ArticleAvicenna journal of medical biotechnology
A Metabolomic Study to Identify Potential Tissue Biomarkers for Indomethacin-Induced Gastric Ulcer in Rats.
Article in Avicenna journal of medical biotechnology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The trial behind it
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- COVID-19: A Systematic Review of Metabolomics Data and Predicting Potential Biomarkers Based on Pathway Analysis.Tanaffos · 2025Review
- Dysregulation of amino acids balance as potential serum-metabolite biomarkers for diagnosis and prognosis of diabetic retinopathy: a metabolomics study.Journal of diabetes and metabolic disorders · 2024Article
- Gastroprotective Effect of 2,3-Dimethylquinoxaline Against Indomethacin-Induced Gastric Ulcer in Rat.Journal of inflammation research · 2024Article
- Protective effect ofFrontiers in medicine · 2024Article
- Chemical components and protective effects ofWorld journal of gastroenterology · 2023Article
- Metabolomic Studies for Metabolic Alterations Induced by Non-Steroidal Anti-Inflammatory Drugs: Mini Review.Biomolecules · 2021Review
- Antimicrobial Activity ofJournal of inflammation research · 2021Article
- UPLC-Q-TOF/MS-Based Serum and Urine Metabonomics Study on the Ameliorative Effects of Palmatine onFrontiers in pharmacology · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric Ulcer (GU) is the most prevalent gastrointestinal disorder induced by various factors and Non-Steroid Anti-Inflammatory Drugs (NSAIDs) as one of the most common reasons. Due to the absence of appropriate molecular markers for GU, the aim of this study was to utilize a metabolomics approach in order to find potential metabolite markers for the disease.
methodsStomach tissue samples from indomethacin-treated rats and normal controls were used to perform a 1H-NMR metabolomics study. The altered metabolites were identified using random forest multivariate analysis.
resultsROC curves showed that the random forest model had a good predictive performance with AUC of 1 for the test and 0.708 for the training sets. Seventeen differentially expressed metabolites were found between GU and normal tissue sample. These metabolites included trimethylamine, betaine, carnitine, methionine, acetylcho line, choline, N,N-Dimethylglycine, cis-aconitate, tryptophan, spermidine, acetylcarnitine, creatinine, pantothenate, taurine, isoleucine, glucose and kynurenine.
conclusionThe results of the study demonstrated that metabolomics approach could serve as a viable method to find potential markers for GU. Surely, further studies are needed for the validation of the results.
Indexed as
Identifiers
31908738PMC6925398W2979467448What OpenQuestion holds
Registered trials
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