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一种系统蛋白脂组学方法识别出新型循环系统生物标志物用于异常扩展性心肌病

Shubham Saha¹, Praveen Singh², Abhi Dutta¹

¹School of Biosciences and Bioengineering, IIT-Mandi, Mandi, India.

American journal of physiology. Heart and circulatory physiology

|December 4, 2025

概括

这项研究揭示了一种新的扩张性心肌病 (DCM) 的蛋白质脂质学特征,使用先进的奥米克和机器学习. 脂质和蛋白质 (B2M,CLEC3B) 的综合生物标记面板实现了0.99 AUC,在增强的DCM诊断中表现优于NT-proBNP.

科学领域:

心血管的奥米克斯 (Omics)
生物标志物发现发现
蛋白质脂类药物蛋白质脂类药物

背景情况:

扩张性心肌病 (DCM) 是心力衰竭的主要原因,目前标记者的诊断灵敏度有限.
心脏生理学中的脂质和蛋白质变化可能提供疾病特定的诊断见解.
对DCM进行全面的蛋白脂学研究和验证的生物标志物很少.

研究的目的:

使用整合性奥米学方法识别DCM的蛋白质脂质组签名.
为DCM诊断发现和验证新的蛋白质和脂质生物标志物.
开发一个多参数生物标记面板,以提高DCM的诊断准确性.

主要方法:

从360名参与者 (DCM患者和对照组) 的血样本的基于高分辨率质谱的整合性奥米克分析.
机器学习 (博鲁塔算法) 用于识别分辨脂质和蛋白质.
对于蛋白质生物标记物的ELISA验证 (β2-微型球蛋白[B2M],四菌素[CLEC3B]).
与脂质物种和氧化应激标志物 (8-OHdG) 的相关性分析.
综合接收器操作特征 (ROC) 分析以评估诊断性能.

主要成果:

在DCM血中鉴定出125种显著变化的脂质和10种蛋白质.
通过机器学习选择了39种脂质和10种蛋白质作为主要的歧视因子.
验证了B2M和CLEC3B作为DCM的显著蛋白质生物标志物.
一个由顶部脂质分辨器,B2M和CLEC3B组合的小组实现了0.99.9的AUC.
与NT-proBNP (AUC 0.96) 相比,开发的面板显示出更高的诊断准确性.

结论:

这项研究为DCM提供了第一个全面的蛋白质脂质体特征.
一个新的多参数生物标记面板,结合脂质 (如PA) 和蛋白质 (B2M,CLEC3B),为DCM提供了更高的诊断精度.
这些发现表明,在DCM病原发生过程中,已识别的生物标志物,氧化应激,亡和ECM重塑之间存在潜在的联系.

关键词:

生物标志物生物标志物扩张性心肌病症扩张性心肌病症脂质组的类型蛋白质组学蛋白质组学在scRNA测序过程中,scRNA测序

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