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机器学习驱动的基于血液的生物标志物和治疗药物识别,用于个性化缺血性中风管理。

Machine Learning-Driven Identification of Blood-Based Biomarkers and Therapeutic Agents for Personalized Ischemic Stroke Management.

作者信息

Liu Jing, Bai Congxia, Yang Haitao, Song Li, Xu Haochen, Sun Yingying, Suo Miaomiao, Gao Ziyu, Li Hao, Wang Feng, Chen Jingzhou

机构信息

State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China.

Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.

出版信息

J Cardiovasc Transl Res. 2025 Jul 22. doi: 10.1007/s12265-025-10635-w.

DOI:10.1007/s12265-025-10635-w
PMID:40694178
Abstract

Ischemic stroke (IS) is the most common subtype of stroke. However, reliable blood biomarkers for early diagnosis remain unavailable. This study developed a predictive model based on peripheral blood (PB) biomarkers. PB samples from two independent cohorts including IS patients and healthy controls (CTR) were analyzed by RNA sequencing (RNA-seq). 69 mRNAs were consistently and significantly dysregulated in IS patients. Functional enrichment analysis revealed that the IS phenotype was negatively associated with NK cell-mediated cytotoxicity and single-sample gene set enrichment analysis (ssGSEA) revealed a significant reduction in Cd56 NK cells, Cd56 NK cells, and NKT cells in IS patients. A four-gene diagnostic model-BCL2A1, FAM200B, IGJ, and TXN-was identified and exhibited high diagnostic accuracy across derivation, validation, and external cohorts (AUCs: 0.94, 0.91, and 0.96, respectively). Additionally, potential small molecule compounds were screened using Enrichr database, among which cytochalasin D may represent a novel candidate drug for IS treatment.

摘要

缺血性中风(IS)是中风最常见的亚型。然而,仍没有可用于早期诊断的可靠血液生物标志物。本研究基于外周血(PB)生物标志物开发了一种预测模型。通过RNA测序(RNA-seq)分析了来自包括IS患者和健康对照(CTR)的两个独立队列的PB样本。69种mRNA在IS患者中持续且显著失调。功能富集分析表明,IS表型与NK细胞介导的细胞毒性呈负相关,单样本基因集富集分析(ssGSEA)显示IS患者中Cd56 NK细胞、Cd56 NK细胞和NKT细胞显著减少。鉴定出一个四基因诊断模型——BCL2A1、FAM200B、IGJ和TXN——在推导、验证和外部队列中均表现出高诊断准确性(AUC分别为0.94、0.91和0.96)。此外,使用Enrichr数据库筛选了潜在的小分子化合物,其中细胞松弛素D可能代表一种用于IS治疗的新型候选药物。

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本文引用的文献

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The immunology of stroke and dementia.中风与痴呆的免疫学
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Neuronal plasma biomarkers in acute ischemic stroke.急性缺血性卒中的神经元血浆生物标志物
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Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.基于RNA测序和机器学习的脑出血诊断免疫相关生物标志物的鉴定
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Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke: The MARVEL Randomized Clinical Trial.甲泼尼龙作为大血管闭塞性卒中血管内血栓切除术辅助治疗的疗效:MARVEL随机临床试验
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Neuroinflammation in Acute Ischemic and Hemorrhagic Stroke.急性缺血性和出血性卒中性神经炎症。
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