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Additionally, the unclear pathogenesis of sepsis after trauma contributes to its high morbidity and mortality. Identifying early predictive and diagnostic biomarkers, as well as exploring related metabolic pathways, is crucial for improving early prevention, diagnosis, and treatment. This study prospectively analyzed plasma samples from patients with severe trauma collected between March 2022 and November 2023. Trauma patients were divided into two groups based on whether they developed sepsis within two weeks: the TDDS group (trauma patients who did not develop sepsis) and the TDS group (trauma patients who did develop sepsis). Plasma samples from the TDS group were collected at the time of sepsis diagnosis (Sepsis group). Metabolite concentrations were measured using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS\/MS) through untargeted metabolomics. From the differential metabolites between the TDS and TDDS groups, we identified five significant metabolites (all area under the curve (AUC)\u2009\u2265\u20090.94) as early predictive biomarkers for sepsis after trauma: (1) docosatrienoic acid, (2) 7-alpha-carboxy-17-alpha-carboxyethylandrostan lactone phenyl ester, (3) sphingomyelin (SM) 8:1;2O\/26:1, (4) N1-[1-(3-isopropenylphenyl)-1-methylethyl]-3-oxobutanamide, and (5) SM 34:2;2O. Furthermore, five significant metabolites (all AUC\u2009\u2265\u20090.85) were identified as early diagnostic biomarkers from the comparison between the TDS and TDDS groups: (1) lysophosphatidylcholine (LPC) O-22:1, (2) LPC O-22:0, (3) uric acid, (4) LPC O-24:2, and (5) LPC 22:0-SN1. 26 metabolites shared between two comparisons (TDS vs. TDDS and sepsis vs. TDS) were identified. Of which, 19 metabolites belong to lipid metabolism. The top three metabolic pathways related to sepsis after trauma under the impact of severe trauma were: (1) glycerophospholipid metabolism, (2) porphyrin metabolism, and (3) sphingolipid metabolism. The top three metabolic pathways related to sepsis after trauma under the impact of infection were: (1) caffeine metabolism, (2) biosynthesis of unsaturated fatty acids, and (3) steroid hormone biosynthesis. Our study identified early predictive and diagnostic biomarkers and explored metabolic pathways related to sepsis after trauma. These findings provide a foundation for future research on the onset and development of sepsis, facilitating its early prevention, diagnosis, and treatment based on specific metabolites and metabolic pathways.<\/jats:p>","DOI":"10.1038\/s41598-025-92631-3","type":"journal-article","created":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T19:34:19Z","timestamp":1744140859000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Identifying early predictive and diagnostic biomarkers and exploring metabolic pathways for sepsis after trauma based on an untargeted metabolomics approach"],"prefix":"10.1038","volume":"15","author":[{"given":"Yi","family":"Gou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo-Hui","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun-Fei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng-Ming","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Ping","family":"Hei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing-Jing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian-Zhong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,8]]},"reference":[{"issue":"1","key":"92631_CR1","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1186\/s13054-017-1757-3","volume":"21","author":"H Zhang","year":"2017","unstructured":"Zhang, H. et al. 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