Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

Background
Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.
Methods and Results
Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972) discriminated between HFrEF patients (N = 94, sensitivity = 93.6%) and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%). Interestingly, HFrEF103 showed low sensitivity (12.6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.
Conclusion
CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

研究背景
射血分数降低型心力衰竭（heart failure with reduced ejection fraction, HFrEF）的生物标志物发现与病理生理学新认知，或可从近年来高通量尿液蛋白质组学的技术进展中获得突破，有望推动HFrEF的诊断、风险分层与临床管理水平提升。
研究方法与结果
采用在线毛细管电泳-电喷雾电离微型飞行时间质谱（CE-MS）对尿液样本进行分析，以获取个体尿液蛋白质组图谱。在初始生物标志物发现队列中，对33例HFrEF患者与29例年龄、性别匹配的非HFrEF个体的尿液蛋白质组图谱进行分析，共鉴定出103种在HFrEF患者中排泄水平存在显著差异的肽段。以此103种肽段为基础，构建了基于支持向量机的HFrEF分类器HFrEF103。在后续验证队列中，HFrEF103展现出极高的区分效能（曲线下面积AUC=0.972）：可准确区分94例HFrEF患者与552例合并或不合并肾功能受损及高血压的对照个体，其灵敏度为93.6%，特异度为92.9%。值得注意的是，HFrEF103对176例左心室舒张功能障碍个体的识别灵敏度仅为12.6%。与HFrEF相关的肽类生物标志物主要包含I型与III型纤维状胶原蛋白片段，此外还涉及纤维蛋白原β亚基、α1-抗胰蛋白酶等蛋白的片段。
研究结论
基于CE-MS的尿液蛋白质组分析可作为一种高灵敏度的检测手段，用以鉴定大量与HFrEF相关的尿液肽类生物标志物，这将有助于深化我们对心力衰竭的认知并提升其诊断水平。