The Journal of surgical research · 2026
Metabolomics Profiles and Prognostic Biomarkers in Sepsis Survivors and Nonsurvivors.
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Xu Jing, Huang Zhou, Li He, Han Xiaotong, Liu Yanjuan, Zhang Xingwen, Li Jincheng, Yang Jie, Huang Zhengzhuang, Huang Dongling, Wang Fan, Wei Wanxia, Wang Wei
Аннотация
INTRODUCTION: Sepsis imposes an overwhelming global critical care burden, contributing to an estimated 49 million annual deaths worldwide. Although multiple sepsis-related metabolic profiles have been characterized in prior research, no metabolomic biomarkers have yet entered routine clinical prognostic practice. This study aimed to identify actionable serum metabolite biomarkers to stratify 28-d mortality risk among adult sepsis patients.
METHODS: We performed high-resolution untargeted serum metabolomics to profile molecular signatures across three cohorts: 60 sepsis nonsurvivors, 60 sepsis survivors, and 20 age- and sex-matched healthy controls (HCs). Supervised partial least squares discriminant analysis implemented via MetaboAnalyst 5.0 was used to screen differential circulating metabolites. Receiver operating characteristic curve analysis quantified the predictive performance of candidate metabolites for sepsis mortality. The correlations between differential metabolite concentrations and clinical laboratory/severity indices were analyzed using R software.
RESULTS: Partial least squares discriminant analysis models demonstrated clear metabolic separation among HCs, sepsis survivors, and nonsurvivors. Pairwise comparison identified 1092 differential metabolites between survivors and HCs, 757 metabolites between survivors and nonsurvivors, and 1230 metabolites between nonsurvivors and HCs. A core set of 200 mortality-linked metabolites was enriched in five canonical Kyoto Encyclopedia of Genes and Genomes pathways: steroid hormone biosynthesis, lysine degradation, starch and sucrose metabolism, riboflavin metabolism, and pantothenate/coenzyme A biosynthesis. Five metabolites exhibited superior prognostic power relative to conventional clinical markers: tsangane L-3-glucoside, 5-L-glutamyl-L-alanine, 15-methyl-15S-PGE2, allysine, and 4-nitrophenol. These analytes displayed strong linear correlations with validated disease severity and organ dysfunction biomarkers, supporting their utility as mortality prognostic indicators.
CONCLUSION: Distinct serum metabolomic landscapes differentiate healthy individuals, sepsis survivors, and fatal sepsis patients. Tsangane L-3-glucoside, 5-L-glutamyl-L-alanine, 15-methyl-15S-PGE2, allysine, and 4-nitrophenol represent promising preliminary candidate biomarkers to early discriminate sepsis patients at high risk of 28-d mortality.
METHODS: We performed high-resolution untargeted serum metabolomics to profile molecular signatures across three cohorts: 60 sepsis nonsurvivors, 60 sepsis survivors, and 20 age- and sex-matched healthy controls (HCs). Supervised partial least squares discriminant analysis implemented via MetaboAnalyst 5.0 was used to screen differential circulating metabolites. Receiver operating characteristic curve analysis quantified the predictive performance of candidate metabolites for sepsis mortality. The correlations between differential metabolite concentrations and clinical laboratory/severity indices were analyzed using R software.
RESULTS: Partial least squares discriminant analysis models demonstrated clear metabolic separation among HCs, sepsis survivors, and nonsurvivors. Pairwise comparison identified 1092 differential metabolites between survivors and HCs, 757 metabolites between survivors and nonsurvivors, and 1230 metabolites between nonsurvivors and HCs. A core set of 200 mortality-linked metabolites was enriched in five canonical Kyoto Encyclopedia of Genes and Genomes pathways: steroid hormone biosynthesis, lysine degradation, starch and sucrose metabolism, riboflavin metabolism, and pantothenate/coenzyme A biosynthesis. Five metabolites exhibited superior prognostic power relative to conventional clinical markers: tsangane L-3-glucoside, 5-L-glutamyl-L-alanine, 15-methyl-15S-PGE2, allysine, and 4-nitrophenol. These analytes displayed strong linear correlations with validated disease severity and organ dysfunction biomarkers, supporting their utility as mortality prognostic indicators.
CONCLUSION: Distinct serum metabolomic landscapes differentiate healthy individuals, sepsis survivors, and fatal sepsis patients. Tsangane L-3-glucoside, 5-L-glutamyl-L-alanine, 15-methyl-15S-PGE2, allysine, and 4-nitrophenol represent promising preliminary candidate biomarkers to early discriminate sepsis patients at high risk of 28-d mortality.