ArticleInternational urology and nephrology2021
Discovery of potential biomarkers in acute kidney injury by ultra-high-performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS).
Article in International urology and nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Metabolomics for the Identification of Biomarkers in Kidney Diseases.Nanotheranostics · 2025Review
- CKD Urine Metabolomics: Modern Concepts and Approaches.Pathophysiology : the official journal of the International Society for Pathophysiology · 2023Review
- Metabolomics in Acute Kidney Injury: The Clinical Perspective.Journal of clinical medicine · 2023Review
- Nicotinamide Adenine Dinucleotide Biosynthetic Impairment and Urinary Metabolomic Alterations Observed in Hospitalized Adults With COVID-19-Related Acute Kidney Injury.Kidney international reports · 2021Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveThe LC-MS/MS-based non-targeted metabolomics method was used to differentially screen serum and urine metabolites of acute kidney injury (AKI) patients and healthy people, to explore potential biomarkers of AKI and analyze related pathways, and explain the potential mechanism and biological significance of AKI.
methodsThe serum and urine samples from 30 AKI patients and 20 healthy people were selected to conduct a non-targeted metabolomics study by ultra-high-performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS). The differential metabolites between the two groups were searched by the human metabolome (HMDB) database ( https://hmdb.ca/ ) and the related pathways of these potential biomarkers were identified by searching the Kyoto encyclopedia of genes and genomes (KEGG) database ( https://www.kegg.jp/ ). The total metabolic pathways were analyzed by the MS Peaks to Pathways module of MetaboAnalyst ( https://www.metaboanalyst.ca/ ).
resultsMultivariate data analysis found that serum and urine metabolism in AKI patients was significantly different from healthy people. We found three metabolites in urine (2-S-glutathionyl glutathione acetate, 5-L-Glutamyl-taurine, and L-Phosphoarginine) contributing to the separation of AKI patients from healthy people, and major metabolic pathways associated with these potential biomarkers including cytochrome P450 metabolism, arginine, and proline metabolism.
conclusion2-S-glutathionyl glutathione acetate, 5-L-Glutamyl-taurine, and L-Phosphoarginine were associated with AKI patients, which could be selected as potential biomarkers to predicate AKI disease.
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