OBJECTIVES: To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics.
METHOD: Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC).
RESULTS: The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0).
CONCLUSION: This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy.
METHODS: Warfarin relies on regular monitoring of International Normalized Ratio which is a standardized test to measure prothrombin time and appropriate dose adjustment. Pharmacometabonomics is a novel scientific field which deals with identification and quantification of the metabolites present in the metabolome using spectroscopic techniques such as Nuclear Magnetic Resonance (NMR). Pharmacometabonomics helps to indicate perturbation in the levels of metabolites in the cells and tissues due to drug or ingestion of any substance. NMR is one of the most widely-used spectroscopic techniques in metabolomics because of its reproducibility and speed.
RESULTS: There are many factors that influence the metabolism of warfarin, making changes in drug dosage common, and clinical factors like drug-drug interactions, dietary interactions and age explain for the most part the variability in warfarin dosing. Some studies have showed that pharmacogenetic testing for warfarin dosing does not improve health outcomes, and around 26% of the variation in warfarin dose requirements remains unexplained yet.
CONCLUSION: Many recent pharmacometabonomics studies have been conducted to identify novel biomarkers of drug therapies such as paracetamol, aspirin and simvastatin. Thus, a technique such as NMR based pharmacometabonomics to find novel biomarkers in plasma and urine might be useful to predict warfarin outcome.
AIM OF THE STUDY: To investigate the anti-hyperglycemic potential of AE through in-vitro enzymatic activities and streptozotocin-nicotinamide (STZ-NA) induced diabetic rat models using proton-nuclear magnetic resonance (1H-NMR)-based metabolomics approach.
MATERIALS AND METHODS: Anti-α-amylase and anti-α-glucosidase activities of the hydroethanolic extracts of AE were evaluated. The absolute quantification of bioactive constituents, using ultra-high performance liquid chromatography (UHPLC) was performed for the most active extract. Three different dosage levels of the AE extract were orally administered for 4 weeks consecutively in STZ-NA induced diabetic rats. Physical assessments, biochemical analysis, and an untargeted 1H-NMR-based metabolomics analysis of the urine and serum were carried out on the animal model.
RESULTS: Type 2 diabetes mellitus (T2DM) rat model was successfully developed based on the clear separation observed between the STZ-NA induced diabetic and normal non-diabetic groups. Discriminating biomarkers included glucose, citrate, succinate, allantoin, hippurate, 2-oxoglutarate, and 3-hydroxybutyrate, as determined through an orthogonal partial least squares-discriminant analysis (OPLS-DA) model. A treatment dosage of 250 mg/kg body weight (BW) of standardized 70% ethanolic AE extract mitigated increase in serum glucose, creatinine, and urea levels, providing treatment levels comparable to that obtained using metformin, with flavonoids primarily contribute to the anti-hyperglycemic activities. Urinary metabolomics disclosed that the following disturbed metabolism pathways: the citrate cycle (TCA cycle), butanoate metabolism, glycolysis and gluconeogenesis, pyruvate metabolism, and synthesis and degradation of ketone bodies, were ameliorated after treatment with the standardized AE extract.
CONCLUSIONS: This study demonstrated the first attempt at revealing the therapeutic effect of oral treatment with 250 mg/kg BW of standardized AE extract on chemically induced T2DM rats. The present study provides scientific evidence supporting the ethnomedicinal use of Ardisia elliptica and further advances the understanding of the fundamental molecular mechanisms affected by this herbal antidote.
METHODS: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort.
RESULTS: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis.
CONCLUSION: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.