Hu Kaibo, Shi Ao, Shu Yuan, Sudesh Shivon, Ling Jitao, Chen Yixuan, Hua Fuzhou, Yu Shuchun, Zhang Jing, Yu Peng
Department of Endocrinology and Metabolism, second Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China.
The second Clinical Medical College, Nanchang University, Nanchang, People's Republic of China.
J Inflamm Res. 2025 Mar 15;18:3829-3842. doi: 10.2147/JIR.S509089. eCollection 2025.
Sepsis, a life-threatening inflammatory condition due to an imbalanced response to infections, has been a major concern. Necroptosis, a newly discovered programmed cell death form, plays a crucial role in various inflammatory diseases. Our study aims to identify necroptosis - related genes (NRGs) and explore their potential for sepsis diagnosis.
We used weighted gene co-expression network analysis to identify gene modules associated with sepsis. Cox regression and Kaplan-Meier methods were employed to assess the diagnostic and prognostic value of these genes. Single-cell and immune infiltration analyses were carried out to explore the immune environment in sepsis. Plasma CD74 protein levels were quantified in our samples, and relevant clinical data from electronic patient records were analyzed for correlation.
CD74 was identified through the intersection of the hub genes of sepsis and NRGs related modules. Septic patients had lower CD74 expression compared to healthy controls. The CD74-based diagnostic model showed better performance in the training dataset (AUC, 0.79 [95% CI, 0.75-0.84]), was cross-validated in external datasets, and demonstrated better performances than other published diagnostic models. Pathway analysis and single-cell profiling supported further exploration of CD74-related inflammation and immune response in sepsis.
This study presents the first quantitative assessment of human plasma CD74 in sepsis patients. CD74 levels were significantly lower in the sepsis cohort. CD74 warrants further exploration as a potential prognostic and therapeutic target for sepsis.
脓毒症是一种因对感染反应失衡而危及生命的炎症状态，一直是主要关注点。坏死性凋亡是一种新发现的程序性细胞死亡形式，在各种炎症性疾病中起关键作用。我们的研究旨在识别与坏死性凋亡相关的基因（NRGs），并探索它们在脓毒症诊断中的潜力。
我们使用加权基因共表达网络分析来识别与脓毒症相关的基因模块。采用Cox回归和Kaplan-Meier方法评估这些基因的诊断和预后价值。进行单细胞和免疫浸润分析以探索脓毒症中的免疫环境。对我们样本中的血浆CD74蛋白水平进行定量，并分析电子病历中的相关临床数据以寻找相关性。
通过脓毒症核心基因与NRGs相关模块的交集鉴定出CD74。与健康对照相比，脓毒症患者的CD74表达较低。基于CD74的诊断模型在训练数据集中表现更好（AUC，0.79 [95% CI，0.75 - 0.84]），在外部数据集中进行了交叉验证，并且比其他已发表的诊断模型表现更好。通路分析和单细胞分析支持进一步探索脓毒症中与CD74相关的炎症和免疫反应。
本研究首次对脓毒症患者的人血浆CD74进行了定量评估。脓毒症队列中的CD74水平显著降低。CD74作为脓毒症潜在的预后和治疗靶点值得进一步探索。
