{"title":"脓毒症中线粒体和巨噬细胞极化相关生物标志物的鉴定和实验验证。","authors":"Liping She, Xiaojing Deng, Yeping Bian, Hui Cheng, Jian Xu","doi":"10.1155/emmi/8755175","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> Sepsis is a common and serious condition, where mitochondria and macrophage polarization play a crucial role. Therefore, this study aimed to identify and validate biomarkers for sepsis associated with mitochondria-related genes (MCRGs) and macrophage polarization-related genes (MPRGs), providing new targets and strategies for therapeutic intervention. <b>Methods:</b> This study utilized the GSE95233 and GSE28750 datasets. Initially, intersection genes were identified by overlapping MCRGs and the results from differential expression analysis and weighted gene co-expression network analysis (WGCNA). Biomarkers were identified through machine learning and gene expression analysis. A nomogram was developed and evaluated based on these biomarkers. Finally, functional enrichment, immune infiltration, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analyses were conducted to further elucidate the biological mechanisms underlying sepsis. <b>Results:</b> The study identified YME1L1, ECHDC3, THEM4, and COQ10A as biomarkers for sepsis. Among them, YME1L1, THEM4, and COQ10A showed significantly lower expression levels in sepsis samples, while ECHDC3 exhibited markedly higher expression. Notably, RT-qPCR analysis confirmed that YME1L1, THEM4, and COQ10A exhibited significantly lower expression levels in sepsis samples. A nomogram based on these biomarkers was developed and validated, effectively predicting sepsis risk. Enrichment analysis indicated that the biomarkers were co-enriched in the oxidative phosphorylation pathway. Additionally, 13 significantly different immune cell types were identified between sepsis and control samples. Biomarker association analysis revealed that CD8 T cells had the strongest positive correlation with YME1L1 (cor = 0.84, <i>p</i> < 0.05) and the strongest negative correlation with ECHDC3 (cor = -0.76, <i>p</i> < 0.05), suggesting their potential role in the disease mechanism. <b>Conclusion:</b> In this study, YME1L1, ECHDC3, THEM4, and COQ10A were identified as biomarkers for sepsis, with their expression levels validated in clinical samples. These findings provided a promising theoretical foundation for the development of targeted treatments for sepsis.</p>","PeriodicalId":11528,"journal":{"name":"Emergency Medicine International","volume":"2025 ","pages":"8755175"},"PeriodicalIF":1.2000,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105888/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification and Experimental Validation of Biomarkers Associated With Mitochondria and Macrophage Polarization in Sepsis.\",\"authors\":\"Liping She, Xiaojing Deng, Yeping Bian, Hui Cheng, Jian Xu\",\"doi\":\"10.1155/emmi/8755175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Background:</b> Sepsis is a common and serious condition, where mitochondria and macrophage polarization play a crucial role. Therefore, this study aimed to identify and validate biomarkers for sepsis associated with mitochondria-related genes (MCRGs) and macrophage polarization-related genes (MPRGs), providing new targets and strategies for therapeutic intervention. <b>Methods:</b> This study utilized the GSE95233 and GSE28750 datasets. Initially, intersection genes were identified by overlapping MCRGs and the results from differential expression analysis and weighted gene co-expression network analysis (WGCNA). Biomarkers were identified through machine learning and gene expression analysis. A nomogram was developed and evaluated based on these biomarkers. Finally, functional enrichment, immune infiltration, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analyses were conducted to further elucidate the biological mechanisms underlying sepsis. <b>Results:</b> The study identified YME1L1, ECHDC3, THEM4, and COQ10A as biomarkers for sepsis. Among them, YME1L1, THEM4, and COQ10A showed significantly lower expression levels in sepsis samples, while ECHDC3 exhibited markedly higher expression. Notably, RT-qPCR analysis confirmed that YME1L1, THEM4, and COQ10A exhibited significantly lower expression levels in sepsis samples. A nomogram based on these biomarkers was developed and validated, effectively predicting sepsis risk. Enrichment analysis indicated that the biomarkers were co-enriched in the oxidative phosphorylation pathway. Additionally, 13 significantly different immune cell types were identified between sepsis and control samples. Biomarker association analysis revealed that CD8 T cells had the strongest positive correlation with YME1L1 (cor = 0.84, <i>p</i> < 0.05) and the strongest negative correlation with ECHDC3 (cor = -0.76, <i>p</i> < 0.05), suggesting their potential role in the disease mechanism. <b>Conclusion:</b> In this study, YME1L1, ECHDC3, THEM4, and COQ10A were identified as biomarkers for sepsis, with their expression levels validated in clinical samples. These findings provided a promising theoretical foundation for the development of targeted treatments for sepsis.</p>\",\"PeriodicalId\":11528,\"journal\":{\"name\":\"Emergency Medicine International\",\"volume\":\"2025 \",\"pages\":\"8755175\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2025-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105888/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Emergency Medicine International\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1155/emmi/8755175\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"EMERGENCY MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emergency Medicine International","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1155/emmi/8755175","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0
摘要
背景:脓毒症是一种常见且严重的疾病,其中线粒体和巨噬细胞极化起着至关重要的作用。因此,本研究旨在鉴定和验证与线粒体相关基因(MCRGs)和巨噬细胞极化相关基因(MPRGs)相关的脓毒症生物标志物,为治疗干预提供新的靶点和策略。方法:本研究使用GSE95233和GSE28750数据集。最初,交叉基因是通过重叠的mcrg和差异表达分析和加权基因共表达网络分析(WGCNA)的结果来鉴定的。通过机器学习和基因表达分析鉴定生物标志物。基于这些生物标记物,我们开发并评估了一个nomogram。最后通过功能富集、免疫浸润和逆转录定量聚合酶链反应(RT-qPCR)分析进一步阐明脓毒症的生物学机制。结果:本研究确定了YME1L1、ECHDC3、THEM4和COQ10A作为脓毒症的生物标志物。其中,YME1L1、THEM4和COQ10A在脓毒症样本中表达水平显著降低,而ECHDC3在脓毒症样本中表达水平显著升高。值得注意的是,RT-qPCR分析证实,YME1L1、THEM4和COQ10A在脓毒症样本中的表达水平显著降低。基于这些生物标志物的nomogram被开发和验证,有效地预测脓毒症的风险。富集分析表明,这些生物标志物在氧化磷酸化途径中共富集。此外,在败血症和对照样本之间鉴定出13种显著不同的免疫细胞类型。生物标志物相关性分析显示,CD8 T细胞与YME1L1的正相关最强(cor = 0.84, p < 0.05),与ECHDC3的负相关最强(cor = -0.76, p < 0.05),提示其在疾病机制中的潜在作用。结论:在本研究中,YME1L1、ECHDC3、THEM4和COQ10A被确定为脓毒症的生物标志物,其表达水平在临床样本中得到验证。这些发现为脓毒症的靶向治疗提供了有希望的理论基础。
Identification and Experimental Validation of Biomarkers Associated With Mitochondria and Macrophage Polarization in Sepsis.
Background: Sepsis is a common and serious condition, where mitochondria and macrophage polarization play a crucial role. Therefore, this study aimed to identify and validate biomarkers for sepsis associated with mitochondria-related genes (MCRGs) and macrophage polarization-related genes (MPRGs), providing new targets and strategies for therapeutic intervention. Methods: This study utilized the GSE95233 and GSE28750 datasets. Initially, intersection genes were identified by overlapping MCRGs and the results from differential expression analysis and weighted gene co-expression network analysis (WGCNA). Biomarkers were identified through machine learning and gene expression analysis. A nomogram was developed and evaluated based on these biomarkers. Finally, functional enrichment, immune infiltration, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analyses were conducted to further elucidate the biological mechanisms underlying sepsis. Results: The study identified YME1L1, ECHDC3, THEM4, and COQ10A as biomarkers for sepsis. Among them, YME1L1, THEM4, and COQ10A showed significantly lower expression levels in sepsis samples, while ECHDC3 exhibited markedly higher expression. Notably, RT-qPCR analysis confirmed that YME1L1, THEM4, and COQ10A exhibited significantly lower expression levels in sepsis samples. A nomogram based on these biomarkers was developed and validated, effectively predicting sepsis risk. Enrichment analysis indicated that the biomarkers were co-enriched in the oxidative phosphorylation pathway. Additionally, 13 significantly different immune cell types were identified between sepsis and control samples. Biomarker association analysis revealed that CD8 T cells had the strongest positive correlation with YME1L1 (cor = 0.84, p < 0.05) and the strongest negative correlation with ECHDC3 (cor = -0.76, p < 0.05), suggesting their potential role in the disease mechanism. Conclusion: In this study, YME1L1, ECHDC3, THEM4, and COQ10A were identified as biomarkers for sepsis, with their expression levels validated in clinical samples. These findings provided a promising theoretical foundation for the development of targeted treatments for sepsis.
期刊介绍:
Emergency Medicine International is a peer-reviewed, Open Access journal that provides a forum for doctors, nurses, paramedics and ambulance staff. The journal publishes original research articles, review articles, and clinical studies related to prehospital care, disaster preparedness and response, acute medical and paediatric emergencies, critical care, sports medicine, wound care, and toxicology.