Identification of Immune-Related Genes as Potential Biomarkers in Early Septic Shock.

IF 2.5 4区 医学 Q3 ALLERGY
International Archives of Allergy and Immunology Pub Date : 2025-01-01 Epub Date: 2024-09-30 DOI:10.1159/000540949
Beibei Liu, Yonghua Fan, Xianjing Zhang, Huaqing Li, Fei Gao, Wenli Shang, Juntao Hu, Zhanhong Tang
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引用次数: 0

Abstract

Introduction: Septic shock, a severe manifestation of infection-induced systemic immune response, poses a critical threat resulting in life-threatening multi-organ failure. Early diagnosis and intervention are imperative due to the potential for irreversible organ damage. However, specific and sensitive detection tools for the diagnosis of septic shock are still lacking.

Methods: Gene expression files of early septic shock were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT analysis was used to evaluate immune cell infiltration. Genes related to immunity and disease progression were identified using weighted gene co-expression network analysis (WGCNA), followed by enrichment analysis. CytoHubba was then employed to identify hub genes, and their relationships with immune cells were explored through correlation analysis. Blood samples from healthy controls and patients with early septic shock were collected to validate the expression of hub genes, and an external dataset was used to validate their diagnostic efficacy.

Results: Twelve immune cells showed significant infiltration differences in early septic shock compared to control, such as neutrophils, M0 macrophages, and natural killer cells. The identified immune and disease-related genes were mainly enriched in immune, cell signaling, and metabolism pathways. In addition, six hub genes were identified (PECAM1, F11R, ITGAL, ICAM3, HK3, and MCEMP1), all significantly associated with M0 macrophages and exhibiting an area under curve of over 0.7. These genes exhibited abnormal expression in patients with early septic shock. External datasets and real-time qPCR validation supported the robustness of these findings.

Conclusion: Six immune-related hub genes may be potential biomarkers for early septic shock.

Introduction: Septic shock, a severe manifestation of infection-induced systemic immune response, poses a critical threat resulting in life-threatening multi-organ failure. Early diagnosis and intervention are imperative due to the potential for irreversible organ damage. However, specific and sensitive detection tools for the diagnosis of septic shock are still lacking.

Methods: Gene expression files of early septic shock were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT analysis was used to evaluate immune cell infiltration. Genes related to immunity and disease progression were identified using weighted gene co-expression network analysis (WGCNA), followed by enrichment analysis. CytoHubba was then employed to identify hub genes, and their relationships with immune cells were explored through correlation analysis. Blood samples from healthy controls and patients with early septic shock were collected to validate the expression of hub genes, and an external dataset was used to validate their diagnostic efficacy.

Results: Twelve immune cells showed significant infiltration differences in early septic shock compared to control, such as neutrophils, M0 macrophages, and natural killer cells. The identified immune and disease-related genes were mainly enriched in immune, cell signaling, and metabolism pathways. In addition, six hub genes were identified (PECAM1, F11R, ITGAL, ICAM3, HK3, and MCEMP1), all significantly associated with M0 macrophages and exhibiting an area under curve of over 0.7. These genes exhibited abnormal expression in patients with early septic shock. External datasets and real-time qPCR validation supported the robustness of these findings.

Conclusion: Six immune-related hub genes may be potential biomarkers for early septic shock.

鉴定作为早期脓毒性休克潜在生物标志物的免疫相关基因
导言:脓毒性休克是由感染引起的全身免疫反应的一种严重表现,会导致多器官功能衰竭,危及生命。由于可能造成不可逆的器官损伤,早期诊断和干预势在必行。然而,目前仍缺乏诊断脓毒性休克的特异性和敏感性检测工具:方法:从基因表达总库(GEO)数据库中获取早期脓毒性休克的基因表达文件。CIBERSORT分析用于评估免疫细胞浸润。利用加权基因共表达网络分析(WGCNA)确定与免疫和疾病进展相关的基因,然后进行富集分析。然后使用 CytoHubba 来确定枢纽基因,并通过相关性分析探讨它们与免疫细胞的关系。收集健康对照组和早期脓毒性休克患者的血液样本来验证中心基因的表达,并使用外部数据集来验证其诊断效果:结果:与对照组相比,12种免疫细胞在早期脓毒性休克中出现了明显的浸润差异,如中性粒细胞、M0巨噬细胞和自然杀伤细胞。鉴定出的免疫和疾病相关基因主要富集在免疫、细胞信号传导和新陈代谢通路中。此外,还发现了六个枢纽基因(PECAM1、F11R、ITGAL、ICAM3、HK3 和 MCEMP1),它们都与 M0 巨噬细胞显著相关,曲线下面积超过 0.7。这些基因在早期脓毒性休克患者中表现出异常表达。外部数据集和实时 qPCR 验证证实了这些发现的可靠性:结论:六个免疫相关枢纽基因可能是早期脓毒性休克的潜在生物标记物。
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来源期刊
CiteScore
5.60
自引率
3.60%
发文量
105
审稿时长
2 months
期刊介绍: ''International Archives of Allergy and Immunology'' provides a forum for basic and clinical research in modern molecular and cellular allergology and immunology. Appearing monthly, the journal publishes original work in the fields of allergy, immunopathology, immunogenetics, immunopharmacology, immunoendocrinology, tumor immunology, mucosal immunity, transplantation and immunology of infectious and connective tissue diseases.
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