血清蛋白质组分析揭示了脑血管病的病理机制和生物标志物候选物。

IF 4.3 2区 医学 Q1 CLINICAL NEUROLOGY Translational Stroke Research Pub Date : 2025-10-01 Epub Date: 2025-02-11 DOI:10.1007/s12975-025-01332-6
Yun-Chao Wang, Hang-Hang Zhu, Liu-Chang He, Ya-Ting Yao, Lei Zhang, Xin-Li Xue, Jing-Yi Li, Li Zhang, Bo Song, Chang-He Shi, Yu-Sheng Li, Yuan Gao, Jing-Hua Yang, Yu-Ming Xu
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引用次数: 0

摘要

脑血管病(CSVD)是一种以一系列临床、神经影像学和神经病理表现为特征的全球性脑疾病。然而,CSVD的分子病理生理机制尚未深入研究。基于液相色谱-串联质谱技术的蛋白质组学在生物医学领域具有广阔的应用前景。它用于阐明疾病相关的分子过程和病理生理途径,从而为探索CSVD的病理生理机制提供了重要契机。从郑州大学第一附属医院连续招募96名受试者(CSVD患者58名,对照组38名)进行血清采集。去除高丰度蛋白后,使用高分辨率质谱分析血清样本。利用生物信息学方法对获得的蛋白质组学数据进行深入分析,并通过实验对结果进行验证。与对照组相比,CSVD组血清中有52种蛋白表达差异。此外,分析表明,这些差异表达蛋白通过参与补体和凝血级联反应的过度激活以及胰岛素样生长因子结合蛋白的失调,参与了CSVD。结合临床特征,通过机器学习模型识别的蛋白质组学生物标志物面板有望促进CSVD的诊断(AUC = 0.947, 95% CI = 0.895-0.978)。该研究是迄今为止最深入的CSVD蛋白质组学研究,提示补体级联的过度激活和IGFBP对- IGF的失调可能与CSVD的发生和进展密切相关,为开发外周血生物标志物提供了可能,并为CSVD的生物学基础提供了新的见解。
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Proteome Profiling of Serum Reveals Pathological Mechanisms and Biomarker Candidates for Cerebral Small Vessel Disease.

Cerebral small vessel disease (CSVD) is a global brain disorder that is characterized by a series of clinical, neuroimaging, and neuropathological manifestations. However, the molecular pathophysiological mechanisms of CSVD have not been thoroughly investigated. Liquid chromatography-tandem mass spectrometry-based proteomics has broad application prospects in biomedicine. It is used to elucidate disease-related molecular processes and pathophysiological pathways, thus providing an important opportunity to explore the pathophysiological mechanisms of CSVD. Serum samples were obtained from 96 participants (58 with CSVD and 38 controls) consecutively recruited from The First Affiliated Hospital of Zhengzhou University. After removing high-abundance proteins, the serum samples were analyzed using high-resolution mass spectrometry. Bioinformatics methods were used for in-depth analysis of the obtained proteomic data, and the results were verified experimentally. Compared with the control group, 52 proteins were differentially expressed in the sera of the CSVD group. Furthermore, analyses indicated the involvement of these differentially expressed proteins in CSVD through participation in the overactivation of complement and coagulation cascades and dysregulation of insulin-like growth factor-binding proteins. The proteomic biomarker panel identified by the machine learning model combined with clinical features is expected to facilitate the diagnosis of CSVD (AUC = 0.947, 95% CI = 0.895-0.978). The study is the most in-depth study on CSVD proteomics to date and suggests that the overactivation of the complement cascade and the dysregulation of IGFBP on- IGF may be closely correlated with the occurrence and progression of CSVD, offering the potential to develop peripheral blood biomarkers and providing new insights into the biological basis of CSVD.

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来源期刊
Translational Stroke Research
Translational Stroke Research CLINICAL NEUROLOGY-NEUROSCIENCES
CiteScore
13.80
自引率
4.30%
发文量
130
审稿时长
6-12 weeks
期刊介绍: Translational Stroke Research covers basic, translational, and clinical studies. The Journal emphasizes novel approaches to help both to understand clinical phenomenon through basic science tools, and to translate basic science discoveries into the development of new strategies for the prevention, assessment, treatment, and enhancement of central nervous system repair after stroke and other forms of neurotrauma. Translational Stroke Research focuses on translational research and is relevant to both basic scientists and physicians, including but not restricted to neuroscientists, vascular biologists, neurologists, neuroimagers, and neurosurgeons.
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