Zhang Yidan, Wu Shaoduo, Li Xiaoyan
Department of Respiratory and Critical Care Medicine, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, Shanxi, China.
Department of Pulmonary Critical Care Medicine, Zhoupu Hospital in Pudong New Area, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Front Med (Lausanne). 2025 Apr 30;12:1496834. doi: 10.3389/fmed.2025.1496834. eCollection 2025.
The aim of this study is to investigate the differential expression and diagnostic value of ferroptosis-related genes in coronavirus-associated viral sepsis.
This study was conducted in two sequential phases: (1) identification of differentially expressed genes through comprehensive analysis of the experimental dataset (GSE164805); and (2) clinical validation of the candidate molecular markers using both test set samples and clinical samples, followed by rigorous evaluation of their diagnostic performance. Firstly, the microchips associated with coronavirus-associated viral sepsis were retrieved from the GEO database, a public data platform of NCBI (National Center for Biotechnology Information), and differentially expressed genes (DEGs) were obtained through differential analysis. The identified DEGs were then intersected with the ferroptosis gene dataset to obtain ferroptosis-related DEGs. Subsequently, molecular signaling pathways of ferroptosis-related genes in coronavirus-associated viral sepsis were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. CIBERSORT was employed to analyze immune cell infiltration in both the coronavirus-associated viral sepsis group and control group. Furthermore, a protein-protein interaction (PPI) network was constructed to identify hub genes involved in ferroptosis. Finally, the expression of ferroptosis hub genes in coronavirus-associated viral sepsis and its diagnostic value were analyzed in validation set GSE199816 and clinical case samples.
In test set GSE164805, a total of 15,059 differentially expressed genes (DEGs) were identified, comprising 7,458 up-regulated and 7,601 down-regulated genes. Subsequently, an intersection analysis with the ferroptosis gene dataset yielded 189 DEGs associated with ferroptosis. Functional enrichment analyses using GO and KEGG revealed significant enrichment in signaling pathways related to ferroptosis, oxidative stress, and HIF-1. Additionally, CIBERSORT immune-infiltration analysis revealed enhanced infiltration of innate immune cells but reduced infiltration of CD8 T cells and natural killer (NK) cells in the coronavirus-associated viral sepsis group compared with healthy controls. Furthermore, analysis identified that the distribution of these immune cells correlated with the expression levels of IL1-β and HMOX1, suggesting that viral infection in the septic pathological state disrupts the balance between immune activation and suppression. Notably, PPI network analysis also identified IL1-β and HMOX1 as hub genes involved in ferroptosis. Finally, the results were verified in the validation set and clinical case samples, and the results showed that the expressions of IL1-β and HMOX1 in the coronavirus-associated viral sepsis group were decreased compared with the case control group and the healthy control group. In clinical samples, the expression levels were as follows: IL1-β (0.390 ± 0.068 vs. 1.101 ± 0.107), HMOX1 (0.629 ± 0.117 vs. 1.101 ± 0.107), and the differences were statistically significant (all < 0.05). Further diagnostic performance analysis demonstrated that IL1-β and HMOX1 exhibited AUROCs of 0.892 and 0.765, respectively, indicating their robust diagnostic potential for coronavirus-associated viral sepsis.
The present study has successfully identified two hub genes, IL1-β and HMOX1, associated with ferroptosis in coronavirus-associated viral sepsis, and their expression and diagnostic value for the disease. These findings provide effective diagnostic biomarkers and potential therapeutic targets for coronavirus-associated viral sepsis. Notably, this study specifically focused on coronavirus-induced viral sepsis, distinct from previously characterized bacterial sepsis and other viral etiologies, thus warranting future studies with expanded sample sizes for stratified analyses.
本研究旨在探讨铁死亡相关基因在冠状病毒相关病毒性脓毒症中的差异表达及诊断价值。
本研究分两个阶段进行：（1）通过对实验数据集（GSE164805）的综合分析鉴定差异表达基因；（2）使用测试集样本和临床样本对候选分子标志物进行临床验证，随后严格评估其诊断性能。首先，从美国国立生物技术信息中心（NCBI）的公共数据平台基因表达综合数据库（GEO）中检索与冠状病毒相关病毒性脓毒症相关的微芯片，并通过差异分析获得差异表达基因（DEG）。然后将鉴定出的DEG与铁死亡基因数据集进行交集分析，以获得与铁死亡相关的DEG。随后，使用基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析来分析冠状病毒相关病毒性脓毒症中铁死亡相关基因的分子信号通路。采用CIBERSORT分析冠状病毒相关病毒性脓毒症组和对照组中的免疫细胞浸润情况。此外，构建蛋白质-蛋白质相互作用（PPI）网络以鉴定参与铁死亡的枢纽基因。最后，在验证集GSE199816和临床病例样本中分析冠状病毒相关病毒性脓毒症中铁死亡枢纽基因的表达及其诊断价值。
在测试集GSE164805中，共鉴定出15,059个差异表达基因，其中7,458个上调基因和7,601个下调基因。随后，与铁死亡基因数据集进行交集分析，得到189个与铁死亡相关的DEG。使用GO和KEGG进行的功能富集分析显示，与铁死亡、氧化应激和缺氧诱导因子-1相关的信号通路有显著富集。此外，CIBERSORT免疫浸润分析显示，与健康对照组相比，冠状病毒相关病毒性脓毒症组中固有免疫细胞浸润增强，但CD8 T细胞和自然杀伤（NK）细胞浸润减少。此外，分析发现这些免疫细胞的分布与白细胞介素-1β（IL1-β）和血红素加氧酶-1（HMOX1）的表达水平相关，表明脓毒症病理状态下的病毒感染破坏了免疫激活与抑制之间的平衡。值得注意的是，PPI网络分析也将IL1-β和HMOX1鉴定为参与铁死亡的枢纽基因。最后，在验证集和临床病例样本中验证了结果，结果显示冠状病毒相关病毒性脓毒症组中IL1-β和HMOX1的表达与病例对照组和健康对照组相比降低。在临床样本中，表达水平如下：IL1-β（0.390±0.068对1.101±0.107），HMOX1（0.629±0.117对1.101±0.107），差异具有统计学意义（均<0.05）。进一步的诊断性能分析表明，IL1-β和HMOX1的曲线下面积（AUC）分别为0.892和0.765，表明它们对冠状病毒相关病毒性脓毒症具有强大的诊断潜力。
本研究成功鉴定出两个与冠状病毒相关病毒性脓毒症中铁死亡相关的枢纽基因IL1-β和HMOX1，以及它们对该疾病的表达和诊断价值。这些发现为冠状病毒相关病毒性脓毒症提供了有效的诊断生物标志物和潜在的治疗靶点。值得注意的是，本研究专门关注冠状病毒引起的病毒性脓毒症，不同于先前表征的细菌性脓毒症和其他病毒病因，因此需要未来进行更大样本量的分层分析研究。
