METHODS: A cross sectional study was conducted on three groups: individuals with alcohol use disorders (n=30), social drinkers (n=54) and alcohol-naive controls (n=60). 1H NMR-based metabolomics was used to obtain the metabolic profiles of plasma samples. Data were processed by multivariate principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) followed by univariate and multivariate logistic regressions to produce the best fit-model for discrimination between groups.
RESULTS: The OPLS-DA model was able to distinguish between the AUD group and the other groups with high sensitivity, specificity and accuracy of 64.29%, 98.17% and 91.24% respectively. The logistic regression model identified two biomarkers in plasma (propionic acid and acetic acid) as being significantly associated with alcohol use disorders. The reproducibility of all biomarkers was excellent (0.81-1.0).
CONCLUSIONS: The applied plasma metabolomics technique was able to differentiate the metabolites between AUD and the other groups. These metabolites are potential novel biomarkers for diagnosis of alcohol use disorders.
PURPOSE: This study provides new insights on the changes of endogenous metabolites caused by I. aquatica ethanolic extract and improves the understanding on the therapeutic efficacy and mechanism of I. aquatica ethanolic extract.
METHODS: By using a combination of 1H nuclear magnetic resonance (NMR) with multivariate analysis (MVDA), the changes of metabolites due to I. aquatica ethanolic extract administration in obese diabetic-induced Sprague Dawley rats (OB+STZ+IA) were identified.
RESULTS: The results suggested 19 potential biomarkers with variable importance projections (VIP) above 0.5, which include creatine/creatinine, glucose, creatinine, citrate, carnitine, 2-oxoglutarate, succinate, hippurate, leucine, 1-methylnicotinamice (MNA), taurine, 3-hydroxybutyrate (3-HB), tryptophan, lysine, trigonelline, allantoin, formiate, acetoacetate (AcAc) and dimethylamine. From the changes in the metabolites, the affected pathways and aspects of metabolism were identified.
CONCLUSION: I. aquatica ethanolic extract increases metabolite levels such as creatinine/creatine, carnitine, MNA, trigonelline, leucine, lysine, 3-HB and decreases metabolite levels, including glucose and tricarboxylic acid (TCA) intermediates. This implies capabilities of I. aquatica ethanolic extract promoting glycolysis, gut microbiota and nicotinate/nicotinamide metabolism, improving the glomerular filtration rate (GFR) and reducing the β-oxidation rate. However, the administration of I. aquatica ethanolic extract has several drawbacks, such as unimproved changes in amino acid metabolism, especially in reducing branched chain amino acid (BCAA) synthesis pathways and lipid metabolism.
METHODS: The N. oleracea fractions were obtained using solid phase extraction (SPE). A metabolomics approach that coupled the use of proton nuclear magnetic resonance (1H NMR) with multivariate data analysis (MVDA) was applied to distinguish the metabolite variations among the N. oleracea fractions, as well as to assess the correlation between metabolite variation and the studied bioactivities (DPPH free radical scavenging and α-glucosidase inhibitory activities). The bioactive fractions were then subjected to ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) analysis to profile and identify the potential bioactive constituents.
RESULTS: The principal component analysis (PCA) discriminated EF and MF from the other fractions with the higher distributions of phenolics. Partial least squares (PLS) analysis revealed a strong correlation between the phenolics and the studied bioactivities in the EF and the MF. The UHPLC-MS/MS profiling of EF and MF had tentatively identified the phenolics present. Together with some non-phenolic metabolites, a total of 37 metabolites were tentatively assigned.
CONCLUSIONS: The findings of this work supported that N. oleracea is a rich source of phenolics that can be potential antioxidants and α-glucosidase inhibitors for the management of diabetes. To our knowledge, this study is the first report on the metabolite-bioactivity correlation and UHPLC-MS/MS analysis of N. oleracea fractions.