AF during follow-up (FDR<1.0×10-6). Conclusion This is the first study to demonstrate the ability of plasma proteomics to predict new-onset AF in HCM and identify dysregulated signaling pathways.
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