Exploring Infantile Epileptic Spasm Syndrome: A Proteomic Analysis of Plasma Using the Data-Independent Acquisition Approach.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Journal of Proteome Research Pub Date : 2024-06-10 DOI:10.1021/acs.jproteome.4c00298
Haohua Huang, Dezhi Cao, Yan Hu, Qianqian He, Xia Zhao, Li Chen, Sufang Lin, Xufeng Luo, Yuanzhen Ye, Jianxiang Liao, Huafang Zou, Dongfang Zou
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Abstract

This study aimed to identify characteristic proteins in infantile epileptic spasm syndrome (IESS) patients' plasma, offering insights into potential early diagnostic biomarkers and its underlying causes. Plasma samples were gathered from 60 patients with IESS and 40 healthy controls. Data-independent acquisition proteomic analysis was utilized to identify differentially expressed proteins (DEPs). These DEPs underwent functional annotation through Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Gene set enrichment analysis (GSEA) was employed for both GO (GSEA-GO) and KEGG (GSEA-KEGG) analyses to examine the gene expression profiles. Receiver operating characteristic (ROC) curves assessed biomarkers' discriminatory capacity. A total of 124 DEPs were identified in IESS patients' plasma, mainly linked to pathways, encompassing chemokines, cytokines, and oxidative detoxification. GSEA-GO and GSEA-KEGG analyses indicated significant enrichment of genes associated with cell migration, focal adhesion, and phagosome pathways. ROC curve analysis demonstrated that the combination of PRSS1 and ACTB, PRSS3, ACTB, and PRSS1 alone exhibited AUC values exceeding 0.7. This study elucidated the significant contribution of cytokines, chemokines, oxidative detoxification, and phagosomes to the IESS pathogenesis. The combination of PRSS1 and ACTB holds promise as biomarkers for the early diagnosis of IESS.

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探索婴儿癫痫痉挛综合征:利用数据独立获取法对血浆进行蛋白质组分析
本研究旨在确定婴儿癫痫痉挛综合征(IESS)患者血浆中的特征蛋白,从而为潜在的早期诊断生物标记物及其潜在病因提供见解。研究人员采集了60名IESS患者和40名健康对照者的血浆样本。利用独立于数据的采集蛋白质组分析来识别差异表达蛋白质(DEPs)。这些差异表达蛋白通过基因本体(GO)和京都基因组百科全书(KEGG)通路富集分析进行功能注释。GO(GSEA-GO)和KEGG(GSEA-KEGG)分析均采用了基因组富集分析(GSEA)来研究基因表达谱。接收者操作特征曲线(ROC)评估了生物标志物的判别能力。在IESS患者的血浆中总共发现了124个DEPs,主要与趋化因子、细胞因子和氧化解毒等通路有关。GSEA-GO和GSEA-KEGG分析表明,与细胞迁移、病灶粘附和吞噬细胞通路相关的基因显著富集。ROC 曲线分析表明,PRSS1 和 ACTB 的组合、PRSS3、ACTB 和 PRSS1 本身的 AUC 值均超过了 0.7。这项研究阐明了细胞因子、趋化因子、氧化解毒和吞噬体在 IESS 发病机制中的重要作用。PRSS1 和 ACTB 的组合有望成为 IESS 早期诊断的生物标记物。
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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
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