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已发表论文
基于超高效液相色谱 - 四极杆飞行时间质谱的代谢组学分析揭示了儿童感染性休克的潜在生物标志物及代谢改变
Authors Xiao C, Wang C , Wang S, Xu F, Chen Y
Received 5 July 2025
Accepted for publication 19 October 2025
Published 11 November 2025 Volume 2025:18 Pages 15645—15655
DOI https://doi.org/10.2147/JIR.S551775
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Anh Ngo
Changxue Xiao,* Chenhao Wang,* Sa Wang, Feng Xu, Yingfu Chen
Department of Critical Care Medicine, Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yingfu Chen, Department of Critical Care Medicine, Children’s Hospital of Chongqing Medical University, No. 136, 2nd Zhongshan Road, Yuzhong District, Chongqing, 400014, People’s Republic of China, Email chenyfpicu@163.com
Purpose: Septic shock is a major cause of mortality in pediatric intensive care units (PICU). This study aimed to investigate metabolic alterations in PICU patients with septic shock using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) to identify potential biomarkers and unique metabolic pathways for early diagnosis and improved treatment strategies.
Patients and Methods: Serum and urine samples from septic shock survivors (SS), septic shock non-survivors (SNS), and non-infected systemic inflammatory response syndrome (SIRS) patients were analyzed using UPLC-QTOF/MS. All differential metabolites from serum samples were subjected to multiple regression analysis. Bioinformatics analysis was conducted on metabolite data obtained from urine and serum samples of the SS and SNS groups to further investigate differences in metabolic pathways.
Results: Combinational metabolites demonstrated superior diagnostic performance compared with individual metabolites, with an area under the receiver operating characteristic curve (AUC) of 0.925 for SS vs SIRS and 0.901 for SNS vs SIRS. Key metabolic pathways, including glycerophospholipid metabolism, arginine and proline metabolism, were implicated in the development of septic shock. Importantly, alterations in glutamine and glutamate metabolism were associated with survival, suggesting the significant potential for further investigation.
Conclusion: Metabolomic profiling using UPLC-QTOF/MS represents a promising approach for early diagnosis of pediatric septic shock. The identified biomarkers and metabolic pathways provide insights into the pathogenic mechanisms and may assist in the development of targeted therapeutic strategies. Further validation in larger, prospective cohorts is required before clinical application.
Keywords: metabolomics, biomarker, metabolic pathways, septic shock, pediatric
Department of Critical Care Medicine, Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yingfu Chen, Department of Critical Care Medicine, Children’s Hospital of Chongqing Medical University, No. 136, 2nd Zhongshan Road, Yuzhong District, Chongqing, 400014, People’s Republic of China, Email chenyfpicu@163.com
Purpose: Septic shock is a major cause of mortality in pediatric intensive care units (PICU). This study aimed to investigate metabolic alterations in PICU patients with septic shock using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) to identify potential biomarkers and unique metabolic pathways for early diagnosis and improved treatment strategies.
Patients and Methods: Serum and urine samples from septic shock survivors (SS), septic shock non-survivors (SNS), and non-infected systemic inflammatory response syndrome (SIRS) patients were analyzed using UPLC-QTOF/MS. All differential metabolites from serum samples were subjected to multiple regression analysis. Bioinformatics analysis was conducted on metabolite data obtained from urine and serum samples of the SS and SNS groups to further investigate differences in metabolic pathways.
Results: Combinational metabolites demonstrated superior diagnostic performance compared with individual metabolites, with an area under the receiver operating characteristic curve (AUC) of 0.925 for SS vs SIRS and 0.901 for SNS vs SIRS. Key metabolic pathways, including glycerophospholipid metabolism, arginine and proline metabolism, were implicated in the development of septic shock. Importantly, alterations in glutamine and glutamate metabolism were associated with survival, suggesting the significant potential for further investigation.
Conclusion: Metabolomic profiling using UPLC-QTOF/MS represents a promising approach for early diagnosis of pediatric septic shock. The identified biomarkers and metabolic pathways provide insights into the pathogenic mechanisms and may assist in the development of targeted therapeutic strategies. Further validation in larger, prospective cohorts is required before clinical application.
Keywords: metabolomics, biomarker, metabolic pathways, septic shock, pediatric