ArticleIranian journal of basic medical sciences2020
NMR-based plasma metabolic profiling in patients with unstable angina.
Article in Iranian journal of basic medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Metabolomic profiles of being physically active and less sedentary: a critical review.Metabolomics : Official journal of the Metabolomic Society · 2021Pooled it
- Recent progress in metabolomic analysis of acute coronary syndrome: a narrative review.Cardiovascular diagnosis and therapy · 2025Review
- Multi-Omics Research on Angina Pectoris: A Novel Perspective.Aging and disease · 2024Review
- Defining Acute Coronary Syndrome through Metabolomics.Metabolites · 2021Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
objectivesUnstable angina (UA) is a form of the acute coronary syndrome (ACS) that affects more than a third of the population before age 70. Due to the limitations of diagnostic tests, appropriate identification of UA is difficult. In this study, we proceeded to investigate metabolite profiling in UA patients compared with controls to determine potential candidate biomarkers. MATERIALS AND
methodsNinety-four plasma samples from UA and 32 samples from controls were analyzed based on 1H NMR spectroscopy. The raw data were processed, analyzed, and subjected to partial least squares-discrimination analysis (PLS-DA), a supervised classification method with a good separation of control and UA patients was observed. The most important variables (VIP) ≥1 were selected and submitted to MetaboAnalyst pathway enrichment to identify the most important ones.
resultsWe identified 17 disturbed metabolites in UA patients in comparison with the controls. These metabolites are involved in various biochemical pathways such as steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, and lysine degradation. Some of the metabolites were deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, and 2-methoxyestrone. In order to determine test applicability in diagnosing UA, a diagnostic model was further created using the receiver operator characteristic (ROC) curve. The areas under the curve (AUC), sensitivity, specificity, and precision were 0.87, 90%, 65%, and 91%, respectively, for diagnosing of UA.
conclusionThese metabolites could not only be useful for the diagnosis of UA patients but also provide more information for further deciphering of the biological processes of UA.
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