Jiang Linghui, Chen Shiyu, Li Shichao, Wang Jiaxing, Chen Wannan, Shi Yuncen, Xiong Wanxia, Miao Changhong
Department of Anaesthesiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Perioper Med (Lond). 2024 Jul 24;13(1):81. doi: 10.1186/s13741-024-00438-z.
Early diagnosis and prediction of organ dysfunction are critical for intervening and improving the outcomes of septic patients. The study aimed to find novel diagnostic and predictive biomarkers of organ dysfunction for perioperative septic patients.
This is a prospective, controlled, preliminary, and single-center study of emergency surgery patients. Mass spectrometry, Gene Ontology (GO) functional analysis, and the protein-protein interaction (PPI) network were performed to identify the differentially expressed proteins (DEPs) from sepsis patients, which were selected for further verification via enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was used to estimate the relative correlation of selected serum protein levels and clinical outcomes of septic patients. Calibration curves were plotted to assess the calibration of the models.
Five randomized serum samples per group were analyzed via mass spectrometry, and 146 DEPs were identified. GO functional analysis and the PPI network were performed to evaluate the molecular mechanisms of the DEPs. Six DEPs were selected for further verification via ELISA. Cathepsin B (CatB), vascular cell adhesion protein 1 (VCAM-1), neutrophil gelatinase-associated lipocalin (NGAL), protein S100-A9, prosaposin, and thrombospondin-1 levels were significantly increased in the patients with sepsis compared with those of the controls (p < 0.001). Logistic regression analysis showed that CatB, S100-A9, VCAM-1, prosaposin, and NGAL could be used for preoperative diagnosis and postoperative prediction of organ dysfunction. CatB and S100-A9 were possible predictive factors for preoperative diagnosis of renal failure in septic patients. Internal validation was assessed using the bootstrapping validation. The preoperative diagnosis of renal failure model displayed good discrimination with a C-index of 0.898 (95% confidence interval 0.843-0.954) and good calibration.
Serum CatB, S100-A9, VCAM-1, prosaposin, and NGAL may be novel markers for preoperative diagnosis and postoperative prediction of organ dysfunction. Specifically, S100-A9 and CatB were indicators of preoperative renal dysfunction in septic patients. Combining these two biomarkers may improve the accuracy of predicting preoperative septic renal dysfunction.
The study was registered at the Chinese Clinical Trials Registry (ChiCTR2200060418) on June 1, 2022.
器官功能障碍的早期诊断和预测对于干预和改善脓毒症患者的预后至关重要。本研究旨在寻找围手术期脓毒症患者器官功能障碍的新型诊断和预测生物标志物。
这是一项针对急诊手术患者的前瞻性、对照、初步和单中心研究。采用质谱分析、基因本体(GO)功能分析和蛋白质-蛋白质相互作用(PPI)网络来鉴定脓毒症患者中差异表达的蛋白质(DEPs),并通过酶联免疫吸附测定(ELISA)对其进行进一步验证。采用逻辑回归分析来评估所选血清蛋白水平与脓毒症患者临床结局的相对相关性。绘制校准曲线以评估模型的校准情况。
每组分析5份随机血清样本,共鉴定出146个DEPs。进行GO功能分析和PPI网络分析以评估DEPs的分子机制。选择6个DEPs通过ELISA进行进一步验证。与对照组相比,脓毒症患者组织蛋白酶B(CatB)、血管细胞黏附蛋白1(VCAM-1)、中性粒细胞明胶酶相关脂质运载蛋白(NGAL)、蛋白S100-A9、prosaposin和血小板反应蛋白-1水平显著升高(p < 0.001)。逻辑回归分析表明,CatB、S100-A9、VCAM-1、prosaposin和NGAL可用于术前诊断和术后器官功能障碍的预测。CatB和S100-A9可能是脓毒症患者术前肾衰竭诊断的预测因素。使用自举验证评估内部验证。术前肾衰竭模型显示出良好的区分度,C指数为0.898(95%置信区间0.843 - 0.954),校准良好。
血清CatB、S100-A9、VCAM-1、prosaposin和NGAL可能是术前诊断和术后器官功能障碍预测的新型标志物。具体而言,S100-A9和CatB是脓毒症患者术前肾功能障碍的指标。联合这两种生物标志物可能提高术前脓毒症性肾衰竭预测的准确性。
该研究于2022年6月1日在中国临床试验注册中心(ChiCTR)注册(注册号:ChiCTR2200060418)。