ArticlePloS one2020
Urinary chemical fingerprint left behind by repeated NSAID administration: Discovery of putative biomarkers using artificial intelligence.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Investigation of the cortical bone metabolome of C57BL/6J mice with adenine-induced kidney disease.JBMR plus · 2026Article
- Integrated metabolomic and cytokine profiling reveals biomarkers across the clinical spectrum of lupus nephritis.Frontiers in immunology · 2026Article
- Identifying sex-linked metabolomic biomarkers in fish gonads after bacterial infection.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Early Markers of Cardiac and Skeletal Muscle Metabolic Derangement in the Apc(min/+) Male Mouse.Cancer reports (Hoboken, N.J.) · 2025Article
- Metabolomic profiling of VOC-driven interactions between Priestia megaterium and Bacillus licheniformis in a simulated rhizosphere using split petri dishes.Archives of microbiology · 2025Article
- A Review of Experimental Models of Feline Kidney Disease.Journal of the American Association for Laboratory Animal Science : JAALAS · 2025Review
- Integration of deep neural network modeling and LC-MS-based pseudo-targeted metabolomics to discriminate easily confused ginseng species.Journal of pharmaceutical analysis · 2025Article
- Review
- Comparison of serum SDMA and creatinine as a biomarker for the detection of meloxicam-induced kidney injury in cats.Frontiers in veterinary science · 2024Article
- Statistical methods and resources for biomarker discovery using metabolomics.BMC bioinformatics · 2023Review
- Potential progression biomarkers of diabetic kidney disease determined using comprehensive machine learning analysis of non-targeted metabolomics.Scientific reports · 2022Article
- In-depth characterisation of the urine metabolome in cats with and without urinary tract diseases.Metabolomics : Official journal of the Metabolomic Society · 2022Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction and early detection of kidney damage induced by nonsteroidal anti-inflammatories (NSAIDs) would provide the best chances of maximizing the anti-inflammatory effects while minimizing the risk of kidney damage. Unfortunately, biomarkers for detecting NSAID-induced kidney damage in cats remain to be discovered. To identify potential urinary biomarkers for monitoring NSAID-based treatments, we applied an untargeted metabolomics approach to urine collected from cats treated repeatedly with meloxicam or saline for up to 17 days. Applying multivariate analysis, this study identified a panel of seven metabolites that discriminate meloxicam treated from saline treated cats. Combining artificial intelligence machine learning algorithms and an independent testing urinary metabolome data set from cats with meloxicam-induced kidney damage, a panel of metabolites was identified and validated. The panel of metabolites including tryptophan, tyrosine, taurine, threonic acid, pseudouridine, xylitol and lyxitol, successfully distinguish meloxicam-treated and saline-treated cats with up to 75-100% sensitivity and specificity. This panel of urinary metabolites may prove a useful and non-invasive diagnostic tool for monitoring potential NSAID induced kidney injury in feline patients and may act as the framework for identifying urine biomarkers of NSAID induced injury in other species.
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