Zhang Lu, Yue Lei, Jia Peng, Cheng Ziqi, Liu Jiwen
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Department of Neurology, Shangrao Municipal Hospital, Shangrao, Jiangxi, China.
Front Cell Dev Biol. 2025 Apr 17;13:1582252. doi: 10.3389/fcell.2025.1582252. eCollection 2025.
Ischemic stroke (IS) represents a significant contributor to morbidity and mortality globally. The relationship between IS and mitochondrial unfolded protein response was presently uncertain. This study endeavors to explore the fundamental mechanism of in IS by utilizing bioinformatics methods.
In GSE58294, differentially expressed genes (DEGs) were obtained, which were overlapped with key module genes of -related gene ( -RGs) for producing candidate genes. The biomarkers were identified from the candidate genes through machine learning, expression validation, and receiver operating characteristic (ROC) curves. In order to verify the biomarkers, reverse transcription-quantitative PCR (RT-qPCR) experiments were performed on human peripheral blood. Subsequently, a predictive nomogram was created to estimate the likelihood of developing IS. Next, the mechanisms and functions related to the biomarkers were explored by enrichment analysis and immune infiltration. In addition, cells enriched with biomarkers were identified, and the biological processes involved in these cells were analyzed through intercellular communication analysis and virtual knockout experiments.
MCEMP1, CACNA1E, and CLEC4D were identified as biomarkers and subsequently validated by RT-qPCR. RT-qPCR revealed that CLEC4D is the most sensitive biomarker. The nomogram analysis revealed that these biomarkers possess strong diagnostic value. Immune infiltration analysis indicated that all three biomarkers are strongly correlated with neutrophils. Additionally, in the single-cell transcriptome data, these biomarkers were predominantly enriched in neutrophils. Compared to the sham group, the middle cerebral artery occlusion (MCAO) group exhibited enhanced immune-inflammatory responses. Virtual knockout experiments provide preliminary evidence that CLEC4D functions as a regulatory molecule in neutrophil-mediated inflammation, rather than serving merely as a passive marker.
CLEC4D was identified as the most sensitive biomarker for IS related to -RGs, offering a new reference for IS diagnosis and treatment.
缺血性中风（IS）是全球发病和死亡的重要原因。目前，IS与线粒体未折叠蛋白反应之间的关系尚不确定。本研究旨在利用生物信息学方法探索IS的基本机制。
在GSE58294中获得差异表达基因（DEG），将其与线粒体相关基因（MTR - RGs）的关键模块基因进行重叠，以产生候选基因。通过机器学习、表达验证和受试者工作特征（ROC）曲线从候选基因中鉴定生物标志物。为了验证生物标志物，对人外周血进行逆转录定量PCR（RT - qPCR）实验。随后，创建预测列线图以估计发生IS的可能性。接下来，通过富集分析和免疫浸润探索与生物标志物相关的机制和功能。此外，鉴定富含生物标志物的细胞，并通过细胞间通讯分析和虚拟敲除实验分析这些细胞中涉及的生物学过程。
MCEMP1、CACNA1E和CLEC4D被鉴定为生物标志物，随后通过RT - qPCR进行验证。RT - qPCR显示CLEC4D是最敏感的生物标志物。列线图分析表明这些生物标志物具有很强的诊断价值。免疫浸润分析表明，所有三种生物标志物均与中性粒细胞密切相关。此外，在单细胞转录组数据中，这些生物标志物主要富集于中性粒细胞。与假手术组相比，大脑中动脉闭塞（MCAO）组表现出增强的免疫炎症反应。虚拟敲除实验提供了初步证据，表明CLEC4D在中性粒细胞介导的炎症中起调节分子的作用，而不仅仅是作为一个被动标记。
CLEC4D被鉴定为与MTR - RGs相关的IS最敏感生物标志物，为IS的诊断和治疗提供了新的参考。
