Trial reportLipids in health and disease2018
Untargeted metabolomic on urine samples after α-lipoic acid and/or eicosapentaenoic acid supplementation in healthy overweight/obese women.
Trial report in Lipids in health and disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01138774 (Cellular and Molecular Effects of Lipoic Acid and Eicosapentaenoic Acid), which is not on this map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Cellular and Molecular Effects of Lipoic Acid and Eicosapentaenoic Acid (EPA) on Adipose Tissue: Potential Application in Human Obesity
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.
- Alpha-lipoic acid on intermediate disease markers in overweight or obese adults: a systematic review and meta-analysis.BMJ open · 2025Pooled it
- Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies.Metabolomics : Official journal of the Metabolomic Society · 2019Pooled it
- Effects of Long-Chain n-3 Fatty Acids Supplementation During Caloric Restriction on Body Composition in Overweight and Obese Adults: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.Food science & nutrition · 2025Review
- Guidance and Position of RINN22 regarding Precision Nutrition and Nutriomics.Lifestyle genomics · 2025Review
- Changes in urinary metabolomic profile show the effectiveness of a nutritional intervention in children 6-12 years old: The ALINFA study.Food science & nutrition · 2024Article
- Nutritional supplements improve cardiovascular risk factors in overweight and obese patients: A Bayesian network meta-analysis.Frontiers in nutrition · 2023Article
- Metabolomics prospect of obesity and metabolic syndrome; a systematic review.Journal of diabetes and metabolic disorders · 2022Review
- Chitosan Nanoparticles Containing Lipoic Acid with Antioxidant Properties as a Potential Nutritional Supplement.Animals : an open access journal from MDPI · 2022Article
- Metabolomics as a potential tool for the diagnosis of growth hormone deficiency (GHD): a review.Archives of endocrinology and metabolism · 2021Review
- Mechanics Insights of Alpha-Lipoic Acid against Cardiovascular Diseases during COVID-19 Infection.International journal of molecular sciences · 2021Review
- Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics.Metabolites · 2020Article
- Insights on the Use of α-Lipoic Acid for Therapeutic Purposes.Biomolecules · 2019Review
- Diet, Gut Microbiota, and Obesity: Links with Host Genetics and Epigenetics and Potential Applications.Advances in nutrition (Bethesda, Md.) · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundEicosapentaenoic acid (EPA) and α-lipoic acid (α-LA) have been investigated for their beneficial effects on obesity and cardiovascular risk factors. In the current research, the goal was to evaluate metabolomic changes following the dietary supplementation of these two lipids, alone or combined in healthy overweight/obese sedentary women following an energy-restricted diet. For this purpose, an untargeted metabolomics approach was conducted on urine samples using liquid chromatography coupled with time of flight mass spectrometry (HPLC-TOF-MS).
methodsThis is a short-term double blind placebo-controlled study with a parallel nutritional design that lasted 10 weeks. Participants were assigned to one of the 4 experimental groups [Control, EPA (1.3 g/d), α-LA (0.3 g/d) and EPA+α-LA (1.3 g/d + 0.3 g/d)]. All intervention groups followed an energy-restricted diet of 30% less than total energy expenditure. Clinically relevant biochemical measurements were analyzed. Urine samples (24 h) were collected at baseline and after 10 weeks. Untargeted metabolomic analysis on urine samples was carried out, and principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were performed for the pattern recognition and characteristic metabolites identification.
resultsUrine samples were scattered in the PCA scores plots in response to the supplementation with α-LA. Totally, 28 putative discriminant metabolites in positive ionization, and 6 in negative ionization were identified among groups clearly differentiated according to the α-LA administration. Remarkably is the presence of an ascorbate intermediate metabolite (one of the isomers of trihydroxy-dioxohexanoate, or dihydroxy-oxohexanedionate) in the groups supplemented with α-LA. This fact might be associated with antioxidant properties of both α-LA and ascorbic acid. Correlations between phenotypical parameters and putative metabolites of provided additional information on whether there is a direct or inverse relationship between them. Especially interesting are the negative correlation between ascorbate intermediate metabolite and asymmetric dimethylarginine (ADMA) and the positive one between superoxide dismutase (SOD) and α-LA supplementation.
conclusionsThis metabolomic approach supports that the beneficial effects of α-LA administration on body weight reduction may be partly explained by the antioxidant properties of this organosulfur carboxylic acid mediated by isomers of trihydroxy-dioxohexanoate, or dihydroxy-oxohexanedionate.
trial registrationClinicaltrials.gov NCT01138774 .
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Registered trials
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.