Evidence map›Paper›PMID 41999450›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2026

Untargeted urinary metabolomics reveals metabolic alterations and severity biomarkers in cardiac surgery-associated acute kidney injury.

Cheng-Chia Lee, Ya-Ju Hsieh, Chih-Hsiang Chang, Jau-Song Yu, Kuan-Hsing Chen, Cheng-Chieh Hung, Shao-Wei Chen, Wei-Ju Tu, Yi-Ting Chen

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Article in Metabolomics : Official journal of the Metabolomic Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Cheng-Chia Lee *Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Ya-Ju Hsieh *Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan.
Chih-Hsiang ChangKidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Jau-Song YuMolecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan.
Kuan-Hsing ChenKidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Cheng-Chieh HungKidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Shao-Wei ChenGraduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Wei-Ju TuDepartment of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Yi-Ting ChenKidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan. ytchen@mail.cgu.edu.tw.

Funding

Chang Gung Memorial Hospital CORPD1P0061National Science and Technology Council 113-2113-M-182-001, 113-2314-B-182-026, 114-2113-M-182-002, 114-2622-M-182-001National Science and Technology Council 113-2314-B-182A-032
6 · The paper itself

Abstract

introductionCardiac surgery-associated acute kidney injury (CS-AKI) is a frequent, serious complication linked to increased morbidity, mortality, and long-term kidney dysfunction. Progress in early detection and effective interventions remains limited, underscoring the need for novel biomarkers and therapeutic targets. Given the kidneys' high metabolic activity, metabolomics offers a powerful strategy to identify such markers and provide mechanistic insights.

objectivesOur goal is to investigate urinary metabolome alterations associated with CS-AKI.

methodsWe performed untargeted amine/phenol metabolomic profiling of urine samples collected within four hours post-surgery from 55 cardiac surgery patients (26 non-AKI, 29 AKI), using high-performance chemical isotope labeling and liquid chromatography-mass spectrometry (LC-MS). Multivariate analyses were applied to assess group separation and to evaluate the diagnostic performance of key metabolites.

resultsUrinary metabolomic profiles were significantly different between AKI and non-AKI patients. Of 1384 detected metabolites, 45 were differentially altered in AKI (defined by a fold change exceeding the mean ± 2 standard deviations, raw p < 0.05), with 25 metabolites annotated to known compounds. The most prominent metabolite, N-acetylputrescine (Log

conclusionsUntargeted urinary metabolomics distinguished AKI from non-AKI after cardiac surgery and identified distinct metabolic signatures associated with AKI severity. This work underscores the value of urinary metabolomics for revealing mechanistic pathways and identifying candidate biomarkers that may aid early diagnosis and monitoring of CS-AKI.

Indexed as

Acute Kidney InjuryBiomarkersCardiac Surgical ProceduresMetabolomicsAgedFemaleHumansLiquid Chromatography-Mass SpectrometryMaleMetabolomeMiddle AgedBiomarkersAcute kidney injuryBiomarker discoveryChemical isotope labelingDisease severityMetabolomicsPolyamine catabolism

Identifiers

PMID41999450
PMCPMC13091858

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.